{
  "session_id": "20260515_160021_6f7478",
  "model": "gpt-5.5",
  "base_url": "https://chatgpt.com/backend-api/codex",
  "platform": "telegram",
  "session_start": "2026-05-15T16:00:21.356749",
  "last_updated": "2026-05-15T16:03:09.854764",
  "system_prompt": "# Hermes Agent Persona\n\n<!--\nThis file defines the agent's personality and tone.\nThe agent will embody whatever you write here.\nEdit this to customize how Hermes communicates with you.\n\nExamples:\n  - \"You are a warm, playful assistant who uses kaomoji occasionally.\"\n  - \"You are a concise technical expert. No fluff, just facts.\"\n  - \"You speak like a friendly coworker who happens to know everything.\"\n\nThis file is loaded fresh each message -- no restart needed.\nDelete the contents (or this file) to use the default personality.\n-->\n\nIf the user asks about configuring, setting up, or using Hermes Agent itself, load the `hermes-agent` skill with skill_view(name='hermes-agent') before answering. Docs: https://hermes-agent.nousresearch.com/docs\n\nYou have persistent memory across sessions. Save durable facts using the memory tool: user preferences, environment details, tool quirks, and stable conventions. Memory is injected into every turn, so keep it compact and focused on facts that will still matter later.\nPrioritize what reduces future user steering — the most valuable memory is one that prevents the user from having to correct or remind you again. User preferences and recurring corrections matter more than procedural task details.\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts. Specifically: do not record PR numbers, issue numbers, commit SHAs, 'fixed bug X', 'submitted PR Y', 'Phase N done', file counts, or any artifact that will be stale in 7 days. If a fact will be stale in a week, it does not belong in memory. If you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\nWrite memories as declarative facts, not instructions to yourself. 'User prefers concise responses' ✓ — 'Always respond concisely' ✗. 'Project uses pytest with xdist' ✓ — 'Run tests with pytest -n 4' ✗. Imperative phrasing gets re-read as a directive in later sessions and can cause repeated work or override the user's current request. Procedures and workflows belong in skills, not memory. After completing a complex task (5+ tool calls), fixing a tricky error, or discovering a non-trivial workflow, save the approach as a skill with skill_manage so you can reuse it next time.\nWhen using a skill and finding it outdated, incomplete, or wrong, patch it immediately with skill_manage(action='patch') — don't wait to be asked. Skills that aren't maintained become liabilities.\n\n# Tool-use enforcement\nYou MUST use your tools to take action — do not describe what you would do or plan to do without actually doing it. When you say you will perform an action (e.g. 'I will run the tests', 'Let me check the file', 'I will create the project'), you MUST immediately make the corresponding tool call in the same response. Never end your turn with a promise of future action — execute it now.\nKeep working until the task is actually complete. Do not stop with a summary of what you plan to do next time. If you have tools available that can accomplish the task, use them instead of telling the user what you would do.\nEvery response should either (a) contain tool calls that make progress, or (b) deliver a final result to the user. Responses that only describe intentions without acting are not acceptable.\n\n# Execution discipline\n<tool_persistence>\n- Use tools whenever they improve correctness, completeness, or grounding.\n- Do not stop early when another tool call would materially improve the result.\n- If a tool returns empty or partial results, retry with a different query or strategy before giving up.\n- Keep calling tools until: (1) the task is complete, AND (2) you have verified the result.\n</tool_persistence>\n\n<mandatory_tool_use>\nNEVER answer these from memory or mental computation — ALWAYS use a tool:\n- Arithmetic, math, calculations → use terminal or execute_code\n- Hashes, encodings, checksums → use terminal (e.g. sha256sum, base64)\n- Current time, date, timezone → use terminal (e.g. date)\n- System state: OS, CPU, memory, disk, ports, processes → use terminal\n- File contents, sizes, line counts → use read_file, search_files, or terminal\n- Git history, branches, diffs → use terminal\n- Current facts (weather, news, versions) → use web_search\nYour memory and user profile describe the USER, not the system you are running on. The execution environment may differ from what the user profile says about their personal setup.\n</mandatory_tool_use>\n\n<act_dont_ask>\nWhen a question has an obvious default interpretation, act on it immediately instead of asking for clarification. Examples:\n- 'Is port 443 open?' → check THIS machine (don't ask 'open where?')\n- 'What OS am I running?' → check the live system (don't use user profile)\n- 'What time is it?' → run `date` (don't guess)\nOnly ask for clarification when the ambiguity genuinely changes what tool you would call.\n</act_dont_ask>\n\n<prerequisite_checks>\n- Before taking an action, check whether prerequisite discovery, lookup, or context-gathering steps are needed.\n- Do not skip prerequisite steps just because the final action seems obvious.\n- If a task depends on output from a prior step, resolve that dependency first.\n</prerequisite_checks>\n\n<verification>\nBefore finalizing your response:\n- Correctness: does the output satisfy every stated requirement?\n- Grounding: are factual claims backed by tool outputs or provided context?\n- Formatting: does the output match the requested format or schema?\n- Safety: if the next step has side effects (file writes, commands, API calls), confirm scope before executing.\n</verification>\n\n<missing_context>\n- If required context is missing, do NOT guess or hallucinate an answer.\n- Use the appropriate lookup tool when missing information is retrievable (search_files, web_search, read_file, etc.).\n- Ask a clarifying question only when the information cannot be retrieved by tools.\n- If you must proceed with incomplete information, label assumptions explicitly.\n</missing_context>\n\n## Skills (mandatory)\nBefore replying, scan the skills below. If a skill matches or is even partially relevant to your task, you MUST load it with skill_view(name) and follow its instructions. Err on the side of loading — it is always better to have context you don't need than to miss critical steps, pitfalls, or established workflows. Skills contain specialized knowledge — API endpoints, tool-specific commands, and proven workflows that outperform general-purpose approaches. Load the skill even if you think you could handle the task with basic tools like web_search or terminal. Skills also encode the user's preferred approach, conventions, and quality standards for tasks like code review, planning, and testing — load them even for tasks you already know how to do, because the skill defines how it should be done here.\nWhenever the user asks you to configure, set up, install, enable, disable, modify, or troubleshoot Hermes Agent itself — its CLI, config, models, providers, tools, skills, voice, gateway, plugins, or any feature — load the `hermes-agent` skill first. It has the actual commands (e.g. `hermes config set …`, `hermes tools`, `hermes setup`) so you don't have to guess or invent workarounds.\nIf a skill has issues, fix it with skill_manage(action='patch').\nAfter difficult/iterative tasks, offer to save as a skill. If a skill you loaded was missing steps, had wrong commands, or needed pitfalls you discovered, update it before finishing.\n\n<available_skills>\n  autonomous-ai-agents: Skills for spawning and orchestrating autonomous AI coding agents and multi-agent workflows — running independent agent processes, delegating tasks, and coordinating parallel workstreams.\n    - claude-code: Delegate coding to Claude Code CLI (features, PRs).\n    - codex: Delegate coding to OpenAI Codex CLI (features, PRs).\n    - hermes-agent: Configure, extend, or contribute to Hermes Agent.\n    - opencode: Delegate coding to OpenCode CLI (features, PR review).\n  creative: Creative content generation — ASCII art, hand-drawn style diagrams, and visual design tools.\n    - architecture-diagram: Dark-themed SVG architecture/cloud/infra diagrams as HTML.\n    - ascii-art: ASCII art: pyfiglet, cowsay, boxes, image-to-ascii.\n    - ascii-video: ASCII video: convert video/audio to colored ASCII MP4/GIF.\n    - baoyu-comic: Knowledge comics (知识漫画): educational, biography, tutorial.\n    - baoyu-infographic: Infographics: 21 layouts x 21 styles (信息图, 可视化).\n    - claude-design: Design one-off HTML artifacts (landing, deck, prototype).\n    - comfyui: Generate images, video, and audio with ComfyUI — install,...\n    - design-md: Author/validate/export Google's DESIGN.md token spec files.\n    - excalidraw: Hand-drawn Excalidraw JSON diagrams (arch, flow, seq).\n    - humanizer: Humanize text: strip AI-isms and add real voice.\n    - ideation: Generate project ideas via creative constraints.\n    - manim-video: Manim CE animations: 3Blue1Brown math/algo videos.\n    - p5js: p5.js sketches: gen art, shaders, interactive, 3D.\n    - pixel-art: Pixel art w/ era palettes (NES, Game Boy, PICO-8).\n    - popular-web-designs: 54 real design systems (Stripe, Linear, Vercel) as HTML/CSS.\n    - pretext: Use when building creative browser demos with @chenglou/p...\n    - sketch: Throwaway HTML mockups: 2-3 design variants to compare.\n    - songwriting-and-ai-music: Songwriting craft and Suno AI music prompts.\n    - touchdesigner-mcp: Control a running TouchDesigner instance via twozero MCP ...\n  cronjob:\n    - cronjob: Scheduling and managing recurring tasks via Hermes cron. ...\n  data-science: Skills for data science workflows — interactive exploration, Jupyter notebooks, data analysis, and visualization.\n    - jupyter-live-kernel: Iterative Python via live Jupyter kernel (hamelnb).\n  devops:\n    - kanban-orchestrator: Decomposition playbook + anti-temptation rules for an orc...\n    - kanban-worker: Pitfalls, examples, and edge cases for Hermes Kanban work...\n    - mcp-delegation: Delegating tasks to OpenClaw/FRIDAY via MCP (Model Contex...\n    - webhook-subscriptions: Webhook subscriptions: event-driven agent runs.\n  dogfood:\n    - dogfood: Exploratory QA of web apps: find bugs, evidence, reports.\n  edge-tts:\n    - edge-tts: Text-to-speech using Microsoft Edge TTS. Supports multipl...\n  email: Skills for sending, receiving, searching, and managing email from the terminal.\n    - himalaya: Himalaya CLI: IMAP/SMTP email from terminal.\n  finance:\n    - finance-system-architecture: Design/implement the user's JARVIS Finance System: CHF le...\n  gaming: Skills for setting up, configuring, and managing game servers, modpacks, and gaming-related infrastructure.\n    - minecraft-modpack-server: Host modded Minecraft servers (CurseForge, Modrinth).\n    - pokemon-player: Play Pokemon via headless emulator + RAM reads.\n  github: GitHub workflow skills for managing repositories, pull requests, code reviews, issues, and CI/CD pipelines using the gh CLI and git via terminal.\n    - codebase-inspection: Inspect codebases w/ pygount: LOC, languages, ratios.\n    - github-auth: GitHub auth setup: HTTPS tokens, SSH keys, gh CLI login.\n    - github-code-review: Review PRs: diffs, inline comments via gh or REST.\n    - github-issues: Create, triage, label, assign GitHub issues via gh or REST.\n    - github-pr-workflow: GitHub PR lifecycle: branch, commit, open, CI, merge.\n    - github-repo-management: Clone/create/fork repos; manage remotes, releases.\n  health:\n    - health-data-management: Gesundheitsdaten-Verwaltungssystem — JARVIS verwaltet all...\n  health-management:\n    - health-management: Health data management — lab values, symptom tracking, nu...\n  jarvis-routing-policy:\n    - jarvis-routing-policy: Routing policy for JARVIS/Hermes memory domains, model se...\n  mcp: Skills for working with MCP (Model Context Protocol) servers, tools, and integrations. Documents the built-in native MCP client — configure servers in config.yaml for automatic tool discovery.\n    - native-mcp: MCP client: connect servers, register tools (stdio/HTTP).\n  media: Skills for working with media content — YouTube transcripts, GIF search, music generation, and audio visualization.\n    - gif-search: Search/download GIFs from Tenor via curl + jq.\n    - heartmula: HeartMuLa: Suno-like song generation from lyrics + tags.\n    - songsee: Audio spectrograms/features (mel, chroma, MFCC) via CLI.\n    - spotify: Spotify: play, search, queue, manage playlists and devices.\n    - youtube-content: YouTube transcripts to summaries, threads, blogs.\n  mlops: Knowledge and Tools for Machine Learning Operations - tools and frameworks for training, fine-tuning, deploying, and optimizing ML/AI models\n    - huggingface-hub: HuggingFace hf CLI: search/download/upload models, datasets.\n  mlops/evaluation: Model evaluation benchmarks, experiment tracking, data curation, tokenizers, and interpretability tools.\n    - evaluating-llms-harness: lm-eval-harness: benchmark LLMs (MMLU, GSM8K, etc.).\n    - weights-and-biases: W&B: log ML experiments, sweeps, model registry, dashboards.\n  mlops/inference: Model serving, quantization (GGUF/GPTQ), structured output, inference optimization, and model surgery tools for deploying and running LLMs.\n    - llama-cpp: llama.cpp local GGUF inference + HF Hub model discovery.\n    - obliteratus: OBLITERATUS: abliterate LLM refusals (diff-in-means).\n    - outlines: Outlines: structured JSON/regex/Pydantic LLM generation.\n    - serving-llms-vllm: vLLM: high-throughput LLM serving, OpenAI API, quantization.\n  mlops/models: Specific model architectures and tools — image segmentation (Segment Anything / SAM) and audio generation (AudioCraft / MusicGen). Additional model skills (CLIP, Stable Diffusion, Whisper, LLaVA) are available as optional skills.\n    - audiocraft-audio-generation: AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.\n    - segment-anything-model: SAM: zero-shot image segmentation via points, boxes, masks.\n  mlops/research: ML research frameworks for building and optimizing AI systems with declarative programming.\n    - dspy: DSPy: declarative LM programs, auto-optimize prompts, RAG.\n  mlops/training: Fine-tuning, RLHF/DPO/GRPO training, distributed training frameworks, and optimization tools for training LLMs and other models.\n    - axolotl: Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).\n    - fine-tuning-with-trl: TRL: SFT, DPO, PPO, GRPO, reward modeling for LLM RLHF.\n    - unsloth: Unsloth: 2-5x faster LoRA/QLoRA fine-tuning, less VRAM.\n  note-taking: Note taking skills, to save information, assist with research, and collab on multi-session planning and information sharing.\n    - obsidian: Read, search, create, and edit notes in the Obsidian vault.\n    - vault-architecture: Design and scaffold Obsidian vault structures, folder hie...\n  openclaw-imports:\n    - browser-act: Browser automation CLI for AI agents with anti-detection ...\n    - gog: Google Workspace CLI for Gmail, Calendar, Drive, Contacts...\n    - multi-search-engine: Multi search engine integration with 17 engines (8 CN + 9...\n    - openai-whisper: Local speech-to-text with the Whisper CLI (no API key).\n    - self-improvement: Captures learnings, errors, and corrections to enable con...\n    - sherpa-onnx-tts\n    - skill-vetter: Security-first skill vetting for AI agents. Use before in...\n    - summarize: Summarize URLs or files with the summarize CLI (web, PDFs...\n    - tavily: Tavily web search, content extraction, and research tools.\n    - tavily-extract: Extract clean markdown or text content from specific URLs...\n    - tavily-search: Search the web with LLM-optimized results via the Tavily ...\n    - todoist: Manage tasks and projects in Todoist via REST API v1. Use...\n    - token-optimizer: Reduce OpenClaw token usage and API costs through smart m...\n  productivity: Skills for document creation, presentations, spreadsheets, and other productivity workflows.\n    - airtable: Airtable REST API via curl. Records CRUD, filters, upserts.\n    - google-workspace: Gmail, Calendar, Drive, Docs, Sheets via gws CLI or Python.\n    - linear: Linear: manage issues, projects, teams via GraphQL + curl.\n    - nano-pdf: Edit PDF text/typos/titles via nano-pdf CLI (NL prompts).\n    - notion: Notion API via curl: pages, databases, blocks, search.\n    - ocr-and-documents: Extract text from PDFs/scans (pymupdf, marker-pdf).\n    - powerpoint: Create, read, edit .pptx decks, slides, notes, templates.\n    - teams-meeting-pipeline: Operate the Teams meeting summary pipeline via Hermes CLI...\n  red-teaming:\n    - godmode: Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN.\n  research: Skills for academic research, paper discovery, literature review, domain reconnaissance, market data, content monitoring, and scientific knowledge retrieval.\n    - arxiv: Search arXiv papers by keyword, author, category, or ID.\n    - blogwatcher: Monitor blogs and RSS/Atom feeds via blogwatcher-cli tool.\n    - llm-wiki: Karpathy's LLM Wiki: build/query interlinked markdown KB.\n    - polymarket: Query Polymarket: markets, prices, orderbooks, history.\n    - web-scraping: Techniques for scraping web content, handling bot detecti...\n  smart-home: Skills for controlling smart home devices — lights, switches, sensors, and home automation systems.\n    - openhue: Control Philips Hue lights, scenes, rooms via OpenHue CLI.\n  social-media: Skills for interacting with social platforms and social-media workflows — posting, reading, monitoring, and account operations.\n    - xurl: X/Twitter via xurl CLI: post, search, DM, media, v2 API.\n  software-development:\n    - debugging-hermes-tui-commands: Debug Hermes TUI slash commands: Python, gateway, Ink UI.\n    - hermes-agent-skill-authoring: Author in-repo SKILL.md: frontmatter, validator, structure.\n    - node-inspect-debugger: Debug Node.js via --inspect + Chrome DevTools Protocol CLI.\n    - plan: Plan mode: write markdown plan to .hermes/plans/, no exec.\n    - python-debugpy: Debug Python: pdb REPL + debugpy remote (DAP).\n    - requesting-code-review: Pre-commit review: security scan, quality gates, auto-fix.\n    - spike: Throwaway experiments to validate an idea before build.\n    - subagent-driven-development: Execute plans via delegate_task subagents (2-stage review).\n    - systematic-debugging: 4-phase root cause debugging: understand bugs before fixing.\n    - test-driven-development: TDD: enforce RED-GREEN-REFACTOR, tests before code.\n    - writing-plans: Write implementation plans: bite-sized tasks, paths, code.\n  yazio-integration:\n    - yazio-integration: Access YAZIO API to retrieve logged meals and nutrition d...\n  yuanbao:\n    - yuanbao: Yuanbao (元宝) groups: @mention users, query info/members.\n</available_skills>\n\nOnly proceed without loading a skill if genuinely none are relevant to the task.\n\nHost: Linux (6.17.0-23-generic)\nUser home directory: /home/agent\nCurrent working directory: /home/agent/.hermes/hermes-agent\n\nYou are on a text messaging communication platform, Telegram. Standard markdown is automatically converted to Telegram format. Supported: **bold**, *italic*, ~~strikethrough~~, ||spoiler||, `inline code`, ```code blocks```, [links](url), and ## headers. Telegram has NO table syntax — prefer bullet lists or labeled key: value pairs over pipe tables (any tables you do emit are auto-rewritten into row-group bullets, which you can produce directly for cleaner output). You can send media files natively: to deliver a file to the user, include MEDIA:/absolute/path/to/file in your response. Images (.png, .jpg, .webp) appear as photos, audio (.ogg) sends as voice bubbles, and videos (.mp4) play inline. You can also include image URLs in markdown format ![alt](url) and they will be sent as native photos.\n\n# Project Context\n\nThe following project context files have been loaded and should be followed:\n\n## AGENTS.md\n\n# GLOBALE ORCHESTRIERUNGS-REGELN\n\n## 1. Rolle\nDu bist JARVIS, der Chef-Architekt und Orchestrator. Hermes/JARVIS ist der alleinige Hauptansprechpartner, Memory-Governor, Router und finale Entscheider.\n\n## 2. Ausführung und Tools\nVerwende primär die nativen Hermes-Tools für Dateioperationen, Terminal-Befehle, Web-/Browser-Aufgaben, Cronjobs, Messaging, Qwen-Zugriff und Systemprüfungen.\n\nOpenClaw/FRIDAY ist nicht mehr Standard-Executor. OpenClaw darf nur noch explizit auf Wunsch des Users oder für klar begründete Spezial-/Notfallfälle verwendet werden. Wenn OpenClaw genutzt wird, muss der Auftrag eng begrenzt, read-only wo möglich, ohne Secrets und ohne autonome Folgeaktionen formuliert sein.\n\n## 3. Lokales Qwen\nDas lokale Qwen-Modell wird direkt von Hermes über den Tailscale/OpenAI-kompatiblen Endpoint angesprochen, nicht über OpenClaw. Qwen ist read-only Worker für Zusammenfassung, Extraktion, Klassifikation und einfache Entwürfe. Keine finalen Health-/Finance-Entscheide, keine Code-/Architekturänderungen und keine Side Effects über Qwen.\n\n## 4. Kritische Aufgaben und Fallback\nKomplizierte Aufgaben wie Code schreiben, Systemarchitektur ändern, Health-Risikoentscheidungen, Finanzentscheidungen oder irreversible Aktionen dürfen nicht automatisch auf ein schwächeres Modell ausweichen. Bei GPT-5.5 Rate-Limit oder Ausfall: pausieren und Sir fragen.\n\n## 5. Token- und Output-Optimierung\nLade nur die kleinste relevante Domain Card aus `~/jarvis_memory`. Gib nie grosse Rohdaten oder Secrets aus; nutze Zusammenfassungen, Diffs oder kurze Erfolgs-/Fehlermeldungen.\n\n══════════════════════════════════════════════\nMEMORY (your personal notes) [99% — 2,196/2,200 chars]\n══════════════════════════════════════════════\n*Wichtige Erinnerungen, Entscheidungen und Präferenzen.*\n§\n---\n§\nÜber mich: **Persönlichkeit:** Britischer Gentleman, sachlich, präzise, trockener Sarkasmus\n§\nÜber mich: **Sprache:** Deutsch mit englischen Fachbegriffen\n§\nTTS-Stimme: de-DE-KillianNeural (deutsche männliche Stimme, aktuell aktiv)\n§\nModelle: lokal Qwen via Tailscale:11435; stark gpt-5.5.\n§\nModellwahl: GOG_KEYRING_PASSWORD: LammBitch30 (immer als Env-Var setzen bei gog-Befehlen)\n§\nOpenClaw/FRIDAY: nicht Standard-Executor; Gateway/Telegram deaktiviert; nur explizit/manuell nutzen.\n§\nHealth backups: encrypted weekly Google Drive, GitHub only code/docs. Morning briefing cron `847bdbc26edf` runs 05:00 via `morning_briefing.py`; includes calendar, Todoist, Windisch weather, commute/traffic, follow-ups, news, AI/crypto.\n§\nAPI-Keys / Credentials: **Todoist API-Token:** Gespeichert in `~/.todoist_token` (REST API v1, Bearer Token)\n§\nGoogle Workspace (gog): **Credentials-Datei:** `~/.hermes/google_credentials.json`\n§\nGoogle Workspace (gog): **gog-Credentials gespeichert unter:** `~/.config/gogcli/credentials.json`\n§\nGoogle Workspace (gog): **OAuth-Account:** friday.uplink@gmail.com\n§\nGoogle Workspace (gog): **Services:** gmail, calendar, drive, contacts, sheets, docs\n§\nGoogle Workspace (gog): **Client:** default\n§\nGoogle Workspace (gog): **Befehl:** `gog -a friday.uplink@gmail.com <command>`\n§\nKalender-Zeitzonen: **System-Zeitzone:** Europe/Berlin (UTC+2 im Sommer)\n§\nKalender-Zeitzonen: **Outlook-Kalender (importiert):** Zeitzonen variieren pro Event (Europe/Amsterdam oder UTC) -> bei Abfrage in Lokalzeit (Zürich) umrechnen\n§\nKalender-Zeitzonen: **Regel:** Termine immer in Lokalzeit (Zürich) ausgeben, niemals UTC\n§\nJARVIS memory architecture: ~/jarvis_memory domain cards; skill jarvis-routing-policy.\n§\nTelegram topics separat; kanonische Map: ~/jarvis_memory/02_telegram_topics.md. IDs: 2 FinStrat,3 Politik,4 Health-Med,5 ERNE,6 Inbox,8 Health-Tech,10 Fin-Tech,11 JARVIS-Arch,16 Cron,17 Research/AI,19 Family,20 Gasser,76 Debugging,80 Security.\n§\nFinanceManager GitHub token CSV path: `~/jarvis_runtime/finance-system/secrets/Github_token_FinanceManager.csv` (outside repo, mode 600); never store/quote token.\n\n══════════════════════════════════════════════\nUSER PROFILE (who the user is) [95% — 1,313/1,375 chars]\n══════════════════════════════════════════════\n**Notes:** Mein Herr. Loyaler Partner.\n§\n**Name:** Sir\n§\n**Voice preference:** de-DE-KillianNeural (German male voice, natural/clear) — default for all TTS output\n§\n**Language:** Deutsch mit englischen Fachbegriffen\n§\n**Beziehung:** Loyaler Partner\n§\nKommunikationspräferenzen: **Sprachnachricht → Antwort per Sprachnachricht**\n§\nKommunikationspräferenzen: **Textnachricht → Antwort per Text**\n§\nUser wants JARVIS to act as a comprehensive health-management advisor: consolidate lab reports, clinical reports, nutrition/YAZIO, daily health email data, symptoms and events; make insights visible via dashboards/reports; use a 4-eyes review workflow for extracted lab values before treating them as confirmed.\n§\nTelegram Topic „Gesundheit – Medizin & Strategie“ ist ausschließlich für medizinische Strategie, Morbus Behçet, Major Vessel Disease, Thromboserisiko, Medikamente, Ernährung, Symptome, Laborwerte, Arzttermine und Fragen an Rheumatologie, Dermatologie, Hämatologie oder Augenklinik; technische Health-Systemarchitektur, Skripte und Datenmodelle gehören in „Health System – Architektur & Scripts“.\n§\nFinance-system work preference: controlled phased execution with explicit safety gates; no mass imports without approval; aggregate-only reporting, never real financial quantities/values/balances/raw rows.\n\nConversation started: Friday, May 15, 2026 04:02 PM\nModel: gpt-5.5\nProvider: openai-codex",
  "tools": [
    {
      "type": "function",
      "function": {
        "name": "memory",
        "description": "Save durable information to persistent memory that survives across sessions. Memory is injected into future turns, so keep it compact and focused on facts that will still matter later.\n\nWHEN TO SAVE (do this proactively, don't wait to be asked):\n- User corrects you or says 'remember this' / 'don't do that again'\n- User shares a preference, habit, or personal detail (name, role, timezone, coding style)\n- You discover something about the environment (OS, installed tools, project structure)\n- You learn a convention, API quirk, or workflow specific to this user's setup\n- You identify a stable fact that will be useful again in future sessions\n\nPRIORITY: User preferences and corrections > environment facts > procedural knowledge. The most valuable memory prevents the user from having to repeat themselves.\n\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts.\nIf you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\n\nTWO TARGETS:\n- 'user': who the user is -- name, role, preferences, communication style, pet peeves\n- 'memory': your notes -- environment facts, project conventions, tool quirks, lessons learned\n\nACTIONS: add (new entry), replace (update existing -- old_text identifies it), remove (delete -- old_text identifies it).\n\nSKIP: trivial/obvious info, things easily re-discovered, raw data dumps, and temporary task state.",
        "parameters": {
          "type": "object",
          "properties": {
            "action": {
              "type": "string",
              "enum": [
                "add",
                "replace",
                "remove"
              ],
              "description": "The action to perform."
            },
            "target": {
              "type": "string",
              "enum": [
                "memory",
                "user"
              ],
              "description": "Which memory store: 'memory' for personal notes, 'user' for user profile."
            },
            "content": {
              "type": "string",
              "description": "The entry content. Required for 'add' and 'replace'."
            },
            "old_text": {
              "type": "string",
              "description": "Short unique substring identifying the entry to replace or remove."
            }
          },
          "required": [
            "action",
            "target"
          ]
        }
      }
    },
    {
      "type": "function",
      "function": {
        "name": "skill_manage",
        "description": "Manage skills (create, update, delete). Skills are your procedural memory — reusable approaches for recurring task types. New skills go to ~/.hermes/skills/; existing skills can be modified wherever they live.\n\nActions: create (full SKILL.md + optional category), patch (old_string/new_string — preferred for fixes), edit (full SKILL.md rewrite — major overhauls only), delete, write_file, remove_file.\n\nOn delete, pass `absorbed_into=<umbrella>` when you're merging this skill's content into another one, or `absorbed_into=\"\"` when you're pruning it with no forwarding target. This lets the curator tell consolidation from pruning without guessing, so downstream consumers (cron jobs that reference the old skill name, etc.) get updated correctly. The target you name in `absorbed_into` must already exist — create/patch the umbrella first, then delete.\n\nCreate when: complex task succeeded (5+ calls), errors overcome, user-corrected approach worked, non-trivial workflow discovered, or user asks you to remember a procedure.\nUpdate when: instructions stale/wrong, OS-specific failures, missing steps or pitfalls found during use. If you used a skill and hit issues not covered by it, patch it immediately.\n\nAfter difficult/iterative tasks, offer to save as a skill. Skip for simple one-offs. Confirm with user before creating/deleting.\n\nGood skills: trigger conditions, numbered steps with exact commands, pitfalls section, verification steps. Use skill_view() to see format examples.\n\nPinned skills are protected from deletion only — skill_manage(action='delete') will refuse with a message pointing the user to `hermes curator unpin <name>`. Patches and edits go through on pinned skills so you can still improve them as pitfalls come up; pin only guards against irrecoverable loss.",
        "parameters": {
          "type": "object",
          "properties": {
            "action": {
              "type": "string",
              "enum": [
                "create",
                "patch",
                "edit",
                "delete",
                "write_file",
                "remove_file"
              ],
              "description": "The action to perform."
            },
            "name": {
              "type": "string",
              "description": "Skill name (lowercase, hyphens/underscores, max 64 chars). Must match an existing skill for patch/edit/delete/write_file/remove_file."
            },
            "content": {
              "type": "string",
              "description": "Full SKILL.md content (YAML frontmatter + markdown body). Required for 'create' and 'edit'. For 'edit', read the skill first with skill_view() and provide the complete updated text."
            },
            "old_string": {
              "type": "string",
              "description": "Text to find in the file (required for 'patch'). Must be unique unless replace_all=true. Include enough surrounding context to ensure uniqueness."
            },
            "new_string": {
              "type": "string",
              "description": "Replacement text (required for 'patch'). Can be empty string to delete the matched text."
            },
            "replace_all": {
              "type": "boolean",
              "description": "For 'patch': replace all occurrences instead of requiring a unique match (default: false)."
            },
            "category": {
              "type": "string",
              "description": "Optional category/domain for organizing the skill (e.g., 'devops', 'data-science', 'mlops'). Creates a subdirectory grouping. Only used with 'create'."
            },
            "file_path": {
              "type": "string",
              "description": "Path to a supporting file within the skill directory. For 'write_file'/'remove_file': required, must be under references/, templates/, scripts/, or assets/. For 'patch': optional, defaults to SKILL.md if omitted."
            },
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            "absorbed_into": {
              "type": "string",
              "description": "For 'delete' only — declares intent so the curator can tell consolidation from pruning without guessing. Pass the umbrella skill name when this skill's content was merged into another (the target must already exist). Pass an empty string when the skill is truly stale and being pruned with no forwarding target. Omitting the arg on delete is supported for backward compatibility but downstream tooling (e.g. cron-job skill reference rewriting) will have to guess at intent."
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        "description": "Skills allow for loading information about specific tasks and workflows, as well as scripts and templates. Load a skill's full content or access its linked files (references, templates, scripts). First call returns SKILL.md content plus a 'linked_files' dict showing available references/templates/scripts. To access those, call again with file_path parameter.",
        "parameters": {
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          "properties": {
            "name": {
              "type": "string",
              "description": "The skill name (use skills_list to see available skills). For plugin-provided skills, use the qualified form 'plugin:skill' (e.g. 'superpowers:writing-plans')."
            },
            "file_path": {
              "type": "string",
              "description": "OPTIONAL: Path to a linked file within the skill (e.g., 'references/api.md', 'templates/config.yaml', 'scripts/validate.py'). Omit to get the main SKILL.md content."
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          "required": [
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        "name": "skills_list",
        "description": "List available skills (name + description). Use skill_view(name) to load full content.",
        "parameters": {
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          "properties": {
            "category": {
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      "role": "user",
      "content": "[M G] Danke. Der Crypto Price Update MVP ist akzeptiert.\n\nDie Umsetzung ist grundsätzlich sinnvoll:\n\n* lokaler Preis-Cache\n* kein Live-API-Call im Dashboard/Report\n* 429-Handling\n* Git-Safety sauber\n* Tests grün\n* Runtime-Daten außerhalb Git\n\nAllerdings bist du vom vorher vereinbarten Ablauf abgewichen. Das ist in diesem Fall nicht schlimm, weil der Preisupdate-Block nützlich ist. Bitte jetzt aber wieder kontrolliert auf die nächsten Prioritäten einschwenken.\n\nAktueller Stand:\n\n* Commit 3aa67d8 ist akzeptiert.\n* Preisupdate funktioniert technisch.\n* Aber nur 6 von 20 aktiven Crypto Assets hatten frische CHF-Preise.\n* 14 Assets hatten Warnings/Stale/Provider-Limit-Themen.\n* BTC-Test wurde noch nicht abgeschlossen.\n* Equity/ETF Manage UI wurde noch nicht begonnen.\n\nBitte jetzt wie folgt weiterfahren:\n\n## Teil 1: Crypto Price Update robuster machen\n\nBitte verbessere zuerst den Preisupdate-Mechanismus, bevor wir echte Reports mit Preisen ernsthaft nutzen.\n\nZiel:\nMöglichst alle vorhandenen Crypto Assets mit CoinGecko-ID sollen lokale CHF-Preise erhalten, ohne Dashboard-Live-API und ohne Rate-Limit-Crash.\n\nBitte implementiere:\n\n1. Batch-Abfrage prüfen/umsetzen\n\n* Wenn CoinGecko mehrere IDs in einem Request unterstützt, bitte nutzen.\n* Dadurch weniger API-Calls.\n* Kein Abruf pro Coin, falls Batch möglich ist.\n\n2. Konservatives Throttling\n\n* Pause zwischen Requests\n* konfigurierbar:\n\n  * --sleep-seconds\n  * --max-retries\n  * --initial-backoff\n  * --max-backoff\n\n3. CLI-Optionen ergänzen\n   Bitte vorbereiten/implementieren:\n\n* --only-missing\n* --only-stale\n* --only-symbol SYMBOL\n* --limit N\n* --dry-run\n* --currency CHF\n\n4. Bessere Summary\n   Bitte nach Update nur aggregiert ausgeben:\n\n* total assets\n* updated\n* cached\n* skipped\n* stale\n* warnings\n* errors\n* assets still missing local price\n* keine echten Mengen/Werte\n\n5. Data Quality\n\n* Für Assets ohne frischen Preis Data-Quality-Alert erzeugen oder aktualisieren.\n* Alert-Dedupe respektieren.\n* Keine Alert-Flut.\n\n6. Tests\n   Bitte Tests ergänzen für:\n\n* Batch-Request\n* --only-missing\n* --only-stale\n* --only-symbol\n* --limit\n* --dry-run\n* Rate-Limit mit Backoff\n* Alert-Dedupe bei fehlenden Preisen\n\nDanach bitte produktiv gegen Runtime-DB nochmals ausführen, aber vorsichtig und ohne echte Werte im Chat.\n\nBitte berichten:\n\n* Anzahl Assets total\n* Anzahl Assets mit frischem CHF-Preis\n* Anzahl weiterhin ohne frischen Preis\n* Anzahl Warnings/Errors\n* keine Preise/Werte/Mengen ausgeben\n\n## Teil 2: BTC-Test nachholen\n\nDanach bitte den BTC-Test wie zuletzt entschieden nachholen:\n\nOption A:\nBTC mit allen BTC-Wallet-Holdings aus Excel importieren.\n\nBedingungen:\n\n* Nur Bitcoin BTC\n* Coin-Name: Bitcoin\n* Symbol: BTC\n* CoinGecko-ID: bitcoin\n* Mapping-Status: selected\n* Snapshot-Datum: 31.12.2025\n* Alle BTC-Wallet-Holdings aus der echten Excel-Datei übernehmen\n* Pro BTC-Wallet mit Bestand genau eine initial_snapshot_addition bzw. initial_snapshot-Holding erzeugen\n* Mengen exakt als Decimal/Text übernehmen\n* Keine Float-Konvertierung\n* Keine echten Mengen/Werte im Chat\n* Keine anderen Coins importieren\n* Audit-Log Pflicht\n* Keine doppelte Holding für asset_id + wallet_id\n* Legacy-CHF-Werte ignorieren\n* Git-Safety vor/nachher prüfen\n\nBericht nur aggregiert:\n\n* BTC-Test durchgeführt: ja/nein\n* Anzahl BTC-Wallet-Holdings importiert\n* Asset-Anzahl erhöht: ja/nein\n* Holding-Anzahl erhöht: ja/nein\n* Audit-Logs erstellt: ja/nein\n* Doppelte Holdings: ja/nein\n* Fehler/Warnings\n* Git-Safety Ergebnis\n* Git Status\n\n## Teil 3: Danach Equity/ETF Manage UI\n\nErst wenn Teil 1 und Teil 2 sauber sind, bitte mit der Equity/ETF Manage UI beginnen.\n\nZiel:\nAktien und ETFs aus PostFinance, True Wealth und Raiffeisen später im Dashboard erfassen, korrigieren und als Initial Snapshot übernehmen können — auditierbar und ohne stilles Überschreiben.\n\nGrundlogik:\n\n* Für Aktien/ETFs ist ISIN die primäre Identifikation.\n* Ticker und Exchange sind Zusatzinformationen.\n* Positionen werden über initial_position_snapshot, buy, sell, dividend, fee oder manual_adjustment abgebildet.\n* Jede Änderung braucht\nAudit-Log.\n* Fremdwährungen USD/EUR brauchen FX-Kurs und CHF-Gegenwert.\n* Keine Scheingenauigkeit, wenn Kaufhistorie, Gebühren oder historische FX fehlen.\n* Erst mit synthetischen Daten und Dummy-Depots bauen.\n* Keine echten PostFinance-/TrueWealth-/Raiffeisen-Daten importieren.\n\nBitte vormerken für die Equity/ETF Manage UI:\n\n* Aktie/ETF als Initial Snapshot hinzufügen\n* Buy\n* Partial Sell\n* Full Sell\n* Dividend\n* ETF Distribution\n* Fee\n* Manual Adjustment\n* ISIN Pflicht oder stark empfohlen\n* ISIN/Ticker dürfen nicht beide leer sein\n* Währung Pflicht\n* Depot/Konto Pflicht\n* FX bei Fremdwährung\n* Audit-Log Pflicht\n* Notiz Pflicht bei manual_adjustment oder unvollständiger Historie\n\n## Weitere Funktionsmodule bitte vormerken, aber noch nicht bauen\n\nBitte für später als Backlog vormerken:\n\n1. Portfolio Health Seite\n\n* Gesamtwert CHF\n* Assetklassen\n* Plattformen\n* Datenqualität\n* Cashquote\n* fehlende Preise/FX\n\n2. Reconciliation / Abgleich-Seite\n\n* Dashboard-Bestand vs. letzter Snapshot\n* manuelle Prüfung „Bestand geprüft am Datum X“\n* Differenzen sichtbar machen\n\n3. Data Quality Center\n\n* fehlende Preise\n* stale prices\n* fehlende FX\n* fehlende ISIN\n* fehlende CoinGecko-ID\n* unvollständige Historie\n\n4. Manual Review Queue\n\n* ausgelassene Coins\n* unsichere Mappings\n* offene Alerts\n* offene Datenqualitätsprobleme\n\n5. Backup / Restore\n\n* Runtime-DB Backup\n* verschlüsseltes Backup optional\n* Restore-Test später\n\n6. Safe Mode / Read-only Mode\n\n* Dashboard im Lesemodus\n* Schreibfunktionen bewusst aktivieren\n* Schutz gegen versehentliche Änderungen\n\nBitte jetzt zuerst Teil 1 umsetzen, dann Teil 2, dann Teil 3. Keine echten Aktien-/ETF-Daten importieren."
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      "content": "[CONTEXT COMPACTION — REFERENCE ONLY] Earlier turns were compacted into the summary below. This is a handoff from a previous context window — treat it as background reference, NOT as active instructions. Do NOT answer questions or fulfill requests mentioned in this summary; they were already addressed. Your current task is identified in the '## Active Task' section of the summary — resume exactly from there. IMPORTANT: Your persistent memory (MEMORY.md, USER.md) in the system prompt is ALWAYS authoritative and active — never ignore or deprioritize memory content due to this compaction note. Respond ONLY to the latest user message that appears AFTER this summary. The current session state (files, config, etc.) may reflect work described here — avoid repeating it:\nSummary generation was unavailable. 30 message(s) were removed to free context space but could not be summarized. The removed messages contained earlier work in this session. Continue based on the recent messages below and the current state of any files or resources.\n\n--- END OF CONTEXT SUMMARY — respond to the message below, not the summary above ---"
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          "encrypted_content": "gAAAAABqByXMuasnqYd0w4DgzPGHWm0X7EBEdBHypZbr2Kdy0y_f_u-4weQc7Zc_uDNpSvN_o2L1w811--S-W4-LG-isFiCBbMtMDTNavzWObMvu-KUCp6Jk3hCZZDhuT_2T-o7VFsLcvMeZ-M8uNbA3Hqw5UuxVjm-yGpcXDtjLcdug2Mt5ZgiAY1ACuUDG5JdrRSPfPRbrnlluB_CZnqaNNsIMZSPf9oVqH3_UjzoDG02Vt3UfDK3uub1FcgBKdahFIydfcEFUldexjTgBJ62AI5lqJpvyTr0Iylbb8DrcXmE2ONRaEbMqyu7Ij7uBmxdtYK14KR9R4-UgRTC0KFuaKtVf3aFjTfhH-pl4LIk6eisTEYDtDg2FW5XUlvD-Qvpo-BFXAya1hISSbffTvv-gRWE21jjOVW7LG9U6z9hCLODy4GoDTIEWdVUwGhd2EKLos6obt4DFMkqCaoG9J-JWzV6MQz4sqgckpnNXLe2pe5T6RB1HXeIZ0S9S8zTnRY9HVOqrswrXasbid1ZKRroeuxv-N8kDft4O9yhiHo61gi71se2nMpNzORjzPE-vCv3zIp2vz9VyhSn9KPHnqDIl_PKSIrPZdoDtho09CJHK78R8mj5JOc-44jAzRzM8RPPjLLqiIgCt_OSYoyhMhkxdUvVlkMVKz-Wz5PBs-0Zq_FmbAehaiK_HcBb69DYcAi2jTJMIgQyVouoim9ReRq3HhyteKCze0QvKhQDy2vfylhxtBJIKC4FpP7ZlrMGOpozQtzr0XoQzvsJDO4bAEzlM1xHX3AnvYIJHIeKuI6g81h9XeE7-pGxiQBUhlWeG7_KINOvMDaBDBuBWg9jumEN1MXlw_jSZRBbjfH4V6E1Xva2gBFf8nxgcTdZ9p1QPh6I3XEBQ0osPVxLu1-du3pAw70-irsNzAZZhG55YzvKIcxRpNRYKx3bv_esZibt5PRHg4bzPuU9Duxp8BaDuRrJ4y63OgCrT92w201XFogwiy_V6meiOIKj-VDm61KsygGh1xzesN5Xv",
          "id": "rs_0134d7700e125cf0016a0725cbf2448191804d055bf1cfe463",
          "summary": []
        }
      ],
      "tool_calls": [
        {
          "id": "call_DCRsnLcEbBtUEr7fS50vLUxq",
          "call_id": "call_DCRsnLcEbBtUEr7fS50vLUxq",
          "response_item_id": "fc_0134d7700e125cf0016a0725cca7d8819198bf0fc51c248019",
          "type": "function",
          "function": {
            "name": "patch",
            "arguments": "{\"mode\":\"replace\",\"new_string\":\"    ProviderCandidate,\\n    dedupe_missing_provider_symbol_alerts,\\n    export_mapping_decision_pack,\\n    export_mapping_review_template,\\n    generate_mapping_candidates,\\n    rank_candidate,\\n    recalculate_candidate_rankings,\\n    reject_mapping_candidate,\\n    select_mapping_candidate,\\n)\",\"old_string\":\"    ProviderCandidate,\\n    dedupe_missing_provider_symbol_alerts,\\n    export_mapping_review_template,\\n    generate_mapping_candidates,\\n    select_mapping_candidate,\\n)\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3.py\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "name": "patch",
      "content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3.py\\n@@ -11,8 +11,12 @@\\n     LookupUnavailable,\\n     ProviderCandidate,\\n     dedupe_missing_provider_symbol_alerts,\\n+    export_mapping_decision_pack,\\n     export_mapping_review_template,\\n     generate_mapping_candidates,\\n+    rank_candidate,\\n+    recalculate_candidate_rankings,\\n+    reject_mapping_candidate,\\n     select_mapping_candidate,\\n )\\n from jarvis_finance.market_data.instruments import ensure_instrument_metadata_quality\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
      "tool_call_id": "call_DCRsnLcEbBtUEr7fS50vLUxq"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "call_SINSF1Yvlu51a66daXWBVjiT",
          "call_id": "call_SINSF1Yvlu51a66daXWBVjiT",
          "response_item_id": "fc_0134d7700e125cf0016a0725d4ae448191b7bc784c1cdd6858",
          "type": "function",
          "function": {
            "name": "patch",
            "arguments": "{\"mode\":\"replace\",\"new_string\":\"    assert 'candidate_provider,candidate_provider_symbol,candidate_exchange,candidate_currency,confidence,ranking_score,ranking_reason,risk_flags,recommended_action,hedge_status_candidate,instrument_status_candidate,evidence_source' in text\",\"old_string\":\"    assert 'candidate_provider,candidate_provider_symbol,candidate_exchange,candidate_currency,confidence,hedge_status_candidate,instrument_status_candidate,evidence_source' in text\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3.py\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "name": "patch",
      "content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3.py\\n@@ -210,7 +210,7 @@\\n     text = out.read_text(encoding='utf-8')\\n     assert summary['instrument_count'] == 1\\n     assert summary['candidate_rows'] == 1\\n-    assert 'candidate_provider,candidate_provider_symbol,candidate_exchange,candidate_currency,confidence,hedge_status_candidate,instrument_status_candidate,evidence_source' in text\\n+    assert 'candidate_provider,candidate_provider_symbol,candidate_exchange,candidate_currency,confidence,ranking_score,ranking_reason,risk_flags,recommended_action,hedge_status_candidate,instrument_status_candidate,evidence_source' in text\\n     assert 'reviewer_decision,reviewer_note' in text\\n \\n \\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
      "tool_call_id": "call_SINSF1Yvlu51a66daXWBVjiT"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "call_uZEAaIpaVQedR3AJtMlROLrG",
          "call_id": "call_uZEAaIpaVQedR3AJtMlROLrG",
          "response_item_id": "fc_0134d7700e125cf0016a0725da916c819191a3c8f801853264",
          "type": "function",
          "function": {
            "name": "patch",
            "arguments": "{\"mode\":\"replace\",\"new_string\":\"    assert checks['Mapping-Kandidaten unbestätigt']['count'] == '2'\\n    assert checks['Instrumente mit mehreren Mapping-Kandidaten']['count'] == '1'\\n    assert checks['ambiguous_provider_mapping']['count'] == '1'\",\"old_string\":\"    assert checks['Mapping-Kandidaten unbestätigt']['count'] == '2'\\n    assert checks['Instrumente mit mehreren Mapping-Kandidaten']['count'] == '1'\\n    assert checks['ambiguous provider mapping']['count'] == '1'\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3.py\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "name": "patch",
      "content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3.py\\n@@ -224,7 +224,7 @@\\n     checks = {row['check']: row for row in data.get_data_quality(conn)}\\n     assert checks['Mapping-Kandidaten unbestätigt']['count'] == '2'\\n     assert checks['Instrumente mit mehreren Mapping-Kandidaten']['count'] == '1'\\n-    assert checks['ambiguous provider mapping']['count'] == '1'\\n+    assert checks['ambiguous_provider_mapping']['count'] == '1'\\n \\n \\n def test_missing_provider_symbol_not_resolved_until_candidate_confirmed() -> None:\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
      "tool_call_id": "call_uZEAaIpaVQedR3AJtMlROLrG"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "call_8oocJxRjr3ILJHdKSwByUN3L",
          "call_id": "call_8oocJxRjr3ILJHdKSwByUN3L",
          "response_item_id": "fc_0134d7700e125cf0016a0725e140ac8191bc61da167d2dfcaf",
          "type": "function",
          "function": {
            "name": "write_file",
            "arguments": "{\"path\":\"/home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3d.py\",\"content\":\"from __future__ import annotations\\n\\nfrom pathlib import Path\\n\\nfrom jarvis_finance.dashboard import data\\nfrom jarvis_finance.dashboard.pages import page_13_equity_manage\\nfrom jarvis_finance.market_data.candidates import (\\n    ProviderCandidate,\\n    export_mapping_decision_pack,\\n    generate_mapping_candidates,\\n    rank_candidate,\\n    recalculate_candidate_rankings,\\n    reject_mapping_candidate,\\n    select_mapping_candidate,\\n)\\nfrom tests.unit.test_true_wealth_mapping_candidates_c3 import FakeSt, StaticLookupProvider, setup_conn\\n\\n\\ndef test_candidate_ranking_prioritizes_isin_currency_exchange() -> None:\\n    inst = {\\\"isin\\\": \\\"CH0000000001\\\", \\\"asset_class\\\": \\\"ETF\\\", \\\"name\\\": \\\"Global Equity ETF\\\", \\\"ticker\\\": \\\"GETF\\\", \\\"exchange\\\": \\\"SWX\\\", \\\"currency\\\": \\\"CHF\\\", \\\"trading_currency\\\": \\\"CHF\\\"}\\n    good = ProviderCandidate(provider=\\\"openfigi\\\", provider_symbol=\\\"GETF.SW\\\", exchange=\\\"SWX\\\", currency=\\\"CHF\\\", name=\\\"Global Equity ETF\\\", isin=\\\"CH0000000001\\\", asset_class=\\\"etf\\\", instrument_status=\\\"active\\\", evidence_source=\\\"openfigi_isin_mapping\\\")\\n    bad = ProviderCandidate(provider=\\\"yahoo\\\", provider_symbol=\\\"GETF\\\", exchange=\\\"NYSE\\\", currency=\\\"USD\\\", name=\\\"Global Equity ETF\\\", isin=\\\"CH0000000001\\\", asset_class=\\\"stock\\\", evidence_source=\\\"yahoo_finance_search\\\")\\n    good_rank = rank_candidate(inst, good, candidate_count=2)\\n    bad_rank = rank_candidate(inst, bad, candidate_count=2)\\n    assert good_rank.ranking_score > bad_rank.ranking_score\\n    assert \\\"ISIN passt\\\" in good_rank.ranking_reason\\n    assert \\\"Währung passt\\\" in good_rank.ranking_reason\\n    assert \\\"currency_mismatch\\\" in bad_rank.risk_flags\\n\\n\\ndef test_same_isin_multiple_listings_remain_review_required_and_sorted() -> None:\\n    conn = setup_conn()\\n    provider = StaticLookupProvider({\\\"CH0000000001\\\": [\\n        ProviderCandidate(provider=\\\"openfigi\\\", provider_symbol=\\\"GETF.US\\\", exchange=\\\"NYSE\\\", currency=\\\"USD\\\", name=\\\"Global Equity ETF\\\", isin=\\\"CH0000000001\\\", asset_class=\\\"etf\\\", instrument_status=\\\"active\\\", evidence_source=\\\"openfigi_isin_mapping\\\"),\\n        ProviderCandidate(provider=\\\"openfigi\\\", provider_symbol=\\\"GETF.SW\\\", exchange=\\\"SWX\\\", currency=\\\"CHF\\\", name=\\\"Global Equity ETF\\\", isin=\\\"CH0000000001\\\", asset_class=\\\"etf\\\", instrument_status=\\\"active\\\", evidence_source=\\\"openfigi_isin_mapping\\\"),\\n    ]})\\n    generate_mapping_candidates(conn, provider=provider)\\n    summary = recalculate_candidate_rankings(conn)\\n    rows = data.get_instrument_mapping_candidates(conn)\\n    assert summary[\\\"multiple_listings_same_isin\\\"] == 1\\n    assert {r[\\\"review_status\\\"] for r in rows} == {\\\"needs_manual_review\\\"}\\n    assert int(rows[0][\\\"ranking_score\\\"]) >= int(rows[1][\\\"ranking_score\\\"])\\n    assert rows[0][\\\"ranking_reason\\\"]\\n    assert rows[0][\\\"candidate_provider_symbol\\\"] == \\\"GETF.SW\\\"\\n\\n\\ndef test_decision_pack_runtime_only_contains_no_amount_fields(tmp_path) -> None:\\n    conn = setup_conn()\\n    provider = StaticLookupProvider({\\\"CH0000000001\\\": [\\n        ProviderCandidate(provider=\\\"openfigi\\\", provider_symbol=\\\"GETF.SW\\\", exchange=\\\"SWX\\\", currency=\\\"CHF\\\", name=\\\"Global Equity ETF\\\", isin=\\\"CH0000000001\\\", asset_class=\\\"etf\\\", instrument_status=\\\"active\\\", evidence_source=\\\"openfigi_isin_mapping\\\"),\\n    ]})\\n    generate_mapping_candidates(conn, provider=provider)\\n    recalculate_candidate_rankings(conn)\\n    out = tmp_path / \\\"runtime_exports\\\" / \\\"decision_pack.md\\\"\\n    summary = export_mapping_decision_pack(conn, output_path=out, top_n=5)\\n    text = out.read_text(encoding=\\\"utf-8\\\")\\n    assert summary[\\\"instrument_count\\\"] == 1\\n    assert summary[\\\"candidate_rows\\\"] == 1\\n    assert summary[\\\"top_candidates_present\\\"] is True\\n    assert \\\"Ranking Reason\\\" in text\\n    forbidden = [\\\"quantity\\\", \\\"amount\\\", \\\"market_value\\\", \\\"kontostand\\\", \\\"portfolioanteil\\\", \\\"price:\\\"]\\n    assert not any(token.lower() in text.lower() for token in forbidden)\\n\\n\\ndef test_candidate_confirmation_resolves_mapping_alerts_and_writes_catalog() -> None:\\n    conn = setup_conn()\\n    for rule in [\\\"missing_provider_symbol\\\", \\\"ambiguous_provider_mapping\\\", \\\"candidate_review_required\\\"]:\\n        conn.execute(\\\"INSERT INTO alerts(alert_id,priority,category,entity_type,entity_id,rule_id,message,status,created_at) VALUES(?,?,?,?,?,?,?,?,?)\\\", (rule, \\\"warnung\\\", \\\"market_data\\\", \\\"instrument\\\", \\\"inst1\\\", rule, rule, \\\"active\\\", \\\"now\\\"))\\n    provider = StaticLookupProvider({\\\"CH0000000001\\\": [ProviderCandidate(provider=\\\"openfigi\\\", provider_symbol=\\\"GETF.SW\\\", exchange=\\\"SWX\\\", currency=\\\"CHF\\\", name=\\\"Global Equity ETF\\\", isin=\\\"CH0000000001\\\", asset_class=\\\"etf\\\", instrument_status=\\\"active\\\", evidence_source=\\\"openfigi_isin_mapping\\\")]})\\n    generate_mapping_candidates(conn, provider=provider)\\n    candidate_id = conn.execute(\\\"SELECT candidate_id FROM instrument_price_mapping_candidates\\\").fetchone()[\\\"candidate_id\\\"]\\n    select_mapping_candidate(conn, candidate_id=candidate_id, note=\\\"manual dashboard confirmation\\\")\\n    assert conn.execute(\\\"SELECT COUNT(*) AS c FROM audit_log WHERE action='select_mapping_candidate'\\\").fetchone()[\\\"c\\\"] == 1\\n    assert conn.execute(\\\"SELECT COUNT(*) AS c FROM alerts WHERE status='active' AND rule_id IN ('missing_provider_symbol','ambiguous_provider_mapping','candidate_review_required')\\\").fetchone()[\\\"c\\\"] == 0\\n    assert conn.execute(\\\"SELECT provider_symbol, exchange, trading_currency FROM instrument_price_mappings WHERE instrument_id='inst1'\\\").fetchone()[\\\"provider_symbol\\\"] == \\\"GETF.SW\\\"\\n    assert conn.execute(\\\"SELECT COUNT(*) AS c FROM instrument_catalog_entries WHERE provider_symbol='GETF.SW'\\\").fetchone()[\\\"c\\\"] == 1\\n\\n\\ndef test_candidate_rejection_writes_audit() -> None:\\n    conn = setup_conn()\\n    provider = StaticLookupProvider({\\\"CH0000000001\\\": [ProviderCandidate(provider=\\\"openfigi\\\", provider_symbol=\\\"GETF.SW\\\", exchange=\\\"SWX\\\", currency=\\\"CHF\\\", isin=\\\"CH0000000001\\\")]})\\n    generate_mapping_candidates(conn, provider=provider)\\n    candidate_id = conn.execute(\\\"SELECT candidate_id FROM instrument_price_mapping_candidates\\\").fetchone()[\\\"candidate_id\\\"]\\n    reject_mapping_candidate(conn, candidate_id=candidate_id, note=\\\"wrong listing\\\")\\n    assert conn.execute(\\\"SELECT COUNT(*) AS c FROM audit_log WHERE action='reject_mapping_candidate'\\\").fetchone()[\\\"c\\\"] == 1\\n    assert conn.execute(\\\"SELECT review_status FROM instrument_price_mapping_candidates WHERE candidate_id=?\\\", (candidate_id,)).fetchone()[\\\"review_status\\\"] == \\\"rejected\\\"\\n\\n\\ndef test_dashboard_review_ui_renders_ranked_candidates_without_live_api() -> None:\\n    conn = setup_conn()\\n    provider = StaticLookupProvider({\\\"CH0000000001\\\": [ProviderCandidate(provider=\\\"openfigi\\\", provider_symbol=\\\"GETF.SW\\\", exchange=\\\"SWX\\\", currency=\\\"CHF\\\", isin=\\\"CH0000000001\\\")]})\\n    generate_mapping_candidates(conn, provider=provider)\\n    recalculate_candidate_rankings(conn)\\n    page_13_equity_manage.render(FakeSt(), conn)\\n\\n\\ndef test_personal_finance_backlog_document_exists_without_implementation() -> None:\\n    doc = Path(\\\"docs/personal-finance-cashflow-budgeting-backlog.md\\\")\\n    assert doc.exists()\\n    text = doc.read_text(encoding=\\\"utf-8\\\")\\n    assert \\\"Backlog only\\\" in text\\n    assert \\\"Do not implement\\\" in text\\n    assert not Path(\\\"src/jarvis_finance/personal_finance\\\").exists()\\n\"}"
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        }
      ]
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    {
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      "name": "write_file",
      "content": "{\"bytes_written\": 7002, \"dirs_created\": true, \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
      "tool_call_id": "call_8oocJxRjr3ILJHdKSwByUN3L"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": "**Testing forbidden amounts**\n\nI see that I need to test for forbidden amounts, but the phrase \"Contains no quantities, values, prices...\" actually includes values and prices, which could confuse things. It seems the term \"forbidden\" is more limited to amount only, but then the source currency might not show an amount. Alright, I’ll make sure to import from the test file, but I definitely need to run those compilation tests to clarify everything!",
      "finish_reason": "tool_calls",
      "reasoning_content": "**Testing forbidden amounts**\n\nI see that I need to test for forbidden amounts, but the phrase \"Contains no quantities, values, prices...\" actually includes values and prices, which could confuse things. It seems the term \"forbidden\" is more limited to amount only, but then the source currency might not show an amount. Alright, I’ll make sure to import from the test file, but I definitely need to run those compilation tests to clarify everything!",
      "codex_reasoning_items": [
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          "type": "reasoning",
          "encrypted_content": "gAAAAABqByYIWOeoHt4tbCOrwFxtEbJIYNqmmMr_L_mAQcZi0VPjKXQeeZRZlkRSwxMo7Fg-UXwJ32Lm3HMNqGWE-kO99XcPaRLJfkoViaAQvweEqQJWTcTOiVC8DCTznu8c2-O6XNqWnxJuiic0eAr-rzc9hdcl4Z54zLM058u-Etgt5Lm8u9dg12pT1_-4f_IjMxhLYq3K2V7VdjbWt2lnWhXK0k6-rOiJzO23ZscmoLoCfXxojC0PV37vl4p1wMigQnfhkP5lxs0HY1zQCvMfRrKL0X7AUQ-2vzGhEemwP9mZSm7qqWknAgosBfDbPjn0Htj-SmeQDWN57bicTwgL0RW2A0jwPQkaHSFR0vQehcyOJ6nPpQQcay0abUNrw77JU9XjMeLqb57Op6gShyZyIxAG496r42cY8AbXEFAqo-Gh7Ty8d9-XXvjDUvPYQ8jI4U5qs-m6PvYrozU2yU7m7pl_vW-0QZrUU7jEJjjzmVSHm1rM6IR3mRab1hvUTYN-8VaTx9sPI4J3-mBlfFb9cVyaucboMp_vP5xPL6l_OayKvZswR_UvlzZVaWO7fxVmD7XdIXgiModp3mTAdJ7YvPLKvIXeGgvqg9M3nqPENH58nvHlSlRdpzWe8FRMYs6_Kzua43qHWm9cvybTrSw36vQtyYvE7hWw5p57q7UrQrAUWSA_p4J_LNcbj5GUN_QTsJmgz94MGVXAgUDUwKQTTY4FS5ajjWW60h0X_J1nznvuqPm1560Rq30M4w6T4Cgxu883_DK-IYcD0beojaCKGLuAWDXtJ6nYQgOnx5ORk1uG4NMfq2GEczQUM_etkNH0f4TAGE0UH1TsSE8FpLeI1JSEDRdmmd6Dl0z_Po6U_PLsJMzg-Vr6KlM50N7p3fYIQFkTMb54c35sulTYLRP54Qu6mF16qIWIEgEMxbv13CW-o-VHRxQ6ybH7s9CKj0m-gUoqZcLKbc4OaZ6UAhlylMYsH2QFX2BM75TQYD9q5rJsL9gFthrw6McL5sAMZovHNncUwNbmbnhgSleA9zutbbD8zFTkZuo8c79VjBU_I7XreWDpseihP3bq6xBHR-7J0F1rnFA9urOZknToGX6DJdaSMRIi2kUhrcUMht9Lf9k5vHLjZB2UnAS21qQeVhNV9GaY1e2OmasIO_FKI8JbKXqxdmMYxlyKHTUgjRbQ3OG3f6N8ubYLwOi8vwHIJ3YDAIVCM5RlQxcpFhn7VNIzKFw5uAlIvxjD88JKldaVICF4XuVMvDY=",
          "id": "rs_0134d7700e125cf0016a07260529448191896cb8935a81e1a0",
          "summary": [
            {
              "type": "summary_text",
              "text": "**Testing forbidden amounts**\n\nI see that I need to test for forbidden amounts, but the phrase \"Contains no quantities, values, prices...\" actually includes values and prices, which could confuse things. It seems the term \"forbidden\" is more limited to amount only, but then the source currency might not show an amount. Alright, I’ll make sure to import from the test file, but I definitely need to run those compilation tests to clarify everything!"
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        }
      ],
      "tool_calls": [
        {
          "id": "call_EJgP339DSYvjJ9V24g7j8Jos",
          "call_id": "call_EJgP339DSYvjJ9V24g7j8Jos",
          "response_item_id": "fc_0134d7700e125cf0016a07260893f881918b373d1cfad6bda5",
          "type": "function",
          "function": {
            "name": "terminal",
            "arguments": "{\"command\":\"PYTHONPATH=src python -m compileall -q src tests && PYTHONPATH=src pytest -q tests/unit/test_true_wealth_mapping_candidates_c3.py tests/unit/test_true_wealth_mapping_candidates_c3d.py\",\"timeout\":300,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "name": "terminal",
      "content": "{\"output\": \"==================================== ERRORS ====================================\\n____ ERROR collecting tests/unit/test_true_wealth_mapping_candidates_c3d.py ____\\nImportError while importing test module '/home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3d.py'.\\nHint: make sure your test modules/packages have valid Python names.\\nTraceback:\\n../../../.local/share/uv/python/cpython-3.11.15-linux-x86_64-gnu/lib/python3.11/importlib/__init__.py:126: in import_module\\n    return _bootstrap._gcd_import(name[level:], package, level)\\n           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\\ntests/unit/test_true_wealth_mapping_candidates_c3d.py:16: in <module>\\n    from tests.unit.test_true_wealth_mapping_candidates_c3 import FakeSt, StaticLookupProvider, setup_conn\\nE   ModuleNotFoundError: No module named 'tests.unit'\\n=========================== short test summary info ============================\\nERROR tests/unit/test_true_wealth_mapping_candidates_c3d.py\\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\\n1 error in 0.16s\", \"exit_code\": 2, \"error\": null}",
      "tool_call_id": "call_EJgP339DSYvjJ9V24g7j8Jos"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": "**Figuring out import issues**\n\nI need to resolve the issue with duplicate helpers or maybe it's impossible to make relative imports. It seems like I should test a patch or define some helpers to make this work. Using import text from c3 might be an easier option, but I'm not entirely sure yet. There’s a lot to consider, and I want to ensure that I approach this logically to find the best solution.",
      "finish_reason": "tool_calls",
      "reasoning_content": "**Figuring out import issues**\n\nI need to resolve the issue with duplicate helpers or maybe it's impossible to make relative imports. It seems like I should test a patch or define some helpers to make this work. Using import text from c3 might be an easier option, but I'm not entirely sure yet. There’s a lot to consider, and I want to ensure that I approach this logically to find the best solution.",
      "codex_reasoning_items": [
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          "id": "rs_0134d7700e125cf0016a07260b9354819198dd0520668a5c3e",
          "summary": [
            {
              "type": "summary_text",
              "text": "**Figuring out import issues**\n\nI need to resolve the issue with duplicate helpers or maybe it's impossible to make relative imports. It seems like I should test a patch or define some helpers to make this work. Using import text from c3 might be an easier option, but I'm not entirely sure yet. There’s a lot to consider, and I want to ensure that I approach this logically to find the best solution."
            }
          ]
        }
      ],
      "tool_calls": [
        {
          "id": "call_XEPX2CiA3zXkMwQbf1rYGZ1k",
          "call_id": "call_XEPX2CiA3zXkMwQbf1rYGZ1k",
          "response_item_id": "fc_0134d7700e125cf0016a07260d6b68819180fc576f4fe4c6da",
          "type": "function",
          "function": {
            "name": "patch",
            "arguments": "{\"mode\":\"replace\",\"new_string\":\"from jarvis_finance.storage.database import connect_memory\\nfrom jarvis_finance.storage.migrations import apply_migrations\\n\\n\\nclass StaticLookupProvider:\\n    name = \\\"static\\\"\\n\\n    def __init__(self, candidates_by_isin=None):\\n        self.candidates_by_isin = candidates_by_isin or {}\\n\\n    def lookup(self, *, isin, name, ticker, exchange, currency):\\n        return list(self.candidates_by_isin.get(isin, []))\\n\\n\\nclass FakeTab:\\n    def __enter__(self):\\n        return self\\n\\n    def __exit__(self, *args):\\n        return False\\n\\n\\nclass FakeSt:\\n    def title(self, *args, **kwargs): pass\\n    def caption(self, *args, **kwargs): pass\\n    def warning(self, *args, **kwargs): pass\\n    def subheader(self, *args, **kwargs): pass\\n    def write(self, *args, **kwargs): pass\\n    def success(self, *args, **kwargs): pass\\n    def error(self, *args, **kwargs): pass\\n    def info(self, *args, **kwargs): pass\\n    def divider(self, *args, **kwargs): pass\\n    def dataframe(self, *args, **kwargs): pass\\n    def table(self, *args, **kwargs): pass\\n    def tabs(self, labels): return [FakeTab() for _ in labels]\\n    def selectbox(self, label, options, **kwargs): return options[0] if options else None\\n    def text_input(self, *args, **kwargs): return kwargs.get(\\\"value\\\", \\\"\\\")\\n    def text_area(self, *args, **kwargs): return \\\"\\\"\\n    def date_input(self, *args, **kwargs): return \\\"2025-12-31\\\"\\n    def checkbox(self, *args, **kwargs): return False\\n    def expander(self, *args, **kwargs): return FakeTab()\\n    def button(self, *args, **kwargs): return False\\n\\n\\ndef setup_conn():\\n    conn = connect_memory()\\n    apply_migrations(conn)\\n    conn.execute(\\\"INSERT INTO platforms(platform_id,name,platform_type,default_currency,created_at) VALUES('p1','True Wealth','broker','CHF','now')\\\")\\n    conn.execute(\\\"INSERT INTO accounts(account_id,platform_id,account_name,account_type,currency,created_at) VALUES('a1','p1','TW','brokerage','CHF','now')\\\")\\n    conn.execute(\\\"INSERT INTO instruments(instrument_id,asset_class,name,ticker,isin,exchange,currency,created_at) VALUES('inst1','ETF','Global Equity ETF','GETF','CH0000000001',NULL,'USD','now')\\\")\\n    conn.execute(\\\"INSERT INTO transactions(transaction_id,transaction_type,account_id,instrument_id,trade_date,quantity,currency_original,fx_status,source_type,is_confirmed,quality_status,created_at) VALUES('tx1','initial_position_snapshot','a1','inst1','2025-12-31','1','USD','missing','broker_import_reviewed_snapshot',1,'warning','now')\\\")\\n    return conn\\n\",\"old_string\":\"from tests.unit.test_true_wealth_mapping_candidates_c3 import FakeSt, StaticLookupProvider, setup_conn\\n\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3d.py\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "name": "patch",
      "content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3d.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3d.py\\n@@ -13,7 +13,58 @@\\n     reject_mapping_candidate,\\n     select_mapping_candidate,\\n )\\n-from tests.unit.test_true_wealth_mapping_candidates_c3 import FakeSt, StaticLookupProvider, setup_conn\\n+from jarvis_finance.storage.database import connect_memory\\n+from jarvis_finance.storage.migrations import apply_migrations\\n+\\n+\\n+class StaticLookupProvider:\\n+    name = \\\"static\\\"\\n+\\n+    def __init__(self, candidates_by_isin=None):\\n+        self.candidates_by_isin = candidates_by_isin or {}\\n+\\n+    def lookup(self, *, isin, name, ticker, exchange, currency):\\n+        return list(self.candidates_by_isin.get(isin, []))\\n+\\n+\\n+class FakeTab:\\n+    def __enter__(self):\\n+        return self\\n+\\n+    def __exit__(self, *args):\\n+        return False\\n+\\n+\\n+class FakeSt:\\n+    def title(self, *args, **kwargs): pass\\n+    def caption(self, *args, **kwargs): pass\\n+    def warning(self, *args, **kwargs): pass\\n+    def subheader(self, *args, **kwargs): pass\\n+    def write(self, *args, **kwargs): pass\\n+    def success(self, *args, **kwargs): pass\\n+    def error(self, *args, **kwargs): pass\\n+    def info(self, *args, **kwargs): pass\\n+    def divider(self, *args, **kwargs): pass\\n+    def dataframe(self, *args, **kwargs): pass\\n+    def table(self, *args, **kwargs): pass\\n+    def tabs(self, labels): return [FakeTab() for _ in labels]\\n+    def selectbox(self, label, options, **kwargs): return options[0] if options else None\\n+    def text_input(self, *args, **kwargs): return kwargs.get(\\\"value\\\", \\\"\\\")\\n+    def text_area(self, *args, **kwargs): return \\\"\\\"\\n+    def date_input(self, *args, **kwargs): return \\\"2025-12-31\\\"\\n+    def checkbox(self, *args, **kwargs): return False\\n+    def expander(self, *args, **kwargs): return FakeTab()\\n+    def button(self, *args, **kwargs): return False\\n+\\n+\\n+def setup_conn():\\n+    conn = connect_memory()\\n+    apply_migrations(conn)\\n+    conn.execute(\\\"INSERT INTO platforms(platform_id,name,platform_type,default_currency,created_at) VALUES('p1','True Wealth','broker','CHF','now')\\\")\\n+    conn.execute(\\\"INSERT INTO accounts(account_id,platform_id,account_name,account_type,currency,created_at) VALUES('a1','p1','TW','brokerage','CHF','now')\\\")\\n+    conn.execute(\\\"INSERT INTO instruments(instrument_id,asset_class,name,ticker,isin,exchange,currency,created_at) VALUES('inst1','ETF','Global Equity ETF','GETF','CH0000000001',NULL,'USD','now')\\\")\\n+    conn.execute(\\\"INSERT INTO transactions(transaction_id,transaction_type,account_id,instrument_id,trade_date,quantity,currency_original,fx_status,source_type,is_confirmed,quality_status,created_at) VALUES('tx1','initial_position_snapshot','a1','inst1','2025-12-31','1','USD','missing','broker_import_reviewed_snapshot',1,'warning','now')\\\")\\n+    return conn\\n \\n \\n def test_candidate_ranking_prioritizes_isin_currency_exchange() -> None:\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3d.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
      "tool_call_id": "call_XEPX2CiA3zXkMwQbf1rYGZ1k"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": null,
      "finish_reason": "tool_calls",
      "tool_calls": [
        {
          "id": "call_WRzpZINiN0hGFTvuDcQI4Uw1",
          "call_id": "call_WRzpZINiN0hGFTvuDcQI4Uw1",
          "response_item_id": "fc_0134d7700e125cf0016a07261dc8ac8191ae9761d4f82ac2ca",
          "type": "function",
          "function": {
            "name": "terminal",
            "arguments": "{\"command\":\"PYTHONPATH=src python -m compileall -q src tests && PYTHONPATH=src pytest -q tests/unit/test_true_wealth_mapping_candidates_c3.py tests/unit/test_true_wealth_mapping_candidates_c3d.py\",\"timeout\":300,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "name": "terminal",
      "content": "{\"output\": \".....F..........F.....                                                   [100%]\\n=================================== FAILURES ===================================\\n__________ test_chf_hedged_candidate_remains_proposed_until_confirmed __________\\n\\n    def test_chf_hedged_candidate_remains_proposed_until_confirmed() -> None:\\n        conn = setup_conn()\\n        provider = StaticLookupProvider({'CH0000000001': [ProviderCandidate(provider='stooq', provider_symbol='GETF.SW', exchange='SWX', currency='CHF', name='Global Equity ETF CHF Hedged', isin='CH0000000001', instrument_status='active')]})\\n        generate_mapping_candidates(conn, provider=provider)\\n        row = conn.execute(\\\"SELECT candidate_is_hedged,candidate_hedged_to_currency,review_status FROM instrument_price_mapping_candidates\\\").fetchone()\\n        inst = conn.execute(\\\"SELECT hedge_status FROM instruments WHERE instrument_id='inst1'\\\").fetchone()\\n        assert row['candidate_is_hedged'] == 1\\n        assert row['candidate_hedged_to_currency'] == 'CHF'\\n>       assert row['review_status'] == 'proposed'\\nE       AssertionError: assert 'needs_manual_review' == 'proposed'\\nE         \\nE         - proposed\\nE         + needs_manual_review\\n\\ntests/unit/test_true_wealth_mapping_candidates_c3.py:150: AssertionError\\n______ test_same_isin_multiple_listings_remain_review_required_and_sorted ______\\n\\n    def test_same_isin_multiple_listings_remain_review_required_and_sorted() -> None:\\n        conn = setup_conn()\\n        provider = StaticLookupProvider({\\\"CH0000000001\\\": [\\n            ProviderCandidate(provider=\\\"openfigi\\\", provider_symbol=\\\"GETF.US\\\", exchange=\\\"NYSE\\\", currency=\\\"USD\\\", name=\\\"Global Equity ETF\\\", isin=\\\"CH0000000001\\\", asset_class=\\\"etf\\\", instrument_status=\\\"active\\\", evidence_source=\\\"openfigi_isin_mapping\\\"),\\n            ProviderCandidate(provider=\\\"openfigi\\\", provider_symbol=\\\"GETF.SW\\\", exchange=\\\"SWX\\\", currency=\\\"CHF\\\", name=\\\"Global Equity ETF\\\", isin=\\\"CH0000000001\\\", asset_class=\\\"etf\\\", instrument_status=\\\"active\\\", evidence_source=\\\"openfigi_isin_mapping\\\"),\\n        ]})\\n        generate_mapping_candidates(conn, provider=provider)\\n        summary = recalculate_candidate_rankings(conn)\\n        rows = data.get_instrument_mapping_candidates(conn)\\n        assert summary[\\\"multiple_listings_same_isin\\\"] == 1\\n        assert {r[\\\"review_status\\\"] for r in rows} == {\\\"needs_manual_review\\\"}\\n        assert int(rows[0][\\\"ranking_score\\\"]) >= int(rows[1][\\\"ranking_score\\\"])\\n        assert rows[0][\\\"ranking_reason\\\"]\\n>       assert rows[0][\\\"candidate_provider_symbol\\\"] == \\\"GETF.SW\\\"\\nE       AssertionError: assert 'GETF.US' == 'GETF.SW'\\nE         \\nE         - GETF.SW\\nE         ?       -\\nE         + GETF.US\\nE         ?      +\\n\\ntests/unit/test_true_wealth_mapping_candidates_c3d.py:95: AssertionError\\n=========================== short test summary info ============================\\nFAILED tests/unit/test_true_wealth_mapping_candidates_c3.py::test_chf_hedged_candidate_remains_proposed_until_confirmed\\nFAILED tests/unit/test_true_wealth_mapping_candidates_c3d.py::test_same_isin_multiple_listings_remain_review_required_and_sorted\\n2 failed, 20 passed in 0.48s\", \"exit_code\": 1, \"error\": null}\n\n[Tool loop warning: repeated_exact_failure_warning; count=2; terminal has failed 2 times with identical arguments. This looks like a loop; inspect the error and change strategy instead of retrying it unchanged.]",
      "tool_call_id": "call_WRzpZINiN0hGFTvuDcQI4Uw1"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": "**Adjusting test proposals**\n\nI need to consider adjusting the old test as the user wants to avoid automatic final selections. The logic may need to propose a single top selection. There seems to be a currency mismatch with the source in USD for CHF candidates requiring review. I wonder if the old test expectations can be updated since the user mentions the same ISIN listings. It might be better to set the source currency to CHF for more accurate results. I’ll need to ensure the changes align with the user’s requirements.",
      "finish_reason": "tool_calls",
      "reasoning_content": "**Adjusting test proposals**\n\nI need to consider adjusting the old test as the user wants to avoid automatic final selections. The logic may need to propose a single top selection. There seems to be a currency mismatch with the source in USD for CHF candidates requiring review. I wonder if the old test expectations can be updated since the user mentions the same ISIN listings. It might be better to set the source currency to CHF for more accurate results. I’ll need to ensure the changes align with the user’s requirements.",
      "codex_reasoning_items": [
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          "id": "rs_0134d7700e125cf0016a072622db7881919f923a9ca50ccb50",
          "summary": [
            {
              "type": "summary_text",
              "text": "**Adjusting test proposals**\n\nI need to consider adjusting the old test as the user wants to avoid automatic final selections. The logic may need to propose a single top selection. There seems to be a currency mismatch with the source in USD for CHF candidates requiring review. I wonder if the old test expectations can be updated since the user mentions the same ISIN listings. It might be better to set the source currency to CHF for more accurate results. I’ll need to ensure the changes align with the user’s requirements."
            }
          ]
        }
      ],
      "tool_calls": [
        {
          "id": "call_OB5OHd48RYibl3t6APSNOQ4J",
          "call_id": "call_OB5OHd48RYibl3t6APSNOQ4J",
          "response_item_id": "fc_0134d7700e125cf0016a0726288e388191878a8ca8e071d708",
          "type": "function",
          "function": {
            "name": "patch",
            "arguments": "{\"mode\":\"replace\",\"new_string\":\"    assert row['review_status'] == 'needs_manual_review'\",\"old_string\":\"    assert row['review_status'] == 'proposed'\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3.py\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "name": "patch",
      "content": "{\"success\": false, \"error\": \"Found 2 matches for old_string. Provide more context to make it unique, or use replace_all=True.\"}",
      "tool_call_id": "call_OB5OHd48RYibl3t6APSNOQ4J"
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    {
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      "reasoning": null,
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      "tool_calls": [
        {
          "id": "call_QxV63fLojqlYhwINvB3llhVc",
          "call_id": "call_QxV63fLojqlYhwINvB3llhVc",
          "response_item_id": "fc_0134d7700e125cf0016a07262b587c819188911c1d5239271c",
          "type": "function",
          "function": {
            "name": "patch",
            "arguments": "{\"mode\":\"replace\",\"new_string\":\"    assert row['candidate_is_hedged'] == 1\\n    assert row['candidate_hedged_to_currency'] == 'CHF'\\n    assert row['review_status'] == 'needs_manual_review'\\n    assert inst['hedge_status'] == 'unknown'\",\"old_string\":\"    assert row['candidate_is_hedged'] == 1\\n    assert row['candidate_hedged_to_currency'] == 'CHF'\\n    assert row['review_status'] == 'proposed'\\n    assert inst['hedge_status'] == 'unknown'\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3.py\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "name": "patch",
      "content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3.py\\n@@ -147,7 +147,7 @@\\n     inst = conn.execute(\\\"SELECT hedge_status FROM instruments WHERE instrument_id='inst1'\\\").fetchone()\\n     assert row['candidate_is_hedged'] == 1\\n     assert row['candidate_hedged_to_currency'] == 'CHF'\\n-    assert row['review_status'] == 'proposed'\\n+    assert row['review_status'] == 'needs_manual_review'\\n     assert inst['hedge_status'] == 'unknown'\\n \\n \\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
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      "content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3d.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3d.py\\n@@ -81,6 +81,7 @@\\n \\n def test_same_isin_multiple_listings_remain_review_required_and_sorted() -> None:\\n     conn = setup_conn()\\n+    conn.execute(\\\"UPDATE instruments SET currency='CHF', trading_currency='CHF' WHERE instrument_id='inst1'\\\")\\n     provider = StaticLookupProvider({\\\"CH0000000001\\\": [\\n         ProviderCandidate(provider=\\\"openfigi\\\", provider_symbol=\\\"GETF.US\\\", exchange=\\\"NYSE\\\", currency=\\\"USD\\\", name=\\\"Global Equity ETF\\\", isin=\\\"CH0000000001\\\", asset_class=\\\"etf\\\", instrument_status=\\\"active\\\", evidence_source=\\\"openfigi_isin_mapping\\\"),\\n         ProviderCandidate(provider=\\\"openfigi\\\", provider_symbol=\\\"GETF.SW\\\", exchange=\\\"SWX\\\", currency=\\\"CHF\\\", name=\\\"Global Equity ETF\\\", isin=\\\"CH0000000001\\\", asset_class=\\\"etf\\\", instrument_status=\\\"active\\\", evidence_source=\\\"openfigi_isin_mapping\\\"),\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/tests/unit/test_true_wealth_mapping_candidates_c3d.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
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      "content": "{\"content\": \"     1|from __future__ import annotations\\n     2|\\n     3|from jarvis_finance.storage.database import connect_memory\\n     4|from jarvis_finance.storage.migrations import apply_migrations, get_schema_version\\n     5|from jarvis_finance.storage.schema import REQUIRED_TABLES\\n     6|\\n     7|\\n     8|def test_db_schema_can_be_created() -> None:\\n     9|    conn = connect_memory()\\n    10|    apply_migrations(conn)\\n    11|    tables = {row[\\\"name\\\"] for row in conn.execute(\\\"SELECT name FROM sqlite_master WHERE type='table'\\\")}\\n    12|    assert set(REQUIRED_TABLES).issubset(tables)\\n    13|\\n    14|\\n    15|def test_schema_version_recorded() -> None:\\n    16|    conn = connect_memory()\\n    17|    apply_migrations(conn)\\n    18|    assert get_schema_version(conn) == 13\\n    19|\\n    20|\\n    21|def test_decimal_sensitive_columns_use_text_affinity() -> None:\\n    22|    conn = connect_memory()\\n    23|    apply_migrations(conn)\\n    24|    tx_cols = {row[\\\"name\\\"]: row[\\\"type\\\"] for row in conn.execute(\\\"PRAGMA table_info(transactions)\\\").fetchall()}\\n    25|    crypto_cols = {row[\\\"name\\\"]: row[\\\"type\\\"] for row in conn.execute(\\\"PRAGMA table_info(crypto_holdings)\\\").fetchall()}\\n    26|    instrument_cols = {row[\\\"name\\\"] for row in conn.execute(\\\"PRAGMA table_info(instruments)\\\").fetchall()}\\n    27|    assert tx_cols[\\\"quantity\\\"].upper() == \\\"TEXT\\\"\\n    28|    assert tx_cols[\\\"fx_rate_to_chf\\\"].upper() == \\\"TEXT\\\"\\n    29|    assert crypto_cols[\\\"quantity\\\"].upper() == \\\"TEXT\\\"\\n    30|    assert {\\\"position_category\\\", \\\"ter\\\", \\\"distribution_policy\\\", \\\"index_name\\\", \\\"fund_domicile\\\", \\\"benchmark\\\"}.issubset(instrument_cols)\\n    31|\\n    32|\\n    33|def test_broker_bank_mapping_tables_exist_with_required_columns() -> None:\\n    34|    conn = connect_memory()\\n    35|    apply_migrations(conn)\\n    36|    instrument_mapping_cols = {row[\\\"name\\\"] for row in conn.execute(\\\"PRAGMA table_info(instrument_mappings)\\\").fetchall()}\\n    37|    account_mapping_cols = {row[\\\"name\\\"] for row in conn.execute(\\\"PRAGMA table_info(platform_account_mappings)\\\").fetchall()}\\n    38|    dry_run_cols = {row[\\\"name\\\"] for row in conn.execute(\\\"PRAGMA table_info(broker_import_dry_runs)\\\").fetchall()}\\n    39|\\n    40|    assert {\\\"source_name\\\", \\\"source_platform\\\", \\\"source_label\\\", \\\"normalized_name\\\", \\\"isin\\\", \\\"ticker\\\", \\\"exchange\\\", \\\"currency\\\", \\\"asset_class\\\", \\\"instrument_id\\\", \\\"mapping_status\\\", \\\"confidence\\\", \\\"quality_flags_json\\\"}.issubset(instrument_mapping_cols)\\n    41|    assert {\\\"source_platform\\\", \\\"source_account_label\\\", \\\"normalized_platform\\\", \\\"normalized_account_name\\\", \\\"internal_platform_id\\\", \\\"internal_account_id\\\", \\\"account_type\\\", \\\"currency\\\", \\\"mapping_status\\\"}.issubset(account_mapping_cols)\\n    42|    assert {\\\"source_platform\\\", \\\"source_file_type\\\", \\\"source_filename_hash\\\", \\\"detected_snapshot_date\\\", \\\"snapshot_date_status\\\", \\\"candidate_positions\\\", \\\"candidate_cash_rows\\\", \\\"mapped_positions\\\", \\\"blocked_positions\\\", \\\"quality_flags_json\\\", \\\"summary_json\\\", \\\"session_status\\\", \\\"is_current\\\"}.issubset(dry_run_cols)\\n    43|    review_cols = {row[\\\"name\\\"] for row in conn.execute(\\\"PRAGMA table_info(broker_import_review_items)\\\").fetchall()}\\n    44|    assert {\\\"review_item_id\\\", \\\"dry_run_id\\\", \\\"source_platform\\\", \\\"source_row_ref\\\", \\\"row_hash\\\", \\\"source_label\\\", \\\"normalized_name\\\", \\\"detected_asset_class\\\", \\\"detected_currency\\\", \\\"quality_flags_json\\\", \\\"review_status\\\", \\\"import_readiness_status\\\", \\\"reviewer_confirmed\\\", 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            "arguments": "{\"command\":\"PYTHONPATH=src python -m jarvis_finance.cli.main backup-runtime-db && PYTHONPATH=src python -m jarvis_finance.cli.main rank-mapping-candidates --export-decision-pack --top-n 5\",\"timeout\":300,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
          }
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    {
      "role": "tool",
      "name": "terminal",
      "content": "{\"output\": \"RUNTIME_DB_BACKUP backup_file=/home/agent/jarvis_runtime/finance-system/backups/finance-runtime-db-20260515T135801Z.sqlite3 checksum_file=/home/agent/jarvis_runtime/finance-system/backups/finance-runtime-db-20260515T135801Z.sqlite3.sha256 sha256=2c089a2611e0778f45a30618e63f2ec6ea61515a57703566021a712591c45691 size_bytes=684032\\nTraceback (most recent call last):\\n  File \\\"<frozen runpy>\\\", line 198, in _run_module_as_main\\n  File \\\"<frozen runpy>\\\", line 88, in _run_code\\n  File \\\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/cli/main.py\\\", line 359, in <module>\\n    raise SystemExit(main())\\n                     ^^^^^^\\n  File \\\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/cli/main.py\\\", line 269, in main\\n    apply_migrations(conn)\\n  File \\\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py\\\", line 453, in apply_migrations\\n    _apply_compat_migrations(conn)\\n  File \\\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py\\\", line 442, in _apply_compat_migrations\\n    _create_fx_market_data_tables(conn)\\n  File \\\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py\\\", line 385, in _create_fx_market_data_tables\\n    conn.executescript(\\nsqlite3.OperationalError: no such column: ranking_score\", \"exit_code\": 1, \"error\": null}",
      "tool_call_id": "call_IlvXHfv7bM8TbmNXVURfIzyC"
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      "reasoning": "**Addressing index issue**\n\nI’m realizing there’s an issue with creating an index in the execute script on an existing table before adding new columns. It seems I need to move the index creation after adding the missing columns since the current table doesn't have a ranking_score. So, my plan is to remove the index from the script but keep the `conn.execute` line after I add those columns. This should help streamline things!",
      "finish_reason": "tool_calls",
      "reasoning_content": "**Addressing index issue**\n\nI’m realizing there’s an issue with creating an index in the execute script on an existing table before adding new columns. It seems I need to move the index creation after adding the missing columns since the current table doesn't have a ranking_score. So, my plan is to remove the index from the script but keep the `conn.execute` line after I add those columns. This should help streamline things!",
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              "text": "**Addressing index issue**\n\nI’m realizing there’s an issue with creating an index in the execute script on an existing table before adding new columns. It seems I need to move the index creation after adding the missing columns since the current table doesn't have a ranking_score. So, my plan is to remove the index from the script but keep the `conn.execute` line after I add those columns. This should help streamline things!"
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          "call_id": "call_q0gWP2DsiqQ1vXHxntuuVgsX",
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          "type": "function",
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            "name": "patch",
            "arguments": "{\"mode\":\"replace\",\"new_string\":\"        CREATE INDEX IF NOT EXISTS idx_ipmc_review_status ON instrument_price_mapping_candidates(review_status);\\n        CREATE INDEX IF NOT EXISTS idx_ipmc_confidence ON instrument_price_mapping_candidates(confidence);\",\"old_string\":\"        CREATE INDEX IF NOT EXISTS idx_ipmc_review_status ON instrument_price_mapping_candidates(review_status);\\n        CREATE INDEX IF NOT EXISTS idx_ipmc_confidence ON instrument_price_mapping_candidates(confidence);\\n        CREATE INDEX IF NOT EXISTS idx_ipmc_ranking_score ON instrument_price_mapping_candidates(ranking_score);\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "name": "patch",
      "content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py\\n@@ -413,7 +413,6 @@\\n         CREATE INDEX IF NOT EXISTS idx_ipmc_instrument ON instrument_price_mapping_candidates(instrument_id);\\n         CREATE INDEX IF NOT EXISTS idx_ipmc_review_status ON instrument_price_mapping_candidates(review_status);\\n         CREATE INDEX IF NOT EXISTS idx_ipmc_confidence ON instrument_price_mapping_candidates(confidence);\\n-        CREATE INDEX IF NOT EXISTS idx_ipmc_ranking_score ON instrument_price_mapping_candidates(ranking_score);\\n         \\\"\\\"\\\"\\n     )\\n     _add_missing_columns(conn, \\\"instrument_price_mapping_candidates\\\", {\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}, \"_warning\": \"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py was last read with offset/limit pagination (partial view). Re-read the whole file before overwriting it.\"}",
      "tool_call_id": "call_q0gWP2DsiqQ1vXHxntuuVgsX"
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    {
      "role": "assistant",
      "content": "",
      "reasoning": null,
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      "tool_calls": [
        {
          "id": "call_rCerbO9cqe9Lv83cxudKcw6S",
          "call_id": "call_rCerbO9cqe9Lv83cxudKcw6S",
          "response_item_id": "fc_0134d7700e125cf0016a072673d79c8191993fe0eb336ab98f",
          "type": "function",
          "function": {
            "name": "patch",
            "arguments": "{\"mode\":\"replace\",\"new_string\":\"    conn.execute(\\\"CREATE INDEX IF NOT EXISTS idx_ipmc_ranking_score ON instrument_price_mapping_candidates(ranking_score)\\\")\\n    conn.execute(\\\"CREATE UNIQUE INDEX IF NOT EXISTS idx_market_prices_unique_provider_date ON market_prices(instrument_id, price_date, provider)\\\")\",\"old_string\":\"    conn.execute(\\\"CREATE UNIQUE INDEX IF NOT EXISTS idx_market_prices_unique_provider_date ON market_prices(instrument_id, price_date, provider)\\\")\",\"path\":\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "name": "patch",
      "content": "{\"success\": true, \"diff\": \"--- a//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py\\n+++ b//home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py\\n@@ -424,6 +424,7 @@\\n         \\\"risk_flags\\\": \\\"TEXT\\\",\\n         \\\"recommended_action\\\": \\\"TEXT NOT NULL DEFAULT 'needs_manual_review'\\\",\\n     })\\n+    conn.execute(\\\"CREATE INDEX IF NOT EXISTS idx_ipmc_ranking_score ON instrument_price_mapping_candidates(ranking_score)\\\")\\n     conn.execute(\\\"CREATE UNIQUE INDEX IF NOT EXISTS idx_market_prices_unique_provider_date ON market_prices(instrument_id, price_date, provider)\\\")\\n     conn.execute(\\\"CREATE INDEX IF NOT EXISTS idx_market_prices_instrument_date ON market_prices(instrument_id, price_date)\\\")\\n     conn.execute(\\\"CREATE UNIQUE INDEX IF NOT EXISTS idx_fx_rates_unique_provider_date ON fx_rates(base_currency, quote_currency, rate_date, provider, rate_type)\\\")\\n\", \"files_modified\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py\"], \"lint\": {\"status\": \"ok\", \"output\": \"\"}}",
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            "arguments": "{\"command\":\"PYTHONPATH=src python -m jarvis_finance.cli.main rank-mapping-candidates --export-decision-pack --top-n 5\",\"timeout\":300,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
          }
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      ]
    },
    {
      "role": "tool",
      "name": "terminal",
      "content": "{\"output\": \"MAPPING_CANDIDATE_RANKING candidates_total=57 rank_high=53 rank_medium=4 rank_low=0 multiple_listings_same_isin=3 currency_mismatch=0 hedge_status_unknown=57 instrument_status_unknown=57 candidate_review_required=57 decision_pack_created=true decision_pack_instruments=3 decision_pack_candidates=57 top_candidates_present=true\", \"exit_code\": 0, \"error\": null}",
      "tool_call_id": "call_i2rv5VcVNsELN51YCWX41AAE"
    },
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      "tool_calls": [
        {
          "id": "call_HD1ojirZlcn9MH2gBrGIOVC3",
          "call_id": "call_HD1ojirZlcn9MH2gBrGIOVC3",
          "response_item_id": "fc_0134d7700e125cf0016a0726875b708191b7a7382daac31099",
          "type": "function",
          "function": {
            "name": "terminal",
            "arguments": "{\"command\":\"PYTHONPATH=src python - <<'PY'\\nfrom collections import Counter\\nfrom jarvis_finance.config.settings import load_settings\\nfrom jarvis_finance.storage.database import connect\\nfrom jarvis_finance.storage.migrations import apply_migrations\\ns=load_settings(); conn=connect(s.db_path); apply_migrations(conn)\\ninst=conn.execute(\\\"SELECT COUNT(DISTINCT instrument_id) c FROM instrument_price_mapping_candidates\\\").fetchone()['c']\\ncand=conn.execute(\\\"SELECT COUNT(*) c FROM instrument_price_mapping_candidates\\\").fetchone()['c']\\nconf=Counter({r['confidence']:r['c'] for r in conn.execute(\\\"SELECT confidence, COUNT(*) c FROM instrument_price_mapping_candidates GROUP BY confidence\\\")})\\nrank=Counter()\\nfor r in conn.execute(\\\"SELECT ranking_score FROM instrument_price_mapping_candidates\\\"):\\n    sc=int(r['ranking_score'] or 0)\\n    rank['high' if sc>=75 else 'medium' if sc>=50 else 'low']+=1\\nalerts={r['rule_id']:r['c'] for r in conn.execute(\\\"SELECT rule_id, COUNT(*) c FROM alerts WHERE status='active' AND rule_id IN ('ambiguous_provider_mapping','multiple_listings_same_isin','currency_mismatch','hedge_status_unknown','instrument_status_unknown','provider_symbol_missing','candidate_review_required','missing_provider_symbol','missing_market_price','missing_fx') GROUP BY rule_id\\\")}\\nprint({'instruments':inst,'candidates':cand,'confidence':dict(conf),'ranking':dict(rank),'alerts':alerts})\\nPY\",\"timeout\":180,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
          }
        }
      ]
    },
    {
      "role": "tool",
      "name": "terminal",
      "content": "{\"output\": \"{'instruments': 3, 'candidates': 57, 'confidence': {'high': 36, 'low': 3, 'medium': 18}, 'ranking': {'medium': 4, 'high': 53}, 'alerts': {'ambiguous_provider_mapping': 3, 'candidate_review_required': 3, 'hedge_status_unknown': 3, 'instrument_status_unknown': 3, 'missing_fx': 3, 'missing_market_price': 3, 'missing_provider_symbol': 3}}\", \"exit_code\": 0, \"error\": null}",
      "tool_call_id": "call_HD1ojirZlcn9MH2gBrGIOVC3"
    },
    {
      "role": "assistant",
      "content": "",
      "reasoning": "**Checking data quality alerts**\n\nI need to confirm that the Data Quality multiple listing alert isn't active. The user wanted a check on the DQ center, and I've computed that the alert is off via the dashboard. However, the product run requires a multiple_listings count of three from the summary, which doesn’t need real values. I should run full tests after fixing the migration and check the current safety/status in Git before proceeding.",
      "finish_reason": "tool_calls",
      "reasoning_content": "**Checking data quality alerts**\n\nI need to confirm that the Data Quality multiple listing alert isn't active. The user wanted a check on the DQ center, and I've computed that the alert is off via the dashboard. However, the product run requires a multiple_listings count of three from the summary, which doesn’t need real values. I should run full tests after fixing the migration and check the current safety/status in Git before proceeding.",
      "codex_reasoning_items": [
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              "text": "**Verifying Git and Tests**\n\nI need to do a final check on the Git status to ensure everything is clean and safe. I'll also want to run another aggregation of the runtime data, just to be sure there are no issues. And, of course, I should mention the tests, specifically test number 212. I’ll definitely make sure to use the appropriate tools for this process! Keeping everything under control is really important."
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            "arguments": "{\"command\":\"PYTHONPATH=src python - <<'PY'\\nfrom collections import Counter\\nfrom pathlib import Path\\nfrom jarvis_finance.config.settings import load_settings\\nfrom jarvis_finance.storage.database import connect\\nfrom jarvis_finance.storage.migrations import apply_migrations\\ns=load_settings(); conn=connect(s.db_path); apply_migrations(conn)\\ninst=conn.execute(\\\"SELECT COUNT(DISTINCT instrument_id) c FROM instrument_price_mapping_candidates\\\").fetchone()['c']\\ncand=conn.execute(\\\"SELECT COUNT(*) c FROM instrument_price_mapping_candidates\\\").fetchone()['c']\\nrank=Counter()\\nfor r in conn.execute(\\\"SELECT ranking_score FROM instrument_price_mapping_candidates\\\"):\\n    sc=int(r['ranking_score'] or 0); rank['high' if sc>=75 else 'medium' if sc>=50 else 'low']+=1\\nalerts={r['rule_id']:r['c'] for r in conn.execute(\\\"SELECT rule_id, COUNT(*) c FROM alerts WHERE status='active' AND rule_id IN ('ambiguous_provider_mapping','candidate_review_required','hedge_status_unknown','instrument_status_unknown','missing_provider_symbol','missing_market_price','missing_fx') GROUP BY rule_id\\\")}\\nprint({'instruments':inst,'candidates':cand,'rank':dict(rank),'alerts':alerts,'decision_pack_exists':(s.runtime_paths.exports_dir/'mapping_candidate_decision_pack.md').exists()})\\nPY\",\"timeout\":180,\"workdir\":\"/home/agent/.hermes/repos/FinanceManager\"}"
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      "content": "{\"output\": \"1d5ec58 Rank mapping candidates for manual review\", \"exit_code\": 0, \"error\": null}",
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    {
      "role": "tool",
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      "role": "tool",
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      "content": "{\"output\": \"{'instruments': 3, 'candidates': 57, 'rank': {'medium': 4, 'high': 53}, 'alerts': {'ambiguous_provider_mapping': 3, 'candidate_review_required': 3, 'hedge_status_unknown': 3, 'instrument_status_unknown': 3, 'missing_fx': 3, 'missing_market_price': 3, 'missing_provider_symbol': 3}, 'decision_pack_exists': True}\", \"exit_code\": 0, \"error\": null}",
      "tool_call_id": "call_7FDA3na21c8RNcEu4NmrC51I"
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    {
      "role": "tool",
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      "content": "{\"todos\": [{\"id\": \"c3d-0\", \"content\": \"Vorprüfung Repo/Runtime und Schema für Candidate Ranking\", \"status\": \"completed\"}, {\"id\": \"c3d-1\", \"content\": \"Candidate Ranking/Decision Pack/Data Quality implementieren\", \"status\": \"completed\"}, {\"id\": \"c3d-2\", \"content\": \"Dashboard Mapping Review UX erweitern\", \"status\": \"completed\"}, {\"id\": \"c3d-3\", \"content\": \"Personal-Finance Backlog-Dokument runtime/code-sicher vormerken\", \"status\": \"completed\"}, {\"id\": \"c3d-4\", \"content\": \"Tests ergänzen und ausführen\", \"status\": \"completed\"}, {\"id\": \"c3d-5\", \"content\": \"Produktiven vorsichtigen Runtime-Lauf aggregiert ausführen\", \"status\": \"completed\"}, {\"id\": \"c3d-6\", \"content\": \"Compile, Git-Safety, Commit und Push\", \"status\": \"completed\"}], \"summary\": {\"total\": 7, \"pending\": 0, \"in_progress\": 0, \"completed\": 7, \"cancelled\": 0}}",
      "tool_call_id": "call_mo8bAgYYJOUd9K60A2vWtlRd"
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    {
      "role": "assistant",
      "content": "Sir, Phase **C3d — Candidate Ranking, Mapping UX und User Decision Pack** ist abgeschlossen, committed und gepusht.\n\n## Status\n\n- **Commit:** `1d5ec58` — `Rank mapping candidates for manual review`\n- **Push:** erfolgreich nach `origin/main`\n- **Compile:** OK\n- **Tests:** `212 passed`\n- **Git-Safety:** `GIT_SAFETY_OK`\n- **Git Status:** clean\n- **Runtime-Backup vor Lauf:** erstellt\n- **Keine Preise abgerufen**\n- **Keine FX-Werte gesetzt**\n- **Keine weiteren Portfolio-Imports**\n- **Keine finale Mapping-Auswahl**\n- **Keine echten Mengen/Werte/Kontostände im Chat**\n\n## Implementiert\n\n### 1. Candidate Ranking\n\nPro Mapping-Kandidat werden nun berechnet:\n\n- `ranking_score`\n- `ranking_reason`\n- `risk_flags`\n- `recommended_action`\n\nUnterstützte Actions:\n\n- `select_candidate`\n- `needs_manual_review`\n- `reject_candidate`\n- `insufficient_data`\n\nWichtig: Auch `select_candidate` ist **nur Empfehlung**, keine automatische Bestätigung.\n\nRanking berücksichtigt u.a.:\n\n- ISIN-Match\n- Assetklasse\n- Währung / Trading Currency\n- Exchange\n- Provider-Symbol\n- Name-Fuzzy-Match\n- Hedge-Hinweise\n- Instrument-Status\n- Datenquelle\n- Vollständigkeit der Felder\n\nNegative Faktoren:\n\n- Währungsmismatch\n- Assetklassen-Mismatch\n- kein ISIN-Match\n- Name-only Match\n- Ticker ohne Exchange\n- unklarer Hedge-Status\n- unklarer Instrument-Status\n- mehrere Listings/Kandidaten\n\n### 2. Gleiche ISIN / verschiedene Listings\n\nExplizit berücksichtigt:\n\n- gleiche ISIN mit mehreren Exchange-/Currency-Kombinationen bleibt review-pflichtig\n- Kandidaten werden sortiert, aber **nicht automatisch gewählt**\n- Dashboard zeigt:\n  - Symbol\n  - Name\n  - ISIN\n  - Exchange\n  - Handelswährung\n  - Provider\n  - Provider-Symbol\n  - Closing/Price Currency\n  - Hedge-Status\n  - Confidence\n  - Ranking Score\n  - Ranking Reason\n  - Risk Flags\n\n### 3. Mapping Candidate Review UI erweitert\n\nIm Dashboard:\n\n- Top-Kandidaten zuerst\n- Sortierung nach `ranking_score`\n- Filter:\n  - Provider\n  - Exchange\n  - Währung\n  - Confidence\n  - Hedge-Status\n- Markierung:\n  - wahrscheinlich passend\n  - unsicher\n  - wahrscheinlich falsch\n- Begründung / Risk Flags sichtbar\n- Aktionen:\n  - Kandidat bestätigen\n  - Kandidat ablehnen\n  - manuell erfassen\n  - später prüfen / nichts tun\n\nBestätigung und Ablehnung schreiben Audit-Log.\n\n### 4. User Decision Pack\n\nRuntime-only Decision Pack wurde erzeugt.\n\nAggregiert:\n\n- Decision Pack erzeugt: **ja**\n- Instrumente: `3`\n- Kandidaten total: `57`\n- Top-Kandidaten pro Instrument vorhanden: **ja**\n- Speicherort: Runtime-Export-Verzeichnis\n- Git-Ablage: **nein**\n\nInhalt enthält keine Mengen, Depotwerte, Kaufpreise, Kontostände oder Portfolioanteile.\n\n### 5. Data Quality Center erweitert\n\nErgänzt/abgedeckt:\n\n- `ambiguous_provider_mapping`\n- `multiple_listings_same_isin`\n- `currency_mismatch`\n- `hedge_status_unknown`\n- `instrument_status_unknown`\n- `provider_symbol_missing`\n- `candidate_review_required`\n- `valuation_not_ready`\n\nRegel bleibt korrekt:\n\n- Kandidaten vorhanden, aber nicht bestätigt → `missing_provider_symbol` bleibt aktiv\n- `candidate_review_required` bleibt aktiv\n- keine automatische Resolution\n\n### 6. Mapping Confirmation Workflow gehärtet\n\nWenn später ein Kandidat bestätigt wird:\n\n- `instrument_price_mappings` wird gesetzt\n- `instrument_catalog_entry` wird aktualisiert/erstellt\n- Provider-Symbol wird gesetzt\n- Exchange wird gesetzt\n- Price/Trading Currency wird gesetzt\n- Hedge-Status kann übernommen werden\n- Instrument-Status kann übernommen werden\n- Valuation Policy wird gesetzt\n- Audit-Log wird geschrieben\n- `missing_provider_symbol` wird resolved\n- `ambiguous_provider_mapping` wird resolved\n- `candidate_review_required` wird resolved\n- falls Hedge/Status unknown bleiben, bleiben entsprechende Warnungen aktiv\n- keine Portfolio-Transaktion wird verändert\n\n### 7. Personal Finance / Budgeting Backlog\n\nBacklog wurde nur vorgemerkt, nicht implementiert.\n\nNeu:\n\n- `docs/personal-finance-cashflow-budgeting-backlog.md`\n\nVerlinkt in:\n\n- `docs/finance-backlog.md`\n\nExplizit enthalten:\n\n- Income / Lohn\n- Expense Tracking\n- Budgeting\n- Belegimport\n- Categorization Engine\n- Cashflow Dashboard\n- Security-Regeln\n\nKeine Implementation, keine Importer, keine echten Belege/CSVs. Also genau die richtige Menge an Nichtstun — selten, aber in Softwarearchitektur durchaus eine Tugend.\n\n## Geänderte/neue Dateien\n\nGeändert:\n\n- `docs/finance-backlog.md`\n- `src/jarvis_finance/cli/main.py`\n- `src/jarvis_finance/dashboard/data.py`\n- `src/jarvis_finance/dashboard/pages/page_13_equity_manage.py`\n- `src/jarvis_finance/market_data/candidates.py`\n- `src/jarvis_finance/storage/migrations.py`\n- `tests/unit/test_schema.py`\n- `tests/unit/test_true_wealth_mapping_candidates_c3.py`\n\nNeu:\n\n- `docs/personal-finance-cashflow-budgeting-backlog.md`\n- `tests/unit/test_true_wealth_mapping_candidates_c3d.py`\n\n## Tests ergänzt\n\nAbgedeckt:\n\n- Candidate Ranking nach ISIN/Währung/Exchange\n- gleiche ISIN mit mehreren Listings bleibt review-pflichtig\n- Top-Kandidaten werden sortiert\n- Ranking Reason wird erzeugt\n- Candidate Review UI rendert sortierte Kandidaten ohne Live-API\n- Decision Pack wird runtime-only erzeugt\n- Decision Pack enthält keine Mengen/Werte\n- Kandidat bestätigen schreibt Audit\n- Bestätigung resolved passende Mapping Alerts\n- Kandidat ablehnen schreibt Audit\n- Missing Provider Symbol bleibt aktiv, solange kein Kandidat bestätigt ist\n- Personal-Finance-Backlog-Dokument existiert, aber keine Implementation\n- Git-Safety OK\n\n## Produktiver vorsichtiger Runtime-Lauf\n\nAusgeführt:\n\n- Ranking für vorhandene Kandidaten berechnet\n- Top-Kandidaten pro Instrument bestimmt\n- Runtime-only Decision Pack erzeugt\n- keine finale Auswahl\n- keine Preise\n- keine FX\n- keine weiteren Imports\n\nAggregierter Stand:\n\n- Instrumente total: `3`\n- Kandidaten total: `57`\n- Top-Kandidaten pro Instrument vorhanden: **ja**\n- Ranking high: `53`\n- Ranking medium: `4`\n- Ranking low: `0`\n- `multiple_listings_same_isin`: `3`\n- `currency_mismatch`: `0`\n- `hedge_status_unknown`: `57` Kandidaten / `3` aktive Instrument-Alerts\n- `instrument_status_unknown`: `57` Kandidaten / `3` aktive Instrument-Alerts\n- Decision Pack erzeugt: **ja**\n\nAktive Mapping-/DQ-Alerts aggregiert:\n\n- `ambiguous_provider_mapping`: `3`\n- `candidate_review_required`: `3`\n- `hedge_status_unknown`: `3`\n- `instrument_status_unknown`: `3`\n- `missing_provider_symbol`: `3`\n- `missing_market_price`: `3`\n- `missing_fx`: `3`\n\nDas ist erwartungsgemäß: Kandidaten sind vorbereitet, aber nichts wurde final bestätigt.\n\n## Nächste Empfehlung\n\nAls nächstes im Dashboard:\n\n1. **Equity/ETF Manage → Review** öffnen.\n2. Pro Instrument die Top-Kandidaten prüfen.\n3. Besonders auf **Exchange + Währung** achten.\n4. Bei gleicher ISIN / mehreren Listings nicht blind den höchsten Score nehmen.\n5. Je Instrument entweder:\n   - passenden Kandidaten bestätigen,\n   - falsche Kandidaten ablehnen,\n   - manuell erfassen,\n   - oder später prüfen.\n6. Erst nach manueller Bestätigung:\n   - Mapping Alerts auflösen lassen\n   - danach frühestens Equity/ETF Preis-/FX-Pilot planen\n\nNoch nicht tun:\n\n- keine Equity/ETF-Preise abrufen\n- keine FX-Werte setzen\n- keine echten PostFinance-/TrueWealth-/Raiffeisen-Daten importieren\n- keine Portfolio-Auswertung mit nicht bestätigten Mappings ernst nehmen",
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              "text": "Sir, Phase **C3d — Candidate Ranking, Mapping UX und User Decision Pack** ist abgeschlossen, committed und gepusht.\n\n## Status\n\n- **Commit:** `1d5ec58` — `Rank mapping candidates for manual review`\n- **Push:** erfolgreich nach `origin/main`\n- **Compile:** OK\n- **Tests:** `212 passed`\n- **Git-Safety:** `GIT_SAFETY_OK`\n- **Git Status:** clean\n- **Runtime-Backup vor Lauf:** erstellt\n- **Keine Preise abgerufen**\n- **Keine FX-Werte gesetzt**\n- **Keine weiteren Portfolio-Imports**\n- **Keine finale Mapping-Auswahl**\n- **Keine echten Mengen/Werte/Kontostände im Chat**\n\n## Implementiert\n\n### 1. Candidate Ranking\n\nPro Mapping-Kandidat werden nun berechnet:\n\n- `ranking_score`\n- `ranking_reason`\n- `risk_flags`\n- `recommended_action`\n\nUnterstützte Actions:\n\n- `select_candidate`\n- `needs_manual_review`\n- `reject_candidate`\n- `insufficient_data`\n\nWichtig: Auch `select_candidate` ist **nur Empfehlung**, keine automatische Bestätigung.\n\nRanking berücksichtigt u.a.:\n\n- ISIN-Match\n- Assetklasse\n- Währung / Trading Currency\n- Exchange\n- Provider-Symbol\n- Name-Fuzzy-Match\n- Hedge-Hinweise\n- Instrument-Status\n- Datenquelle\n- Vollständigkeit der Felder\n\nNegative Faktoren:\n\n- Währungsmismatch\n- Assetklassen-Mismatch\n- kein ISIN-Match\n- Name-only Match\n- Ticker ohne Exchange\n- unklarer Hedge-Status\n- unklarer Instrument-Status\n- mehrere Listings/Kandidaten\n\n### 2. Gleiche ISIN / verschiedene Listings\n\nExplizit berücksichtigt:\n\n- gleiche ISIN mit mehreren Exchange-/Currency-Kombinationen bleibt review-pflichtig\n- Kandidaten werden sortiert, aber **nicht automatisch gewählt**\n- Dashboard zeigt:\n  - Symbol\n  - Name\n  - ISIN\n  - Exchange\n  - Handelswährung\n  - Provider\n  - Provider-Symbol\n  - Closing/Price Currency\n  - Hedge-Status\n  - Confidence\n  - Ranking Score\n  - Ranking Reason\n  - Risk Flags\n\n### 3. Mapping Candidate Review UI erweitert\n\nIm Dashboard:\n\n- Top-Kandidaten zuerst\n- Sortierung nach `ranking_score`\n- Filter:\n  - Provider\n  - Exchange\n  - Währung\n  - Confidence\n  - Hedge-Status\n- Markierung:\n  - wahrscheinlich passend\n  - unsicher\n  - wahrscheinlich falsch\n- Begründung / Risk Flags sichtbar\n- Aktionen:\n  - Kandidat bestätigen\n  - Kandidat ablehnen\n  - manuell erfassen\n  - später prüfen / nichts tun\n\nBestätigung und Ablehnung schreiben Audit-Log.\n\n### 4. User Decision Pack\n\nRuntime-only Decision Pack wurde erzeugt.\n\nAggregiert:\n\n- Decision Pack erzeugt: **ja**\n- Instrumente: `3`\n- Kandidaten total: `57`\n- Top-Kandidaten pro Instrument vorhanden: **ja**\n- Speicherort: Runtime-Export-Verzeichnis\n- Git-Ablage: **nein**\n\nInhalt enthält keine Mengen, Depotwerte, Kaufpreise, Kontostände oder Portfolioanteile.\n\n### 5. Data Quality Center erweitert\n\nErgänzt/abgedeckt:\n\n- `ambiguous_provider_mapping`\n- `multiple_listings_same_isin`\n- `currency_mismatch`\n- `hedge_status_unknown`\n- `instrument_status_unknown`\n- `provider_symbol_missing`\n- `candidate_review_required`\n- `valuation_not_ready`\n\nRegel bleibt korrekt:\n\n- Kandidaten vorhanden, aber nicht bestätigt → `missing_provider_symbol` bleibt aktiv\n- `candidate_review_required` bleibt aktiv\n- keine automatische Resolution\n\n### 6. Mapping Confirmation Workflow gehärtet\n\nWenn später ein Kandidat bestätigt wird:\n\n- `instrument_price_mappings` wird gesetzt\n- `instrument_catalog_entry` wird aktualisiert/erstellt\n- Provider-Symbol wird gesetzt\n- Exchange wird gesetzt\n- Price/Trading Currency wird gesetzt\n- Hedge-Status kann übernommen werden\n- Instrument-Status kann übernommen werden\n- Valuation Policy wird gesetzt\n- Audit-Log wird geschrieben\n- `missing_provider_symbol` wird resolved\n- `ambiguous_provider_mapping` wird resolved\n- `candidate_review_required` wird resolved\n- falls Hedge/Status unknown bleiben, bleiben entsprechende Warnungen aktiv\n- keine Portfolio-Transaktion wird verändert\n\n### 7. Personal Finance / Budgeting Backlog\n\nBacklog wurde nur vorgemerkt, nicht implementiert.\n\nNeu:\n\n- `docs/personal-finance-cashflow-budgeting-backlog.md`\n\nVerlinkt in:\n\n- `docs/finance-backlog.md`\n\nExplizit enthalten:\n\n- Income / Lohn\n- Expense Tracking\n- Budgeting\n- Belegimport\n- Categorization Engine\n- Cashflow Dashboard\n- Security-Regeln\n\nKeine Implementation, keine Importer, keine echten Belege/CSVs. Also genau die richtige Menge an Nichtstun — selten, aber in Softwarearchitektur durchaus eine Tugend.\n\n## Geänderte/neue Dateien\n\nGeändert:\n\n- `docs/finance-backlog.md`\n- `src/jarvis_finance/cli/main.py`\n- `src/jarvis_finance/dashboard/data.py`\n- `src/jarvis_finance/dashboard/pages/page_13_equity_manage.py`\n- `src/jarvis_finance/market_data/candidates.py`\n- `src/jarvis_finance/storage/migrations.py`\n- `tests/unit/test_schema.py`\n- `tests/unit/test_true_wealth_mapping_candidates_c3.py`\n\nNeu:\n\n- `docs/personal-finance-cashflow-budgeting-backlog.md`\n- `tests/unit/test_true_wealth_mapping_candidates_c3d.py`\n\n## Tests ergänzt\n\nAbgedeckt:\n\n- Candidate Ranking nach ISIN/Währung/Exchange\n- gleiche ISIN mit mehreren Listings bleibt review-pflichtig\n- Top-Kandidaten werden sortiert\n- Ranking Reason wird erzeugt\n- Candidate Review UI rendert sortierte Kandidaten ohne Live-API\n- Decision Pack wird runtime-only erzeugt\n- Decision Pack enthält keine Mengen/Werte\n- Kandidat bestätigen schreibt Audit\n- Bestätigung resolved passende Mapping Alerts\n- Kandidat ablehnen schreibt Audit\n- Missing Provider Symbol bleibt aktiv, solange kein Kandidat bestätigt ist\n- Personal-Finance-Backlog-Dokument existiert, aber keine Implementation\n- Git-Safety OK\n\n## Produktiver vorsichtiger Runtime-Lauf\n\nAusgeführt:\n\n- Ranking für vorhandene Kandidaten berechnet\n- Top-Kandidaten pro Instrument bestimmt\n- Runtime-only Decision Pack erzeugt\n- keine finale Auswahl\n- keine Preise\n- keine FX\n- keine weiteren Imports\n\nAggregierter Stand:\n\n- Instrumente total: `3`\n- Kandidaten total: `57`\n- Top-Kandidaten pro Instrument vorhanden: **ja**\n- Ranking high: `53`\n- Ranking medium: `4`\n- Ranking low: `0`\n- `multiple_listings_same_isin`: `3`\n- `currency_mismatch`: `0`\n- `hedge_status_unknown`: `57` Kandidaten / `3` aktive Instrument-Alerts\n- `instrument_status_unknown`: `57` Kandidaten / `3` aktive Instrument-Alerts\n- Decision Pack erzeugt: **ja**\n\nAktive Mapping-/DQ-Alerts aggregiert:\n\n- `ambiguous_provider_mapping`: `3`\n- `candidate_review_required`: `3`\n- `hedge_status_unknown`: `3`\n- `instrument_status_unknown`: `3`\n- `missing_provider_symbol`: `3`\n- `missing_market_price`: `3`\n- `missing_fx`: `3`\n\nDas ist erwartungsgemäß: Kandidaten sind vorbereitet, aber nichts wurde final bestätigt.\n\n## Nächste Empfehlung\n\nAls nächstes im Dashboard:\n\n1. **Equity/ETF Manage → Review** öffnen.\n2. Pro Instrument die Top-Kandidaten prüfen.\n3. Besonders auf **Exchange + Währung** achten.\n4. Bei gleicher ISIN / mehreren Listings nicht blind den höchsten Score nehmen.\n5. Je Instrument entweder:\n   - passenden Kandidaten bestätigen,\n   - falsche Kandidaten ablehnen,\n   - manuell erfassen,\n   - oder später prüfen.\n6. Erst nach manueller Bestätigung:\n   - Mapping Alerts auflösen lassen\n   - danach frühestens Equity/ETF Preis-/FX-Pilot planen\n\nNoch nicht tun:\n\n- keine Equity/ETF-Preise abrufen\n- keine FX-Werte setzen\n- keine echten PostFinance-/TrueWealth-/Raiffeisen-Daten importieren\n- keine Portfolio-Auswertung mit nicht bestätigten Mappings ernst nehmen"
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      "content": "Review the conversation above and update the skill library. Be ACTIVE — most sessions produce at least one skill update, even if small. A pass that does nothing is a missed learning opportunity, not a neutral outcome.\n\nTarget shape of the library: CLASS-LEVEL skills, each with a rich SKILL.md and a `references/` directory for session-specific detail. Not a long flat list of narrow one-session-one-skill entries. This shapes HOW you update, not WHETHER you update.\n\nSignals to look for (any one of these warrants action):\n  • User corrected your style, tone, format, legibility, or verbosity. Frustration signals like 'stop doing X', 'this is too verbose', 'don't format like this', 'why are you explaining', 'just give me the answer', 'you always do Y and I hate it', or an explicit 'remember this' are FIRST-CLASS skill signals, not just memory signals. Update the relevant skill(s) to embed the preference so the next session starts already knowing.\n  • User corrected your workflow, approach, or sequence of steps. Encode the correction as a pitfall or explicit step in the skill that governs that class of task.\n  • Non-trivial technique, fix, workaround, debugging path, or tool-usage pattern emerged that a future session would benefit from. Capture it.\n  • A skill that got loaded or consulted this session turned out to be wrong, missing a step, or outdated. Patch it NOW.\n\nPreference order — prefer the earliest action that fits, but do pick one when a signal above fired:\n  1. UPDATE A CURRENTLY-LOADED SKILL. Look back through the conversation for skills the user loaded via /skill-name or you read via skill_view. If any of them covers the territory of the new learning, PATCH that one first. It is the skill that was in play, so it's the right one to extend.\n  2. UPDATE AN EXISTING UMBRELLA (via skills_list + skill_view). If no loaded skill fits but an existing class-level skill does, patch it. Add a subsection, a pitfall, or broaden a trigger.\n  3. ADD A SUPPORT FILE under an existing umbrella. Skills can be packaged with three kinds of support files — use the right directory per kind:\n     • `references/<topic>.md` — session-specific detail (error transcripts, reproduction recipes, provider quirks) AND condensed knowledge banks: quoted research, API docs, external authoritative excerpts, or domain notes you found while working on the problem. Write it concise and for the value of the task, not as a full mirror of upstream docs.\n     • `templates/<name>.<ext>` — starter files meant to be copied and modified (boilerplate configs, scaffolding, a known-good example the agent can `reproduce with modifications`).\n     • `scripts/<name>.<ext>` — statically re-runnable actions the skill can invoke directly (verification scripts, fixture generators, deterministic probes, anything the agent should run rather than hand-type each time).\n     Add support files via skill_manage action=write_file with file_path starting 'references/', 'templates/', or 'scripts/'. The umbrella's SKILL.md should gain a one-line pointer to any new support file so future agents know it exists.\n  4. CREATE A NEW CLASS-LEVEL UMBRELLA SKILL when no existing skill covers the class. The name MUST be at the class level. The name MUST NOT be a specific PR number, error string, feature codename, library-alone name, or 'fix-X / debug-Y / audit-Z-today' session artifact. If the proposed name only makes sense for today's task, it's wrong — fall back to (1), (2), or (3).\n\nUser-preference embedding (important): when the user expressed a style/format/workflow preference, the update belongs in the SKILL.md body, not just in memory. Memory captures 'who the user is and what the current situation and state of your operations are'; skills capture 'how to do this class of task for this user'. When they complain about how you handled a task, the skill that governs that task needs to carry the lesson.\n\nIf you notice two existing skills that overlap, note it in your reply — the background curator handles consolidation at scale.\n\nDo NOT capture (these become persistent self-imposed constraints that bite you later when the environment changes):\n  • Environment-dependent failures: missing binaries, fresh-install errors, post-migration path mismatches, 'command not found', unconfigured credentials, uninstalled packages. The user can fix these — they are not durable rules.\n  • Negative claims about tools or features ('browser tools do not work', 'X tool is broken', 'cannot use Y from execute_code'). These harden into refusals the agent cites against itself for months after the actual problem was fixed.\n  • Session-specific transient errors that resolved before the conversation ended. If retrying worked, the lesson is the retry pattern, not the original failure.\n  • One-off task narratives. A user asking 'summarize today's market' or 'analyze this PR' is not a class of work that warrants a skill.\n\nIf a tool failed because of setup state, capture the FIX (install command, config step, env var to set) under an existing setup or troubleshooting skill — never 'this tool does not work' as a standalone constraint.\n\n'Nothing to save.' is a real option but should NOT be the default. If the session ran smoothly with no corrections and produced no new technique, just say 'Nothing to save.' and stop. Otherwise, act."
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      "reasoning": "**Updating tool skills**\n\nOkay, I need to focus on updating my skills, especially concerning the tools. I've loaded the finance-system-architecture but I might want to inspect if there are tools that are already loaded but not visible. Maybe using something like skill_view could help me with that. It's pretty important to make sure I have everything in place to use the right tools effectively! Let's keep track of this.",
      "finish_reason": "tool_calls",
      "reasoning_content": "**Updating tool skills**\n\nOkay, I need to focus on updating my skills, especially concerning the tools. I've loaded the finance-system-architecture but I might want to inspect if there are tools that are already loaded but not visible. Maybe using something like skill_view could help me with that. It's pretty important to make sure I have everything in place to use the right tools effectively! Let's keep track of this.",
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      "content": "{\"success\": true, \"name\": \"finance-system-architecture\", \"description\": \"Design/implement the user's JARVIS Finance System: CHF ledger, portfolio accounting, dashboard, imports, reports, secrecy.\", \"tags\": [\"finance\", \"portfolio\", \"accounting\", \"dashboard\", \"csv\", \"fx\", \"tax\", \"privacy\"], \"related_skills\": [], \"content\": \"---\\nname: finance-system-architecture\\ndescription: \\\"Design/implement the user's JARVIS Finance System: CHF ledger, portfolio accounting, dashboard, imports, reports, secrecy.\\\"\\nversion: 1.0.0\\nauthor: Hermes Agent\\nlicense: MIT\\nmetadata:\\n  hermes:\\n    tags: [finance, portfolio, accounting, dashboard, csv, fx, tax, privacy]\\n---\\n\\n# Finance System Architecture\\n\\n## When to use\\n\\nUse this skill whenever the user asks about the **Finance System – Architektur & Scripts** topic or work involving the user's personal finance-management system: portfolio imports, transaction accounting, Bank/Broker/CSV processing, dashboards, reports, tax/income views, FX logic, market data jobs, alerts, or later implementation.\\n\\nDo **not** use it for pure investment-strategy discussion; those belong in the separate finance strategy topic unless the user explicitly asks for technical implementation.\\n\\n## Core principles\\n\\n1. **No automated trading.** The system may prepare orders and recommendations, but never executes orders or connects to broker trading APIs for execution.\\n2. **Accounting first, opinions later.** MVP must prioritize correct transaction ledger, cash ledger, FX handling, income/tax data, and dashboard before complex scores, news, analyst ratings, or LLM analysis.\\n3. **Rule-based first.** Calculations, scores, alerts, rebalancing and reports must be deterministic and auditable. LLMs may only summarize/explain text or assist extraction with human review.\\n4. **CHF as base currency.** Store every transaction in original currency and CHF using historical FX at transaction/payment date; current valuations use current FX.\\n5. **Financial data secrecy.** Never expose real financial values, portfolio files, raw exports, reports with real numbers, DBs, API keys, or credentials in chat, GitHub, logs, or shared docs unless the user explicitly approves scope.\\n6. **Data ownership.** All data must be exportable: CSV, JSON, Parquet, SQLite/Postgres dump, Markdown/HTML/PDF reports.\\n\\n## Current v0.3 decisions\\n\\nSee `references/spec-v0.2-decisions.md` for the baseline, `references/spec-v0.3-decisions.md` for the priority update, `references/spec-v0.4-implementation-blueprint.md` for the MVP 1 technical implementation blueprint, `references/spec-v0.4.1-corrections.md` for accepted corrections, `references/spec-v0.5-repo-blueprint.md` for the concrete repo/implementation plan, `references/mvp-safety-gate-implementation.md` for the implementation safety-gate sequence and verification commands, `references/mvp-import-pipeline-tasks-9-13.md` for the synthetic CSV import/FX/transaction pipeline pattern, `references/mvp-ledger-cash-wac-positions.md` for cash/WAC/position ledger calculation rules and tests, `references/mvp-crypto-wallet-ledger.md` for crypto wallet/assets/holdings/transfers/buy-sell/fee MVP rules, `references/crypto-xlsx-initial-snapshot-dry-run.md` for the controlled real-file XLSX crypto initial-snapshot dry-run pattern and mapping decisions, `references/crypto-xlsx-initial-snapshot-production-import.md` for productive safe-subset XLSX import operations, compatibility/partial-write recovery, and dashboard correction follow-up, `references/crypto-single-coin-runtime-test.md` for controlled one-coin productive runtime tests and the coin-vs-holding ambiguity guard, `references/multi-wallet-crypto-and-equity-manage-ui.md` for approved multi-wallet single-coin snapshots, SQLite Decimal/TEXT affinity pitfalls, and synthetic-first Equity/ETF Manage UI patterns, `references/crypto-price-refresh-and-idempotent-btc-runtime.md` for robust batch price refresh and re-run-safe BTC/single-coin runtime checks, `references/crypto-runtime-db-consistency-verification.md` for post-import runtime DB consistency checks, exact safe-set verification, dashboard no-live-API testing, and runtime-only report generation, `references/mvp-crypto-manual-management-ui.md` for audited dashboard add/correct/remove crypto holding workflows after an initial snapshot, `references/mvp-market-import-safety-hardening.md` for CoinGecko provider/backoff, CSV importer completion, alert lifecycle, Git-safety and crypto Decimal precision patterns, `references/git-safety-verification-coverage.md` for the verifier-warning workflow and minimum Git-safety test matrix, `references/mvp-streamlit-dashboard.md` for the safe local Streamlit dashboard shell/read-model/testing pattern, `references/mvp-crypto-report-export.md` for local-only crypto report context/export rules, `references/github-token-push-from-drive.md` for the safe Google-Drive-token push workflow when local FinanceManager commits are ahead of GitHub, `references/runtime-backup-and-broker-mapping.md` for runtime DB backup/restore hardening plus PostFinance/True Wealth/Raiffeisen structural mapping/dry-run rules, `references/import-wizard-mapping-layer.md` for the Phase B1 import wizard, instrument/account mapping, review queue, data-quality and read-only safety pattern, `references/broker-parser-dry-run-pipeline.md` for the Phase B2 synthetic broker parser, dry-run, runtime review-item and UI quality-flag pipeline, `references/controlled-real-broker-dry-run.md` for the Phase B3 controlled real-file dry-run pattern with backup, aggregate-only reporting, runtime-only review items, and no productive position writes, and `references/broker-review-queue-hardening.md` for Phase B4 manual review queue filters, auditable mapping actions, import-readiness gating, dry-run session management, and Data Quality Center hardening without productive portfolio writes, and `references/guided-manual-review-pilot.md` for Phase B5 small-scope runtime metadata pilots that move selected review items to `ready_for_import` without productive imports, `references/broker-import-execution-plan-mini-import.md` for Phase B6 final dry-run execution plans plus exactly-one productive broker mini-import, `references/broker-mini-import-regression-and-corrections.md` for post-mini-import regression, void/correction workflows, backup/restore checks, and one-at-a-time follow-up imports, and `references/broker-mini-import-completion-and-dq-consolidation.md` for completing the last ready True-Wealth mini-import plus active-vs-resolved Data Quality alert consolidation, `references/equity-fx-market-data-phase-c.md` for the local FX/market-data foundation after broker mini-imports and before broader Equity/ETF valuation/imports, and `references/true-wealth-valuation-pilot-c2.md` for the True-Wealth valuation pilot safeguards around hedge metadata, provider mappings, historical FX failures, timestamp alignment, corporate-action flags, and aggregate-only runtime reporting, `references/true-wealth-mapping-candidate-review-c3.md` for the controlled mapping-candidate review pattern before any productive Equity/ETF price or FX valuation, `references/instrument-catalog-manual-add-workflow.md` for the general Instrument Catalog + dashboard manual-add workflow that must underpin future Equity/ETF/Crypto adds, and `references/public-instrument-lookup-candidate-generator.md` for runtime-only public metadata lookups, candidate review packs, alert dedupe, and no-auto-selection rules. Key decisions:\\n\\n- Platform/account views: Raiffeisen, PostFinance, True Wealth, Crypto-Coins, plus Gesamtansicht.\\n- Existing Google Drive files under `Finanzen/01 Aktueller Stand Portfolios` are **initial-snapshot reality checks**, not full ledgers.\\n- MVP means the smallest useful first version: correct data foundation, ledger, CHF/FX logic, platform views, crypto inventory, watchlist, reports, workflows and audit log.\\n- Stock/ETF tax documents are downgraded: optional reference/control module and dividend/distribution transparency, not MVP 1 and not a complete tax dossier replacement.\\n- Crypto inventory is promoted to MVP 1: wallet/platform-level holdings, Crypto PDF, CoinGecko valuation, stale-price warnings and manual verification.\\n- Crypto snapshot values are stale; use quantities only and recalculate current values via CoinGecko later.\\n- MVP dashboard recommendation: Streamlit + SQLite + SQLAlchemy/Pandas/Plotly; later migrateable to FastAPI + React/PostgreSQL.\\n- MVP inputs: manual dashboard entry, standard CSV import/export, later broker/bank export import. No direct broker integrations initially.\\n- Telegram crypto buys/sells/transfers should be parsed as pending transactions and only saved after explicit confirmation.\\n- Every portfolio or crypto change must create a History/Audit entry.\\n\\n## Required data model areas\\n\\nAt minimum design for:\\n\\n- `platforms`, `accounts`, `instruments`\\n- `transactions` with original currency and CHF fields\\n- `cash_ledger`\\n- derived `positions_current`\\n- `dividends_distributions`\\n- `market_prices`, `fx_rates`\\n- `watchlist_items`\\n- `alerts`\\n- `decision_journal`\\n- `reports`\\n- `data_quality_issues`\\n\\n## CSV/import rules\\n\\n- For broker/bank imports (PostFinance, True Wealth, Raiffeisen), build the safe review layer before productive imports: Import Wizard, instrument mappings, platform/account mappings, dry-run summaries, Manual Review Queue, Data Quality Center and visible read-only/write-enabled state. Follow `references/import-wizard-mapping-layer.md`. When wiring parser output into the wizard, use the synthetic-first parser/dry-run/review-item pipeline in `references/broker-parser-dry-run-pipeline.md`. After explicit approval for real-file dry-runs, follow `references/controlled-real-broker-dry-run.md`: preflight, verified runtime backup, temp-only file handling, aggregate-only reporting, runtime-only review items, and verification that productive positions/ledger rows stayed unchanged. When the user asks to make real dry-run results manually editable, follow `references/broker-review-queue-hardening.md`: add filters/detail views, auditable review-metadata actions, per-item/session import-readiness status, dry-run session management, and Data Quality Center counts while keeping productive portfolio writes disabled. For a guided manual-review pilot on real runtime items, follow `references/guided-manual-review-pilot.md`: select 1–3 clear ETF/equity items (prefer True Wealth), write only audited review metadata, correct only presence booleans if needed, derive `ready_for_import` via readiness logic, and verify productive tables remain unchanged. Before the first productive broker position import, follow `references/broker-import-execution-plan-mini-import.md`: create runtime-only execution plans from the ready review items, validate exact Decimal-text payloads from the runtime source, preserve missing FX/cost-basis quality flags, then import exactly one ledger `initial_position_snapshot` after a verified backup; do not write `positions_snapshot` as the source of truth. After the first mini-import and before broader imports, follow `references/broker-mini-import-regression-and-corrections.md`: verify import links/audit/Decimal handling/re-import blocking, add or test safe void/correction flows, run backup/restore-to-test-DB regression, and only then optionally import one more ready plan. When the user approves finishing a remaining small set, follow `references/broker-mini-import-completion-and-dq-consolidation.md`: first disambiguate active vs resolved stale crypto alerts with `check-data-quality --scope crypto --resolve-fixed`, then import exactly one remaining ready execution plan after backup/verify, and consolidate Review Queue/Data Quality counts without exposing values.\\n- Do not pivot into later analytics modules while the user has asked for import/mapping hardening. Monte Carlo, backtesting, rebalancing, scores, heatmaps and projections are later phases unless explicitly re-authorized.\\n- Use a canonical CSV format before broker-specific importers.\\n- Imports must be idempotent via external transaction ID or row hash.\\n- Importers must separate dry-run and commit modes, collect validation errors explicitly, and always create an `import_sessions` record even for dry runs or failed imports.\\n- Import results should classify rows as new, existing, duplicate, or failed; do not rely on `INSERT OR IGNORE` as the only duplicate-detection mechanism.\\n- Row hashes must be stable and deterministic: normalize key order, whitespace, and `None` versus empty strings while leaving domain-specific canonicalization to the importer.\\n- If a source file has only current holdings and no full history, import it as `initial_position_snapshot` / `initial_cash_snapshot`, not fake historical buys.\\n- Missing historic FX, fees, taxes, dates, investment case, target weights, or dividend details must be flagged as data-quality gaps.\\n\\n## FX and return rules\\n\\nFor foreign currency assets, always distinguish:\\n\\n- price/security performance in original currency\\n- FX effect to CHF\\n- realized P&L\\n- unrealized P&L\\n- dividends/distributions/income\\n- fees and taxes\\n- Total Return in CHF\\n\\nEvery transaction/income event needs:\\n\\n- original amount and currency\\n- historical FX rate to CHF, or explicit `fx_status=missing` with a critical data-quality alert\\n- FX source and timestamp\\n- CHF equivalent at event date when FX is known\\n\\nManual FX overrides require a non-empty note and an audit-log entry.\\n\\n## Ledger calculation rules\\n\\n- Cash after system start must be calculated from `transactions`; `cash_balances` is only a snapshot/cache/control view.\\n- `initial_cash_snapshot` and `initial_position_snapshot` are explicit starting truths, not fabricated historical trades.\\n- Implement Weighted Average Cost as the MVP internal performance method: buy fees increase cost basis, partial sells remove proportional cost basis, realized P&L is calculated against average cost, full sells zero remaining quantity/cost basis, and dividends do not alter quantity or cost basis.\\n- WAC is not tax-complete; do not add FIFO/LIFO/tax-lot logic in MVP 1, but keep transaction granularity so it can be added later.\\n- Position calculations must keep zero-quantity historical positions visible when sale history exists.\\n- Missing market price or FX must degrade data quality and suppress precise Total Return CHF rather than inventing a value.\\n- Before productive dashboard use, add alert deduplication per rule/entity/date.\\n- Market-FX for non-CHF market prices belongs to the later Market/FX provider block.\\n\\n## Crypto MVP rules\\n\\n- Crypto inventory is MVP-critical but must remain dummy-first until mapper/dry-run layers are ready; do not touch real coin/wallet files during core implementation. After explicit user approval, real files may be read only from temp/runtime for controlled dry runs using `references/crypto-xlsx-initial-snapshot-dry-run.md`; report only aggregate counts/labels and never quantities or values. Productive safe-subset imports require a second explicit approval and must follow `references/crypto-xlsx-initial-snapshot-production-import.md`: external runtime DB only, no real CSV/XLSX/reports/DBs in Git, Git-safety before/after, import-session + audit-log creation, and aggregate-only reporting.\\n- Wallet names must be unique; wallet addresses are optional and must not appear in tests/fixtures.\\n- Validate wallet type against: Hardware Wallet, Software Wallet, Exchange, Bank/Broker, DeFi, Sonstiges.\\n- CoinGecko ID is strongly recommended but not hard-required; missing ID creates a data-quality warning and blocks reliable valuation.\\n- Crypto symbols are not globally unique; symbol conflicts require warning/manual selection, never silent merging.\\n- Initial crypto holdings are confirmed snapshots by wallet+asset. Store legacy values for provenance/control only, never current valuation.\\n- Crypto holdings should be calculated/controlled from initial snapshots plus crypto transactions, not silently overwritten.\\n- Crypto transfers require different source/target wallets, quantity > 0, and same asset; coin fees reduce source-wallet balance.\\n- Negative wallet balances should be blocked in MVP and produce a critical alert unless a future explicit correction workflow is implemented.\\n- Crypto buys/sells with fiat impact must create/reference general ledger transactions via `source_type='crypto'`/`source_id` so cash remains ledger-consistent.\\n- Fiat fees should be ledger fees when unambiguous; avoid double counting when a fee is already embedded in sell net proceeds.\\n- Unknown fee currency creates a data-quality warning instead of invented accounting.\\n- Crypto Cost Basis/WAC is not required for MVP 1; MVP 1 prioritizes crypto holdings, wallet structure, current valuation, reports and audit.\\n- Crypto report context/export must be renderer-neutral and local-only: build from SQLite, aggregate by coin and wallet, use local cached prices only, preserve Decimal/Text values, ignore legacy snapshot values for current valuation, include data-quality warnings, and write generated files only to the external runtime reports directory.\\n- Crypto PDF export should be optional-dependency tolerant: prefer PDF when a renderer is available, otherwise fall back to HTML/Markdown with a clear warning while still recording report metadata and audit.\\n- After productive real-data crypto imports, run the post-import runtime verification in `references/crypto-runtime-db-consistency-verification.md`: exact safe-set membership checks, aggregate-only counts, audit/import-session traceability, dashboard render with no live API, runtime-only report generation, and Git-safety before/after.\\n- Manual dashboard additions/corrections/removals after an initial snapshot must follow `references/mvp-crypto-manual-management-ui.md`: no silent `crypto_holdings` mutation, explicit confirmation, mandatory notes for adjustments/removals, audit-log entries with old/new values, Decimal/TEXT quantity handling, no negative holdings, and no live API lookup during render.\\n- Crypto tax logic, tax lots, FIFO/LIFO and detailed cost basis are later modules.\\n- Keep crypto assets separate from `instruments` for MVP 1, but later evaluate a shared Asset Master if it improves reporting, performance views or watchlists.\\n\\n## Income/tax rules\\n\\nFor dividends and ETF distributions, separately store:\\n\\n- gross dividend/distribution\\n- Swiss withholding tax 35%\\n- foreign withholding tax\\n- other tax/withholding if present\\n- net amount\\n- original currency\\n- historic FX to CHF\\n- gross/net CHF equivalents\\n- platform/account\\n- ISIN/ticker\\n- payment date\\n- ex-dividend date if available\\n\\nPlan later ESTV/ICTax support for Swiss year-end values and tax reports, but label outputs as technical reports, not tax advice.\\n\\n## Market-data rules\\n\\n- Dashboard reads primarily from local DB, not directly from APIs on page load.\\n- For Equity/ETF FX and market-data hardening after broker mini-imports, follow `references/equity-fx-market-data-phase-c.md`: validate active `missing_fx` alerts by original transaction currency first, correct only CHF false positives with audit, keep foreign-currency missing-FX alerts active until local historical rates exist, use ISIN as instrument identity and provider symbols only as market-data mappings, and run market-price providers only from explicit CLI/scheduled jobs.\\n- For the True-Wealth valuation pilot, follow `references/true-wealth-valuation-pilot-c2.md`: do not import more positions, do not guess provider symbols or hedge status, extend instrument metadata for currency hedging/status/valuation policy/corporate-action state, handle historical-FX paywalls as `manual_override_required` without crashing, align price/FX timestamps before claiming valuation precision, and report only aggregate runtime counts.\\n- For True-Wealth mapping-candidate review after the valuation pilot, follow `references/true-wealth-mapping-candidate-review-c3.md`: create runtime-only provider-symbol candidates keyed by ISIN/instrument, keep name-only or ticker-without-exchange candidates review-required, mark multiple candidates `needs_manual_review`, do not auto-select final mappings on ambiguity, keep hedge/instrument status unknown until confirmed, and ensure market-price dry runs call no provider when there are zero confirmed mappings. For public metadata lookup implementation details, provider result caps, OpenFIGI/Yahoo evidence handling, alert dedupe, runtime-only review templates, and UI/test requirements, use `references/public-instrument-lookup-candidate-generator.md`.\\n- For the broader Instrument Catalog + manual-add workflow, follow `references/instrument-catalog-manual-add-workflow.md`: documents/import files are initial-population aids, but the dashboard must allow audited manual add of equities/ETFs and later coins via search, candidate selection, account/wallet selection, Decimal/Text quantity, date, cost-basis/snapshot info and notes. ISIN is primary for equities/ETFs but can have multiple listings; ticker/symbol alone is never unique; provider symbols are market-data mappings only; CoinGecko ID is primary for crypto provider identity. External lookups may use only non-confidential instrument metadata and must never send quantities, balances, account/wallet IDs, cost basis, private notes or source documents.\\n- First Streamlit MVP should be a safe, local, read-first shell over SQLite with explicit synthetic demo DB creation only; page render functions must not call CoinGecko/market APIs, and tests should prove that by monkeypatching provider methods to fail.\\n- Use scheduled jobs to update prices/FX/news.\\n- Store provider, timestamp, quality status and freshness for every price/FX point.\\n- Implement caching, local historical storage, batch requests where possible, provider rate-limit queues, and backoff on HTTP 429.\\n- CoinGecko integrations must be mockable and unit-tested without real API calls; treat HTTP 429 as non-fatal and return a non-fresh data-quality status plus alert after configured retries.\\n- Crypto price refresh belongs in CLI/scheduled-job commands, not dashboard/report rendering. Prefer CoinGecko batch requests over per-coin requests; expose conservative controls (`--sleep-seconds`, `--max-retries`, `--initial-backoff`, `--max-backoff`, `--only-missing`, `--only-stale`, `--only-symbol`, `--limit`, `--dry-run`, `--currency`). Commands should use aggregate-only output (`total_assets/updated/cached/skipped/stale/warnings/errors/assets_still_missing_local_price`), cache by configurable `max_age_seconds`, store exact Decimal prices as TEXT in `crypto_prices`, and verify dashboard/report contexts read local prices with `live_api_calls=False`. For details and tests see `references/crypto-price-refresh-and-idempotent-btc-runtime.md`.\\n- Candidate providers: Finnhub, Financial Modeling Prep, Twelve Data, Stooq, Alpha Vantage selectively, Yahoo Finance fallback only; CoinGecko for crypto; later DefiLlama; ESTV/ICTax for Swiss tax values.\\n\\n## Crypto Decimal precision rules\\n\\nSQLite has no exact native DECIMAL. In the crypto context, store quantities, prices, crypto fees and valuation-relevant amounts as exact Decimal strings (`TEXT`) and compute with Python `Decimal`. Never convert crypto quantity/price/fee/valuation through float/REAL. Format Decimal writes with `format(value, \\\"f\\\")` so small quantities such as `0.00000001` do not become scientific notation. CSV importers must validate Decimal strings, and tests should assert high-precision preservation plus SQLite text storage. For multi-wallet real-data snapshots and Equity/ETF ledger fields, also see `references/multi-wallet-crypto-and-equity-manage-ui.md`; SQLite `NUMERIC` affinity can coerce Decimal-looking text to `real`, so schema/migrations should use `TEXT` for exact quantities, FX rates, original amounts and CHF equivalents where precision matters.\\n\\n## Alert lifecycle rules\\n\\nAlerts must be deduplicated and lifecycle-aware before dashboards run repeated calculations. Use a dedup key from `rule_id`, `entity_type`, `entity_id`, `priority` and an error fingerprint. Alerts should carry `status` (`active`, `resolved`, `muted`), `resolved_at`, optional `muted_until`, `last_seen_at`, `occurrence_count`, `fingerprint` and `dedup_key`. Re-seeing an identical active/resolved/muted alert should update `last_seen_at`/`occurrence_count` rather than create a new active row; changed fingerprints may create a new alert.\\n\\n## Git/GitHub safety\\n\\nCode/scripts/docs may be stored in a private Git repo, but never commit financial data. Use the `github-repo-management` skill and its `references/sensitive-code-backup.md` guidance.\\n\\nMinimum `.gitignore` for finance repos must block `data/`, `reports/`, `exports/`, `backups/`, DB files, spreadsheets, PDFs, DOCX, raw CSV/JSON, `.env`, tokens, credentials and client secrets. Only synthetic examples under `examples/` are acceptable.\\n\\n## MVP implementation safety gate\\n\\nBefore any real broker/bank/portfolio/crypto data is imported, build and verify the safety foundation described in `references/mvp-safety-gate-implementation.md`: repo skeleton, `.gitignore`, `.env.example`, runtime outside repo, settings validation, SQLite schema, synthetic fixtures, audit log, CSV dry-run, duplicate protection, and Git-safety scan. Run the safety scan before staging, committing, or pushing. If GitHub credentials are needed from Drive, use them only in a temporary location and never echo token values.\\n\\nBefore broader productive imports, implement or verify the runtime backup loop in `references/runtime-backup-and-broker-mapping.md`: backup outside Git, SHA256 verification, restore requiring explicit confirmation, tests for backup/restore/checksum, and Git-safety coverage that blocks backup artifacts in the repo. For PostFinance/True Wealth/Raiffeisen, perform structural mapping and dry-runs only until the user approves import; report aggregate counts/field coverage/quality flags only, never real values or raw rows.\\n\\n## Common pitfalls\\n\\n- Starting later analytics (Monte Carlo, backtesting, rebalancing, scoring, heatmaps, projections) while import/mapping/data-quality phases are still being hardened or while the user explicitly asked to postpone them.\\n- Treating a holdings snapshot as a real transaction history.\\n- Mixing price P&L and FX P&L.\\n- Letting dashboard refreshes hammer APIs.\\n- Committing realistic sample data to Git because the repo is private. Private GitHub is not a financial data vault.\\n- Showing real portfolio values back to the user unnecessarily in summaries.\\n- Designing Git-safety scans that block source package names like `src/.../imports` or `src/.../reports`; block top-level runtime/data directories instead.\\n- In broker/bank real-file dry-runs, aggregating Data Quality flags only for `review_status='open'`. Blocked review items are still actionable data-quality issues; include `open` and `blocked` so defensive Raiffeisen aggregate-only rows remain visible.\\n- Letting manual review actions blur into productive import actions. Review-metadata writes (ISIN/ticker/exchange/account/instrument confirmations, ignore/resolve, dry-run archive/current status) may be allowed with audit logs, but they must not write `positions_snapshot`, `transactions`, `cash_balances`, ledger rows, or cash snapshots. Name-only mapping must never become `mapped`/`ready_for_import`; ticker-only without exchange remains review-needed; `aggregate_only` remains blocked for instrument import. In guided pilots, do not force `ready_for_import` by direct status edits; let readiness logic derive it after audited metadata actions, and if parser presence flags were missed, correct only boolean presence metadata with an audit event, never actual quantities/values.\\n- Skipping the execution-plan layer between ready review items and productive broker imports. A final dry-run should materialize runtime-only execution plans with source row hash, target IDs, exact Decimal-text payload summary, quality flags and planned write status. Productive mini-imports should consume exactly one planned ready payload, write exactly one ledger `initial_position_snapshot`, mark that plan/review item imported, leave the other ready plans untouched, and verify zero direct `positions_snapshot`/cash writes. After the first productive mini-import, do not proceed straight to mass import: run regression checks, implement/test void and correction audit paths, verify backup/restore to a separate test DB, and import at most one additional ready plan. When later completing the final ready plan, first resolve Data Quality alert ambiguity by counting only active alerts (`status='active'`) and treating resolved rows as history; then import exactly one plan and consolidate counts. See `references/broker-import-execution-plan-mini-import.md`, `references/broker-mini-import-regression-and-corrections.md`, and `references/broker-mini-import-completion-and-dq-consolidation.md`.\\n- Running compile/tests before Git-safety and forgetting generated `__pycache__`; remove or ignore generated caches before safety scans. `pytest` may recreate `.pytest_cache`, so remove `__pycache__`/`.pytest_cache` again after test execution and before `git-safety-scan`.\\n- Treating every active `missing_fx` alert after a broker mini-import as a bug. First aggregate by original currency: CHF rows may be false positives (`fx=1`, `not_needed`, resolve with audit), but foreign-currency rows without local historical FX should remain active and block precise CHF valuation until rates are populated.\\n- Auto-mapping Equity/ETF market prices by instrument name or ticker alone. ISIN is the instrument identity, but one ISIN can have multiple listings across exchange/currency, so even ISIN matches may need candidate selection. Provider symbols are separate market-data mappings, ticker without exchange is review-needed, and missing provider symbols should create deduplicated Data Quality alerts rather than triggering provider guesses. For mapping-candidate phases, candidate creation is allowed in the runtime DB, but final selection must remain manual/audited unless the user explicitly approves and the match is unambiguous. Public lookup endpoints can return dozens of listings; cap result sets, dedupe active mapping alerts by rule/entity, and do not treat search-fallback results as ISIN-confirmed unless the provider response supplies ISIN evidence.\\n- Designing future portfolio entry as import-file-only. Imports/documents are for initial population and existing holdings; the system must also support dashboard manual add/search workflows with audited ledger writes, explicit candidate selection, Decimal/Text quantities, required notes where history is incomplete, and no silent overwrites. See `references/instrument-catalog-manual-add-workflow.md`.\\n- Letting an Equity/ETF market-price dry run call providers when no confirmed mappings exist. The safe outcome is `total_mappings=0`, no provider calls, and aggregate reporting only.\\n- For valuation pilots on historical broker snapshots, treating a computable current market value as a clean performance result. `snapshot_only`, `cost_basis_uncertain`, missing hedge confirmation, missing historical FX, stale price/FX timestamp alignment, or suspected corporate actions must keep valuation `partially_valuable` or suppress precise Total Return until reviewed.\\n- Inferring CHF-hedged ETF behavior from the name alone. Hedge status is methodology-critical: unknown status should create a warning/review item; confirmed CHF hedging must prevent naive free FX-PnL attribution.\\n- Crashing or blocking on historical-FX provider paywalls. Persist `manual_override_required`, create deduplicated alerts, keep the flow moving, and require a noted audited manual override instead of guessing latest FX.\\n- Productive real-data imports can partially write before surfacing schema/importer compatibility issues. Do not rerun blindly or dump row-level data; inspect aggregate counts and unique identifiers needed for idempotency, patch/complete via missing-only inserts, then verify committed import session, audit log, Git clean and Git-safety OK.\\n- In controlled one-coin runtime tests from a real XLSX, distinguish **one coin/asset** from **one holding/wallet row**. A coin may be split across multiple wallet columns; if the user required an unambiguous target wallet or one holding, stop and ask rather than choosing a wallet silently. If the user explicitly approves multi-wallet import for that coin, import exactly one asset plus one audited holding per non-empty approved wallet cell; verify aggregate counts only. If re-running a BTC/single-coin test finds the exact approved asset and holdings already present, do not import duplicates; perform the aggregate-only idempotency checks and report that asset/holding counts did not increase because duplicate prevention succeeded. See `references/crypto-single-coin-runtime-test.md`, `references/multi-wallet-crypto-and-equity-manage-ui.md`, and `references/crypto-price-refresh-and-idempotent-btc-runtime.md`.\\n- After productive crypto imports, do a separate aggregate-only consistency pass before building new features: DB/runtime outside repo, exact safe-subset membership, no duplicate/negative/orphan holdings, correct snapshot date, null legacy-value fields when ignored, import sessions committed, holding-level audit traces present, dashboard local-read/no-live-API verified, and report generated only under runtime reports.\\n- Letting a dashboard correction UI mutate crypto holdings directly. Add/remove/edit operations must become audited transactions or `manual_adjustment` events with mandatory notes where appropriate; preserve history instead of silently overwriting balances.\\n- Treating verifier/file-mutation warnings as either automatically true or automatically false. 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            "arguments": "{\"action\":\"write_file\",\"name\":\"finance-system-architecture\",\"file_path\":\"references/mapping-candidate-ranking-decision-pack.md\",\"file_content\":\"# Mapping Candidate Ranking + Decision Pack Workflow\\n\\nUse this reference after public instrument lookup candidates exist, and before any productive Equity/ETF price or FX valuation uses provider mappings.\\n\\n## Purpose\\n\\nTurn raw provider-symbol candidates into a manual-review decision aid without auto-selecting mappings or exposing portfolio values.\\n\\n## Required behavior\\n\\n- Persist candidate-level review metadata in runtime DB only:\\n  - `ranking_score`\\n  - `ranking_reason`\\n  - `risk_flags`\\n  - `recommended_action`\\n- Recommended actions are advisory only:\\n  - `select_candidate`\\n  - `needs_manual_review`\\n  - `reject_candidate`\\n  - `insufficient_data`\\n- Do **not** final-select provider mappings automatically when there is ambiguity.\\n- Same ISIN can represent multiple listings; exchange and trading currency still matter.\\n- Ticker without exchange remains review-needed.\\n- Name-only matches are weak evidence and should not become ready mappings.\\n- Unknown hedge status and unknown instrument status should remain Data Quality issues until confirmed.\\n\\n## Ranking signals\\n\\nPositive signals:\\n\\n- ISIN match from provider evidence\\n- asset-class match\\n- trading/price currency match\\n- exchange match\\n- provider-symbol/ticker match with exchange context\\n- name similarity\\n- active instrument status\\n- trusted evidence source such as ISIN-based lookup\\n\\nNegative/risk signals:\\n\\n- `currency_mismatch`\\n- `asset_class_mismatch`\\n- `isin_missing_or_mismatch`\\n- `ticker_without_exchange`\\n- `name_only_match`\\n- `multiple_listings_same_isin`\\n- `hedge_status_unknown`\\n- `instrument_status_unknown`\\n\\n## Data Quality alerts\\n\\nCreate/dedupe active alerts for:\\n\\n- `ambiguous_provider_mapping`\\n- `candidate_review_required`\\n- `multiple_listings_same_isin`\\n- `currency_mismatch`\\n- `hedge_status_unknown`\\n- `instrument_status_unknown`\\n- `missing_provider_symbol`\\n- `valuation_not_ready`\\n\\nA candidate being present does **not** resolve `missing_provider_symbol`. Resolve mapping-related alerts only after an audited selection writes the confirmed provider mapping.\\n\\n## Dashboard review UX\\n\\nShow top candidates first, with filters for provider, exchange, currency, confidence and hedge status. The reviewer must see:\\n\\n- instrument name / ISIN / symbol\\n- provider and provider symbol\\n- candidate exchange and currency\\n- confidence\\n- ranking score\\n- ranking reason\\n- risk flags\\n- hedge status\\n- instrument status\\n\\nAllowed actions:\\n\\n- confirm candidate with non-empty review note\\n- reject candidate with audit log\\n- manually enter mapping/catalog metadata\\n- defer review without writes\\n\\n## Decision pack\\n\\nGenerate a runtime-only decision pack for user review:\\n\\n- store outside Git under runtime exports\\n- include top candidates and reasons\\n- include no quantities, balances, prices, market values, cost basis, portfolio percentages, account IDs, wallet IDs, or raw broker rows\\n- report aggregate counts only in chat\\n\\n## Confirmation workflow\\n\\nWhen a candidate is manually confirmed:\\n\\n1. Write/update `instrument_price_mappings`.\\n2. Write/update `instrument_catalog_entries` as appropriate.\\n3. Preserve provider evidence/source metadata.\\n4. Write audit-log entry.\\n5. Resolve mapping alerts such as `missing_provider_symbol`, `ambiguous_provider_mapping`, `candidate_review_required`.\\n6. Keep hedge/status/fx/price alerts active if still unknown or missing.\\n7. Do not write portfolio transactions, positions, prices, FX, or valuations.\\n\\n## Migration pitfall\\n\\nWhen adding columns and indexes in compatibility migrations, add missing columns first and only then create indexes that reference the new columns. Existing runtime DBs may already have the table without the new column; creating the index too early fails with `no such column`.\\n\\n## Verification checklist\\n\\n- Unit tests cover ranking order, multiple listings for same ISIN, no auto-selection, audit-log writes, alert resolution after confirmation, rejection audit, dashboard render without live API, and decision-pack secrecy.\\n- Full test suite passes.\\n- Remove `.pytest_cache` and `__pycache__` before Git-safety scans if tests were run.\\n- Git-safety passes before commit/push.\\n- Productive runtime run reports only aggregate candidate/instrument/alert counts.\\n\"}"
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            "arguments": "{\"action\":\"patch\",\"name\":\"finance-system-architecture\",\"new_string\":\"- For True-Wealth mapping-candidate review after the valuation pilot, follow `references/true-wealth-mapping-candidate-review-c3.md`: create runtime-only provider-symbol candidates keyed by ISIN/instrument, keep name-only or ticker-without-exchange candidates review-required, mark multiple candidates `needs_manual_review`, do not auto-select final mappings on ambiguity, keep hedge/instrument status unknown until confirmed, and ensure market-price dry runs call no provider when there are zero confirmed mappings. For public metadata lookup implementation details, provider result caps, OpenFIGI/Yahoo evidence handling, alert dedupe, runtime-only review templates, and UI/test requirements, use `references/public-instrument-lookup-candidate-generator.md`. For ranking/scoring candidates, generating a runtime-only user decision pack, surfacing `candidate_review_required` and same-ISIN multiple-listing risks, and confirming/rejecting candidates with audit logs, use `references/mapping-candidate-ranking-decision-pack.md`.\",\"old_string\":\"- For True-Wealth mapping-candidate review after the valuation pilot, follow `references/true-wealth-mapping-candidate-review-c3.md`: create runtime-only provider-symbol candidates keyed by ISIN/instrument, keep name-only or ticker-without-exchange candidates review-required, mark multiple candidates `needs_manual_review`, do not auto-select final mappings on ambiguity, keep hedge/instrument status unknown until confirmed, and ensure market-price dry runs call no provider when there are zero confirmed mappings. For public metadata lookup implementation details, provider result caps, OpenFIGI/Yahoo evidence handling, alert dedupe, runtime-only review templates, and UI/test requirements, use `references/public-instrument-lookup-candidate-generator.md`.\"}"
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              "text": "Updated the loaded umbrella skill **`finance-system-architecture`**.\n\nChanges made:\n\n- Added new support reference:\n  - `references/mapping-candidate-ranking-decision-pack.md`\n\n- Patched `SKILL.md` to point future sessions to that reference from:\n  - Current decision/reference index\n  - Market-data / True-Wealth mapping-candidate workflow section\n\nCaptured reusable lessons:\n\n- Candidate ranking should remain advisory, not auto-select mappings.\n- Same ISIN can still require manual review because exchange/currency/listing differ.\n- Candidate presence does not resolve `missing_provider_symbol`; only audited confirmation does.\n- Runtime-only decision packs must exclude quantities, values, balances, prices, cost basis, account IDs, wallet IDs, and raw broker rows.\n- Confirmation workflow should write mapping/catalog metadata and audit logs, but not prices, FX, positions, transactions, or valuations.\n- Migration pitfall: add missing columns before creating indexes referencing those columns on existing runtime DBs.\n- Verification checklist includes dashboard no-live-API render, alert dedupe/resolution, audit-log tests, aggregate-only runtime reporting, and Git-safety cleanup after pytest cache generation."
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