{ "session_id": "20260516_213441_2a355f", "model": "gpt-5.5", "base_url": "https://chatgpt.com/backend-api/codex", "platform": "telegram", "session_start": "2026-05-16T21:34:41.708387", "last_updated": "2026-05-16T21:36:40.394092", "system_prompt": "You are Hermes Agent, an intelligent AI assistant created by Nous Research. You are helpful, knowledgeable, and direct. You assist users with a wide range of tasks including answering questions, writing and editing code, analyzing information, creative work, and executing actions via your tools. You communicate clearly, admit uncertainty when appropriate, and prioritize being genuinely useful over being verbose unless otherwise directed below. Be targeted and efficient in your exploration and investigations.\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\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\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\n\n\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\n\n\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\n\n\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\n\n\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\n\n\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\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\nConversation started: Saturday, May 16, 2026 09:34 PM\nModel: gpt-5.5\nProvider: openai-codex", "tools": [ { "type": "function", "function": { "name": "patch", "description": "Targeted find-and-replace edits in files. Use this instead of sed/awk in terminal. Uses fuzzy matching (9 strategies) so minor whitespace/indentation differences won't break it. Returns a unified diff. Auto-runs syntax checks after editing.\n\nREPLACE MODE (mode='replace', default): find a unique string and replace it. REQUIRED PARAMETERS: mode, path, old_string, new_string.\nPATCH MODE (mode='patch'): apply V4A multi-file patches for bulk changes. REQUIRED PARAMETERS: mode, patch.", "parameters": { "type": "object", "properties": { "mode": { "type": "string", "enum": [ "replace", "patch" ], "description": "Edit mode. 'replace' (default): requires path + old_string + new_string. 'patch': requires patch content only.", "default": "replace" }, "path": { "type": "string", "description": "REQUIRED when mode='replace'. File path to edit." }, "old_string": { "type": "string", "description": "REQUIRED when mode='replace'. Exact text to find and replace. Must be unique in the file unless replace_all=true. Include surrounding context lines to ensure uniqueness." }, "new_string": { "type": "string", "description": "REQUIRED when mode='replace'. Replacement text. Pass empty string '' to delete the matched text." }, "replace_all": { "type": "boolean", "description": "Replace all occurrences instead of requiring a unique match (default: false)", "default": false }, "patch": { "type": "string", "description": "REQUIRED when mode='patch'. V4A format patch content. Format:\n*** Begin Patch\n*** Update File: path/to/file\n@@ context hint @@\n context line\n-removed line\n+added line\n*** End Patch" } }, "required": [ "mode" ] } } }, { "type": "function", "function": { "name": "process", "description": "Manage background processes started with terminal(background=true). Actions: 'list' (show all), 'poll' (check status + new output), 'log' (full output with pagination), 'wait' (block until done or timeout), 'kill' (terminate), 'write' (send raw stdin data without newline), 'submit' (send data + Enter, for answering prompts), 'close' (close stdin/send EOF).", "parameters": { "type": "object", "properties": { "action": { "type": "string", "enum": [ "list", "poll", "log", "wait", "kill", "write", "submit", "close" ], "description": "Action to perform on background processes" }, "session_id": { "type": "string", "description": "Process session ID (from terminal background output). Required for all actions except 'list'." }, "data": { "type": "string", "description": "Text to send to process stdin (for 'write' and 'submit' actions)" }, "timeout": { "type": "integer", "description": "Max seconds to block for 'wait' action. Returns partial output on timeout.", "minimum": 1 }, "offset": { "type": "integer", "description": "Line offset for 'log' action (default: last 200 lines)" }, "limit": { "type": "integer", "description": "Max lines to return for 'log' action", "minimum": 1 } }, "required": [ "action" ] } } }, { "type": "function", "function": { "name": "read_file", "description": "Read a text file with line numbers and pagination. Use this instead of cat/head/tail in terminal. Output format: 'LINE_NUM|CONTENT'. Suggests similar filenames if not found. Use offset and limit for large files. Reads exceeding ~100K characters are rejected; use offset and limit to read specific sections of large files. NOTE: Cannot read images or binary files — use vision_analyze for images.", "parameters": { "type": "object", "properties": { "path": { "type": "string", "description": "Path to the file to read (absolute, relative, or ~/path)" }, "offset": { "type": "integer", "description": "Line number to start reading from (1-indexed, default: 1)", "default": 1, "minimum": 1 }, "limit": { "type": "integer", "description": "Maximum number of lines to read (default: 500, max: 2000)", "default": 500, "maximum": 2000 } }, "required": [ "path" ] } } }, { "type": "function", "function": { "name": "search_files", "description": "Search file contents or find files by name. Use this instead of grep/rg/find/ls in terminal. Ripgrep-backed, faster than shell equivalents.\n\nContent search (target='content'): Regex search inside files. Output modes: full matches with line numbers, file paths only, or match counts.\n\nFile search (target='files'): Find files by glob pattern (e.g., '*.py', '*config*'). Also use this instead of ls — results sorted by modification time.", "parameters": { "type": "object", "properties": { "pattern": { "type": "string", "description": "Regex pattern for content search, or glob pattern (e.g., '*.py') for file search" }, "target": { "type": "string", "enum": [ "content", "files" ], "description": "'content' searches inside file contents, 'files' searches for files by name", "default": "content" }, "path": { "type": "string", "description": "Directory or file to search in (default: current working directory)", "default": "." }, "file_glob": { "type": "string", "description": "Filter files by pattern in grep mode (e.g., '*.py' to only search Python files)" }, "limit": { "type": "integer", "description": "Maximum number of results to return (default: 50)", "default": 50 }, "offset": { "type": "integer", "description": "Skip first N results for pagination (default: 0)", "default": 0 }, "output_mode": { "type": "string", "enum": [ "content", "files_only", "count" ], "description": "Output format for grep mode: 'content' shows matching lines with line numbers, 'files_only' lists file paths, 'count' shows match counts per file", "default": "content" }, "context": { "type": "integer", "description": "Number of context lines before and after each match (grep mode only)", "default": 0 } }, "required": [ "pattern" ] } } }, { "type": "function", "function": { "name": "terminal", "description": "Execute shell commands on a Linux environment. Filesystem usually persists between calls.\n\nDo NOT use cat/head/tail to read files — use read_file instead.\nDo NOT use grep/rg/find to search — use search_files instead.\nDo NOT use ls to list directories — use search_files(target='files') instead.\nDo NOT use sed/awk to edit files — use patch instead.\nDo NOT use echo/cat heredoc to create files — use write_file instead.\nReserve terminal for: builds, installs, git, processes, scripts, network, package managers, and anything that needs a shell.\n\nForeground (default): Commands return INSTANTLY when done, even if the timeout is high. Set timeout=300 for long builds/scripts — you'll still get the result in seconds if it's fast. Prefer foreground for short commands.\nBackground: Set background=true to get a session_id. Two patterns:\n (1) Long-lived processes that never exit (servers, watchers).\n (2) Long-running tasks with notify_on_complete=true — you can keep working on other things and the system auto-notifies you when the task finishes. Great for test suites, builds, deployments, or anything that takes more than a minute.\nFor servers/watchers, do NOT use shell-level background wrappers (nohup/disown/setsid/trailing '&') in foreground mode. Use background=true so Hermes can track lifecycle and output.\nAfter starting a server, verify readiness with a health check or log signal, then run tests in a separate terminal() call. Avoid blind sleep loops.\nUse process(action=\"poll\") for progress checks, process(action=\"wait\") to block until done.\nWorking directory: Use 'workdir' for per-command cwd.\nPTY mode: Set pty=true for interactive CLI tools (Codex, Claude Code, Python REPL).\n\nDo NOT use vim/nano/interactive tools without pty=true — they hang without a pseudo-terminal. Pipe git output to cat if it might page.\n", "parameters": { "type": "object", "properties": { "command": { "type": "string", "description": "The command to execute on the VM" }, "background": { "type": "boolean", "description": "Run the command in the background. Two patterns: (1) Long-lived processes that never exit (servers, watchers). (2) Long-running tasks paired with notify_on_complete=true — you can keep working and get notified when the task finishes. For short commands, prefer foreground with a generous timeout instead.", "default": false }, "timeout": { "type": "integer", "description": "Max seconds to wait (default: 180, foreground max: 600). Returns INSTANTLY when command finishes — set high for long tasks, you won't wait unnecessarily. Foreground timeout above 600s is rejected; use background=true for longer commands.", "minimum": 1 }, "workdir": { "type": "string", "description": "Working directory for this command (absolute path). Defaults to the session working directory." }, "pty": { "type": "boolean", "description": "Run in pseudo-terminal (PTY) mode for interactive CLI tools like Codex, Claude Code, or Python REPL. Only works with local and SSH backends. Default: false.", "default": false }, "notify_on_complete": { "type": "boolean", "description": "When true (and background=true), you'll be automatically notified exactly once when the process finishes. **This is the right choice for almost every long-running task** — tests, builds, deployments, multi-item batch jobs, anything that takes over a minute and has a defined end. Use this and keep working on other things; the system notifies you on exit. MUTUALLY EXCLUSIVE with watch_patterns — when both are set, watch_patterns is dropped.", "default": false }, "watch_patterns": { "type": "array", "items": { "type": "string" }, "description": "Strings to watch for in background process output. HARD RATE LIMIT: at most 1 notification per 15 seconds per process — matches arriving inside the cooldown are dropped. After 3 consecutive 15-second windows with dropped matches, watch_patterns is automatically disabled for that process and promoted to notify_on_complete behavior (one notification on exit, no more mid-process spam). USE ONLY for truly rare, one-shot mid-process signals on LONG-LIVED processes that will never exit on their own — e.g. ['Application startup complete'] on a server so you know when to hit its endpoint, or ['migration done'] on a daemon. DO NOT use for: (1) end-of-run markers like 'DONE'/'PASS' — use notify_on_complete instead; (2) error patterns like 'ERROR'/'Traceback' in loops or multi-item batch jobs — they fire on every iteration and you'll hit the strike limit fast; (3) anything you'd ever combine with notify_on_complete. When in doubt, choose notify_on_complete. MUTUALLY EXCLUSIVE with notify_on_complete — set one, not both." } }, "required": [ "command" ] } } }, { "type": "function", "function": { "name": "write_file", "description": "Write content to a file, completely replacing existing content. Use this instead of echo/cat heredoc in terminal. Creates parent directories automatically. OVERWRITES the entire file — use 'patch' for targeted edits. Auto-runs syntax checks on .py/.json/.yaml/.toml and other linted languages; only NEW errors introduced by this write are surfaced (pre-existing errors are filtered out).", "parameters": { "type": "object", "properties": { "path": { "type": "string", "description": "Path to the file to write (will be created if it doesn't exist, overwritten if it does)" }, "content": { "type": "string", "description": "Complete content to write to the file" } }, "required": [ "path", "content" ] } } } ], "message_count": 18, "messages": [ { "role": "user", "content": "Inspect runtime SQLite schema and aggregate-only identify Review/Test/True Wealth Review Brokerage artifacts to clean up. Return table names/columns and safe SQL approach with no real values/quantities. Do not modify DB." }, { "role": "assistant", "content": "", "reasoning": "**Inspecting SQLite schema**\n\nI'm considering how to inspect the SQLite schema. Should I use the terminal with `sqlite3`? That seems like a solid option. I might also want to read the repository for the database tables. It could be helpful to run commands like `.tables` or `.schema` in the terminal. Plus, I should check if the database exists in the first place. It feels like there are a lot of steps, but I'm on the right track!", "finish_reason": "tool_calls", "reasoning_content": "**Inspecting SQLite schema**\n\nI'm considering how to inspect the SQLite schema. Should I use the terminal with `sqlite3`? That seems like a solid option. I might also want to read the repository for the database tables. It could be helpful to run commands like `.tables` or `.schema` in the terminal. Plus, I should check if the database exists in the first place. It feels like there are a lot of steps, but I'm on the right track!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqCMbZhMMQz7WyXTGb0INUX56nrveotWmkAFUkfoQfC8ZarFGSEGnAC2fMmo_xkND6bdXZh8QWB5lRotJ2wlEJozwuLIhzJWR8s4QzWdeoFYiDeMHR0IeHwVU7Br_G7KkW8qY5Al3LnxVCpqtZZ6c-1kYPsu-_UuSVvov6OsoYTL5UKfNJ_cpVJstPGDo4sHu-Lq5_EZT7JRKFhv1wD1OutiJEEZOcEKj29nAPGsj8NeYLZscv-hljwOP5LYOT_sfKHsR205Pj0PF12eT96H2C13KJNDVdTp9wWQGXwI2wnXJUO2LbYr8y0rKP2ho51AdbFq5ZJz0CMguyhnMvHNoxg1rdNH0tT1YQF4ONMOXCvyGCNFSicG3kkGHBCO7Y1-PxO0WwhzdDFg4PaTwUv7MEpdg6BWWKYQRpJY4PujIXvz2fYqX1E1lYInlUnteaZp_0J9Og8V6AdiJAa05HuDhDD7frYRj0Tn3joAdHIBQIGzd0Ip_wF9LJC5d92mECml__YKr2qsNGOevBSGNtp5hmKZS-AbGbhDyLUmfnnVoKIxZG2rO5fkl-urXd99UfI42F9wGFJTc4k5gW68yB8LaGNc5ve1MJqpH1_XDLDgvcrzApgvJDL4kLmx7DZxdyjfpGcmtiWGvOrZ9OoYFuCW9ICtsnyOt10TGcLjuiafsGMzCFIvYec6bgpCrTJ1t0WZIhXYknpOPNt1e2JscIEp3SrTb6bMdqCsh3PpAs68x3xJDtQNk4huXGTQSyrM_CzA3zSLgbuHcEKjxSJJFzybtPQc7yr5xpwCD0rbtD1QuymBvaCdeFOY6EbvTOM9jbzrbe22ocWjLsXoir3nBMoq4VdsiBszf5FtZxYoEVWUKvYbjojVrjs1ZgeXUlHOSqK992wMele0tlGaqvKUZQ0ygle3f_S9xP7KfswTTQJEuGyUL62YfIqAaQrv2ox5iB_aiy9kBidRS_xf6_uWlJKHYn7jN7IlP7Jd8-Eli3wUnCuH7tddX8Fx_syewlZAsa21zKdZ5RWk2ZNoNti_TF6cVenI1YegfZ4qXt7FVLrrbqklOe6pIdT7wzoub2OQ_LtPfxeQUs5eOljUV5C7LI2ml06u7ALBzIyMpdPuzqj_OYSHx6Sbv4hnuOneNdIC60FCkvxAbo3jTYKvYnyD3IihOvZk2eCGuZ2b_KymKF-VSiT_FAc7zEP3fUg4DyfENuOVa4sCYvxBjMtGL6jZSAaoG6aKyZ1Ix1-ttf3nPgLNAB7IPKk6V3r1YTcNGureLK7rX1dTyBFkPuA6ECHbUKYgRj0Viu4hj0aoHhoOef0pzI0CO_3LbTLH8ApuceKYsPwd6D3SNA-P2zCCIMQbhhkB-PSiPd0pVNEXsaDpY9DIbGyxma6QakVf3qbTT62gO6k8wYyzd_YLysdY1ARk1V-6VhP6keEsWIDRu5txFBnKM45lkvEd5XH674SnfLFxRKgjQL-KLiv-ifrZV5koEd45bIyv6SaS5izJxHEMx9ZBY9Cc73Tob6NsyUrbCL27RIe8SIbUTFAXNA2aDMzKmnAxVCOonuqsdczEo1MmstCDJEh2HdWRcObdHoBjJ5b-mQUTmMwSmEPKVUU3wmsKSe9mbaLrdhkr6_U5AQ0jtmUfXNJDaHEWwtETh0WPp7j0f_cdkT59Qh13fg2o_kgBkiilrOLmnYC171Ap0ltvQKCD-kbZyno9rzTpA6NJzRuUvon8oqYlU6FQZ0sr0rqvT8_r_IiNx7APtVJtfbtdhbG5sLnaBCb_5ovDhBEoaShkVnF87XgOhfHyjtLtkrWCFrRQ3nznJ868qW_xgs1H4U_UiH10a__xCW-A1rgfxeeZ94UHW5z00g0cB2LS2XKG-9FTUKEzXrailawpbQhaw3cRzP0ZW66d9j-CuCdFN7NLYPpUeW1H_0fHMOTJ3USiOMR2u4CV9pOektQMspxD1LXsmVP2EXDdSHtsVJ-8nUg5N8LAYlDezgzJyrY88w-PhrsvuhgbTPYOFmh_-8-09xXu5FYcfGx6xI4sbKZ4mhANVwqHAaF_vmnOxylz3kkn-Gw4PGt2EhwXJWC5EOJjVdJ9zKBWR7rlQOlBNIVn_0OeNLjcAYOPbW4dC32BmI5DO7VMSLqr50A10HagkA-C39rP5WvcQatjHCK_4CaRCYdz7gIZ01Re6bp0z8U2oyXxuX2tdTsnM72shQAZ2W8k_8JLFp_a7UJWt2P08UC47VfbQvpfr32N4UqVNmuMGraSyFytJ7R-gfHEInvlX9IlnrTjipoPBhYMXrNDo89-MRprdEfIPPVvfTijCYt52EERfbVMFu20OQ2vMdE-lt_5Arwup1FEqN0Qssb0e11ItpcB88PRQCGY9yJxBfl8wN8aP0hiWxu7kYmK0reL7JEKnI7uHl8npb6UtwAadujNDNqO_tnZZFRBrChNk0JtLcpuPGOTIbgSbV6avjet76Oe4COOsRrqEAYLZejAdFoDB0Znr5zEO7GjbT", "id": "rs_056d840a7e61d49e016a08c6d2eaa48191b36f8f2416918ab6", "summary": [ { "type": "summary_text", "text": "**Inspecting SQLite schema**\n\nI'm considering how to inspect the SQLite schema. Should I use the terminal with `sqlite3`? That seems like a solid option. I might also want to read the repository for the database tables. It could be helpful to run commands like `.tables` or `.schema` in the terminal. Plus, I should check if the database exists in the first place. It feels like there are a lot of steps, but I'm on the right track!" } ] } ], "tool_calls": [ { "id": "call_q1gvbWVBqcUBxomgj6zKkHgR", "call_id": "call_q1gvbWVBqcUBxomgj6zKkHgR", "response_item_id": "fc_056d840a7e61d49e016a08c6d9dbec8191a6031bed3b81cbb8", "type": "function", "function": { "name": "search_files", "arguments": "{\"target\":\"files\",\"path\":\"/home/agent/jarvis_runtime/finance-system/data\",\"pattern\":\"*.sqlite3\",\"limit\":20}" } }, { "id": "call_gyOHAA5NGIRXE5BsmwQCM0kF", "call_id": "call_gyOHAA5NGIRXE5BsmwQCM0kF", "response_item_id": "fc_056d840a7e61d49e016a08c6d9dc0081919a85bb59da2b642b", "type": "function", "function": { "name": "search_files", "arguments": "{\"target\":\"files\",\"path\":\"/home/agent/jarvis_runtime/finance-system/uat-vue-dashboard/data\",\"pattern\":\"*.sqlite3\",\"limit\":20}" } }, { "id": "call_iW89q2AG8kPOhoY7o7JSPdNu", "call_id": "call_iW89q2AG8kPOhoY7o7JSPdNu", "response_item_id": "fc_056d840a7e61d49e016a08c6d9dc088191868c1cdbef6873be", "type": "function", "function": { "name": "search_files", "arguments": "{\"target\":\"files\",\"path\":\"/home/agent/.hermes/repos/FinanceManager\",\"pattern\":\"*.py\",\"limit\":20}" } } ] }, { "role": "tool", "name": "search_files", "content": "{\"total_count\": 2, \"files\": [\"/home/agent/jarvis_runtime/finance-system/data/finance.sqlite3\", \"/home/agent/jarvis_runtime/finance-system/data/backups/finance.pre-portfolio-ui-20260516T134252Z.sqlite3\"]}", "tool_call_id": "call_q1gvbWVBqcUBxomgj6zKkHgR" }, { "role": "tool", "name": "search_files", "content": "{\"total_count\": 1, \"files\": [\"/home/agent/jarvis_runtime/finance-system/uat-vue-dashboard/data/finance.sqlite3\"]}", "tool_call_id": "call_gyOHAA5NGIRXE5BsmwQCM0kF" }, { "role": "tool", "name": "search_files", "content": "{\"total_count\": 20, \"files\": [\"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/services/crypto_service.py\", \"/home/agent/.hermes/repos/FinanceManager/tests/unit/test_fastapi_vue_cockpit_v11.py\", \"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/services/manual_entry_service.py\", \"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/api/routers/crypto.py\", \"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/api/main.py\", \"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/api/routers/cash.py\", \"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/api/routers/positions.py\", \"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/api/schemas/positions.py\", \"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/database.py\", \"/home/agent/.hermes/repos/FinanceManager/tests/unit/test_fastapi_user_dashboard_skeleton.py\", \"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/api/routers/reports.py\", \"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/services/report_service.py\", \"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/api/schemas/reports.py\", \"/home/agent/.hermes/repos/FinanceManager/tests/unit/test_git_safety.py\", \"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/quality/git_safety.py\", \"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/services/equity_service.py\", \"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/api/routers/equity.py\", \"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/services/cash_service.py\", \"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/services/portfolio_service.py\", \"/home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/services/api_helpers.py\"]}", "tool_call_id": "call_iW89q2AG8kPOhoY7o7JSPdNu" }, { "role": "assistant", "content": "", "reasoning": "**Retrieving schema details**\n\nI need to get the schema, so I'll be using sqlite3 for that, which means sending some queries. I think I'll have to discover the tables and their columns. It feels like it might involve a bit of digging to understand the structure since databases can be complex. I wonder if there are specific queries I can run to gather all that information efficiently. Let’s see what I can find!", "finish_reason": "tool_calls", "reasoning_content": "**Retrieving schema details**\n\nI need to get the schema, so I'll be using sqlite3 for that, which means sending some queries. I think I'll have to discover the tables and their columns. It feels like it might involve a bit of digging to understand the structure since databases can be complex. I wonder if there are specific queries I can run to gather all that information efficiently. Let’s see what I can find!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqCMbecFIQ0XSDcW6ohQkUPdr-y-V1auiKOlXtTO2nhVC0hT5GGzTaawOkUizR0cqTMvWrgcAhEBtW-nv2ikZxCLKOVcnwbwmjpe2Nk1NbAUWzWTvxKI9X1119hAZQXpw2SOyzVA2W9YcVCTBmCehbds4UNy1gYkNaCs2a1Ng5R9-YHDVu-rUsjkasdnSsrh1DlMz3tpTk3VXc7hAsLe_N2yd3ixnYTzcrOs_wCCchsJHsO6NORzImMs5zJ5XoBu5_1n4_YyH0dyNLrKFeNO3SMkQkdClUMmMw7jmylwzcytdK0EiyQ3ZBoXNGHiegGP_c_ROZ9F7nACYhw9R-kY7QWZSFONPI6oEyoTez0Z-FU2jPYf8m98cZ88Oai-m3YtF77bNFRz1RRmil0Jvu7h_Zg0nf4TLXmr9iVh0m6L8mpHjUZCpIzLtj98CqwXkj-_nbQiHuv3WNVJgSjpnztVYgCOy2jQrc5y0z-Gg7TgGAfs_wEAxRCnv98QMgcQoBB3ncnTIAhE861IQWhEnx332FZzMWtc7WHfHKQGJgP0vYzUf-7tcDfKBspX9KZTju0BiXfFmeKOme2IfxOuxyaD0gH1gvnuwUQavSRooI-jgUvRosC6OGGuVIR9rjjTYEkKtyaA28Rh6AHY0aXZb6VFunCsSxQyVU9QpBSiHucm714HlzcS5sBV4iVoqxiJwBzyUNp986mg45Q7EOXAqz7rs85VDLnRNanLjg2tj3VMNLM6KToplKoRSXkD-qMllzwJD0cPWhukSy3BZWiG7xeUzIjRAHLgLXqOjtk9KwgYYxLehF-8p951R9_3LnHJuMth8lRd7dbDpX4qmN50MxMzchoXlnGeM1Uj0RYPoIuB4pw4QvWkS4f9ZHjk4Ptl4IJJ_R3otR7qT4URiaKjBlmaqEyU-HhSi3w9zacqKNDSawkYHuTpGZQHtjt2WcQYoA54NoE67XvvqhMZcAFLKTFmuM7VN-g0Z_D_pAZq6pBhj1TAcqtEIc96pg2vyNrRgyUMtJKxsH", "id": "rs_0e150df8343ebf8f016a08c6dbfb5c8191b1da09d6ed817177", "summary": [ { "type": "summary_text", "text": "**Retrieving schema details**\n\nI need to get the schema, so I'll be using sqlite3 for that, which means sending some queries. I think I'll have to discover the tables and their columns. It feels like it might involve a bit of digging to understand the structure since databases can be complex. I wonder if there are specific queries I can run to gather all that information efficiently. Let’s see what I can find!" } ] } ], "tool_calls": [ { "id": "call_oG6DiojpOU3kiq0T2pVa9Fac", "call_id": "call_oG6DiojpOU3kiq0T2pVa9Fac", "response_item_id": "fc_0e150df8343ebf8f016a08c6de2de481919625ccb5b6bf9a26", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"python3 - <<'PY'\\nimport sqlite3, json, pathlib\\nfor db in ['/home/agent/jarvis_runtime/finance-system/data/finance.sqlite3','/home/agent/jarvis_runtime/finance-system/uat-vue-dashboard/data/finance.sqlite3']:\\n p=pathlib.Path(db)\\n print('DB', db, 'exists', p.exists(), 'size', p.stat().st_size if p.exists() else None)\\n con=sqlite3.connect(f'file:{db}?mode=ro', uri=True)\\n cur=con.cursor()\\n tables=cur.execute(\\\"select name,type from sqlite_master where type in ('table','view') and name not like 'sqlite_%' order by name\\\").fetchall()\\n for name, typ in tables:\\n cols=cur.execute(f\\\"pragma table_info({name!r})\\\").fetchall()\\n print(typ.upper(), name, 'COLUMNS', ', '.join([c[1]+':' + c[2] for c in cols]))\\n con.close()\\nPY\", \"workdir\":\"/home/agent\", \"timeout\":60}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"DB /home/agent/jarvis_runtime/finance-system/data/finance.sqlite3 exists True size 1040384\\nTABLE accounts COLUMNS account_id:TEXT, platform_id:TEXT, account_name:TEXT, account_type:TEXT, currency:TEXT, performance_included:INTEGER, is_health_reserve:INTEGER, target_cash_min_chf:NUMERIC, target_cash_max_chf:NUMERIC, is_active:INTEGER, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE alerts COLUMNS alert_id:TEXT, priority:TEXT, category:TEXT, entity_type:TEXT, entity_id:TEXT, rule_id:TEXT, message:TEXT, evidence_json:TEXT, status:TEXT, created_at:TEXT, resolved_at:TEXT, muted_until:TEXT, last_seen_at:TEXT, occurrence_count:INTEGER, fingerprint:TEXT, dedup_key:TEXT\\nTABLE audit_log COLUMNS audit_id:TEXT, timestamp:TEXT, source:TEXT, action:TEXT, entity_type:TEXT, entity_id:TEXT, old_values_json:TEXT, new_values_json:TEXT, user_text_note:TEXT, original_input_text:TEXT, confirmed:INTEGER, confirmation_timestamp:TEXT, auto_parsed:INTEGER, parse_confidence:NUMERIC, created_by:TEXT, quality_status:TEXT, created_at:TEXT\\nTABLE broker_import_dry_runs COLUMNS dry_run_id:TEXT, source_name:TEXT, source_platform:TEXT, source_file_label:TEXT, source_file_type:TEXT, source_hash:TEXT, source_filename_hash:TEXT, detected_snapshot_date:TEXT, snapshot_date_status:TEXT, detected_sections_json:TEXT, field_coverage_json:TEXT, rows_total:INTEGER, rows_position_candidates:INTEGER, rows_cash_candidates:INTEGER, candidate_positions:INTEGER, candidate_cash_rows:INTEGER, mapped_positions:INTEGER, blocked_positions:INTEGER, warnings_count:INTEGER, errors_count:INTEGER, quality_flags_json:TEXT, summary_json:TEXT, created_at:TEXT, notes:TEXT, session_status:TEXT, is_current:INTEGER, archived_at:TEXT, discarded_at:TEXT\\nTABLE broker_import_execution_plans COLUMNS execution_plan_id:TEXT, dry_run_id:TEXT, review_item_id:TEXT, source_platform:TEXT, target_account_id:TEXT, target_instrument_id:TEXT, transaction_type:TEXT, snapshot_date:TEXT, payload_status:TEXT, payload_quality_flags_json:TEXT, source_row_hash:TEXT, planned_write_summary_json:TEXT, execution_status:TEXT, transaction_id:TEXT, created_at:TEXT, updated_at:TEXT, executed_at:TEXT, notes:TEXT\\nTABLE broker_import_review_items COLUMNS review_item_id:TEXT, dry_run_id:TEXT, source_platform:TEXT, source_file_type:TEXT, source_row_ref:TEXT, row_hash:TEXT, source_label:TEXT, normalized_name:TEXT, detected_asset_class:TEXT, detected_currency:TEXT, detected_quantity_present:INTEGER, detected_market_value_present:INTEGER, isin:TEXT, ticker:TEXT, exchange:TEXT, mapped_instrument_id:TEXT, mapped_account_id:TEXT, quality_flags_json:TEXT, review_status:TEXT, reviewer_note:TEXT, created_at:TEXT, updated_at:TEXT, import_readiness_status:TEXT, reviewer_confirmed:INTEGER, snapshot_date_confirmed:INTEGER, ticker_exchange_confirmed:INTEGER, account_mapping_status:TEXT\\nTABLE cash_balances COLUMNS cash_balance_id:TEXT, account_id:TEXT, balance_date:TEXT, currency:TEXT, amount_original:NUMERIC, fx_rate_to_chf:NUMERIC, amount_chf:NUMERIC, source_type:TEXT, quality_status:TEXT, notes:TEXT, created_at:TEXT\\nTABLE crypto_assets COLUMNS asset_id:TEXT, coin_name:TEXT, symbol:TEXT, coingecko_id:TEXT, network_chain_default:TEXT, is_stablecoin:INTEGER, price_provider_primary:TEXT, price_provider_fallback:TEXT, is_active:INTEGER, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE crypto_holdings COLUMNS crypto_holding_id:TEXT, asset_id:TEXT, wallet_id:TEXT, quantity:TEXT, acquisition_source:TEXT, last_verified_at:TEXT, verification_status:TEXT, legacy_snapshot_value_original:TEXT, legacy_snapshot_value_chf:TEXT, legacy_snapshot_currency:TEXT, legacy_snapshot_date:TEXT, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE crypto_prices COLUMNS crypto_price_id:TEXT, asset_id:TEXT, coingecko_id:TEXT, price_currency:TEXT, price:TEXT, provider:TEXT, provider_timestamp:TEXT, fetched_at:TEXT, quality_status:TEXT, error_message:TEXT\\nTABLE crypto_transactions COLUMNS crypto_transaction_id:TEXT, transaction_id:TEXT, transaction_type:TEXT, asset_id:TEXT, quantity:TEXT, price_original:TEXT, currency_original:TEXT, gross_amount_original:TEXT, fee_quantity:TEXT, fee_original:TEXT, fee_currency:TEXT, fx_rate_to_chf:TEXT, fx_source:TEXT, amount_chf:TEXT, from_wallet_id:TEXT, to_wallet_id:TEXT, transaction_datetime:TEXT, tx_hash:TEXT, source:TEXT, confirmation_status:TEXT, parse_confidence:NUMERIC, original_input_text:TEXT, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE crypto_wallets COLUMNS wallet_id:TEXT, wallet_name:TEXT, wallet_type:TEXT, platform_provider:TEXT, network_chain:TEXT, wallet_address:TEXT, owner:TEXT, is_active:INTEGER, last_verified_at:TEXT, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE decision_journal COLUMNS decision_id:TEXT, decision_date:TEXT, decision_type:TEXT, entity_type:TEXT, entity_id:TEXT, system_recommendation:TEXT, human_decision:TEXT, rationale:TEXT, investment_case:TEXT, risks:TEXT, exit_rule:TEXT, alternatives_considered:TEXT, sources:TEXT, review_date:TEXT, outcome_status:TEXT, outcome_return_chf:NUMERIC, created_at:TEXT, updated_at:TEXT\\nTABLE fx_rates COLUMNS fx_rate_id:TEXT, base_currency:TEXT, quote_currency:TEXT, rate_date:TEXT, rate_timestamp:TEXT, rate:TEXT, provider:TEXT, rate_type:TEXT, quality_status:TEXT, created_at:TEXT, error_status:TEXT, error_message:TEXT\\nTABLE import_sessions COLUMNS import_session_id:TEXT, import_type:TEXT, source_filename:TEXT, source_hash:TEXT, started_at:TEXT, finished_at:TEXT, status:TEXT, rows_total:INTEGER, rows_imported:INTEGER, rows_failed:INTEGER, errors_json:TEXT, notes:TEXT\\nTABLE instrument_catalog_entries COLUMNS catalog_entry_id:TEXT, asset_class:TEXT, name:TEXT, normalized_name:TEXT, isin:TEXT, ticker:TEXT, exchange:TEXT, trading_currency:TEXT, instrument_currency:TEXT, provider:TEXT, provider_symbol:TEXT, provider_market:TEXT, country:TEXT, sector:TEXT, issuer:TEXT, fund_type:TEXT, is_currency_hedged:INTEGER, hedged_to_currency:TEXT, hedge_status:TEXT, instrument_status:TEXT, valuation_policy:TEXT, source:TEXT, source_confidence:TEXT, last_verified_at:TEXT, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE instrument_import_candidates COLUMNS candidate_id:TEXT, source_file:TEXT, platform:TEXT, account:TEXT, source_row_number:TEXT, raw_name:TEXT, raw_ticker:TEXT, raw_isin:TEXT, raw_currency:TEXT, raw_quantity:TEXT, raw_asset_class:TEXT, extracted_by:TEXT, extraction_confidence:TEXT, proposed_name:TEXT, proposed_ticker:TEXT, proposed_isin:TEXT, proposed_exchange:TEXT, proposed_currency:TEXT, proposed_asset_class:TEXT, provider:TEXT, provider_symbol:TEXT, mapping_status:TEXT, review_note:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE instrument_mappings COLUMNS mapping_id:TEXT, source_name:TEXT, source_platform:TEXT, source_account:TEXT, source_label:TEXT, normalized_name:TEXT, isin:TEXT, ticker:TEXT, exchange:TEXT, currency:TEXT, asset_class:TEXT, source_instrument_name:TEXT, source_isin:TEXT, source_ticker:TEXT, source_exchange:TEXT, source_currency:TEXT, instrument_id:TEXT, mapping_status:TEXT, confidence:TEXT, quality_flags_json:TEXT, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE instrument_price_mapping_candidates COLUMNS candidate_id:TEXT, instrument_id:TEXT, isin:TEXT, candidate_provider:TEXT, candidate_provider_symbol:TEXT, candidate_exchange:TEXT, candidate_currency:TEXT, candidate_name:TEXT, candidate_is_hedged:INTEGER, candidate_hedged_to_currency:TEXT, candidate_instrument_status:TEXT, confidence:TEXT, evidence_source:TEXT, evidence_note:TEXT, review_status:TEXT, created_at:TEXT, updated_at:TEXT, candidate_asset_class:TEXT, candidate_hedge_status:TEXT, candidate_valuation_policy:TEXT, ranking_score:INTEGER, ranking_reason:TEXT, risk_flags:TEXT, recommended_action:TEXT\\nTABLE instrument_price_mappings COLUMNS mapping_id:TEXT, instrument_id:TEXT, isin:TEXT, ticker:TEXT, exchange:TEXT, currency:TEXT, provider:TEXT, provider_symbol:TEXT, provider_market:TEXT, mapping_status:TEXT, confidence:TEXT, notes:TEXT, created_at:TEXT, updated_at:TEXT, hedge_status:TEXT, is_currency_hedged:INTEGER, hedged_to_currency:TEXT, instrument_status:TEXT, valuation_policy:TEXT, trading_currency:TEXT, base_exposure_currency:TEXT\\nTABLE instruments COLUMNS instrument_id:TEXT, asset_class:TEXT, name:TEXT, ticker:TEXT, isin:TEXT, exchange:TEXT, currency:TEXT, country:TEXT, sector:TEXT, industry:TEXT, provider_symbol:TEXT, data_provider_primary:TEXT, data_provider_fallback:TEXT, is_active:INTEGER, notes:TEXT, created_at:TEXT, updated_at:TEXT, position_category:TEXT, ter:TEXT, distribution_policy:TEXT, index_name:TEXT, fund_domicile:TEXT, benchmark:TEXT, is_currency_hedged:INTEGER, hedged_to_currency:TEXT, hedge_status:TEXT, base_exposure_currency:TEXT, trading_currency:TEXT, instrument_status:TEXT, valuation_policy:TEXT, corporate_action_status:TEXT, split_or_corporate_action_review_required:INTEGER\\nTABLE market_prices COLUMNS market_price_id:TEXT, instrument_id:TEXT, price_date:TEXT, price_timestamp:TEXT, open:TEXT, high:TEXT, low:TEXT, close:TEXT, adjusted_close:TEXT, currency:TEXT, provider:TEXT, provider_symbol:TEXT, quality_status:TEXT, created_at:TEXT, provider_market:TEXT, error_message:TEXT, corporate_action_status:TEXT\\nTABLE platform_account_mappings COLUMNS mapping_id:TEXT, source_name:TEXT, source_platform:TEXT, source_platform_label:TEXT, source_account_label:TEXT, normalized_platform:TEXT, normalized_account_name:TEXT, source_account_type:TEXT, account_type:TEXT, source_currency:TEXT, currency:TEXT, platform_id:TEXT, account_id:TEXT, internal_platform_id:TEXT, internal_account_id:TEXT, mapping_status:TEXT, quality_flags_json:TEXT, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE platforms COLUMNS platform_id:TEXT, name:TEXT, platform_type:TEXT, country:TEXT, default_currency:TEXT, is_active:INTEGER, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE positions_snapshot COLUMNS position_snapshot_id:TEXT, snapshot_date:TEXT, account_id:TEXT, platform_id:TEXT, instrument_id:TEXT, quantity:NUMERIC, average_cost_original:NUMERIC, cost_basis_original:NUMERIC, cost_basis_chf:NUMERIC, market_price_original:NUMERIC, market_value_original:NUMERIC, market_fx_rate_to_chf:NUMERIC, market_value_chf:NUMERIC, unrealized_price_pnl_chf:NUMERIC, unrealized_fx_pnl_chf:NUMERIC, realized_pnl_chf:NUMERIC, income_chf:NUMERIC, fees_chf:NUMERIC, taxes_chf:NUMERIC, total_return_chf:NUMERIC, portfolio_weight_pct:NUMERIC, category:TEXT, data_quality_status:TEXT, created_at:TEXT\\nTABLE reports COLUMNS report_id:TEXT, report_type:TEXT, title:TEXT, period_start:TEXT, period_end:TEXT, generated_at:TEXT, file_path:TEXT, format:TEXT, data_quality_status:TEXT, summary_json:TEXT, created_at:TEXT\\nTABLE schema_migrations COLUMNS version:INTEGER, name:TEXT, applied_at:TEXT, checksum:TEXT\\nTABLE transactions COLUMNS transaction_id:TEXT, transaction_type:TEXT, account_id:TEXT, instrument_id:TEXT, trade_date:TEXT, settlement_date:TEXT, quantity:TEXT, price_original:TEXT, gross_amount_original:TEXT, fee_original:TEXT, tax_original:TEXT, net_amount_original:TEXT, currency_original:TEXT, fx_rate_to_chf:TEXT, fx_source:TEXT, fx_status:TEXT, gross_amount_chf:TEXT, fee_chf:TEXT, tax_chf:TEXT, net_amount_chf:TEXT, source_type:TEXT, source_id:TEXT, external_transaction_id:TEXT, row_hash:TEXT, is_confirmed:INTEGER, quality_status:TEXT, notes:TEXT, created_at:TEXT, updated_at:TEXT, is_voided:INTEGER, voided_at:TEXT, void_reason:TEXT, voided_by:TEXT, correction_of_transaction_id:TEXT, correction_reason:TEXT\\nTABLE watchlist COLUMNS watchlist_id:TEXT, instrument_id:TEXT, crypto_asset_id:TEXT, name:TEXT, asset_class:TEXT, reason:TEXT, target_entry_price:NUMERIC, target_entry_currency:TEXT, desired_position_size_chf:NUMERIC, desired_weight_pct:NUMERIC, trigger_rules:TEXT, risk_notes:TEXT, investment_case:TEXT, bear_case:TEXT, sources:TEXT, status:TEXT, next_review_date:TEXT, created_at:TEXT, updated_at:TEXT\\nDB /home/agent/jarvis_runtime/finance-system/uat-vue-dashboard/data/finance.sqlite3 exists True size 1073152\\nTABLE accounts COLUMNS account_id:TEXT, platform_id:TEXT, account_name:TEXT, account_type:TEXT, currency:TEXT, performance_included:INTEGER, is_health_reserve:INTEGER, target_cash_min_chf:NUMERIC, target_cash_max_chf:NUMERIC, is_active:INTEGER, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE alerts COLUMNS alert_id:TEXT, priority:TEXT, category:TEXT, entity_type:TEXT, entity_id:TEXT, rule_id:TEXT, message:TEXT, evidence_json:TEXT, status:TEXT, created_at:TEXT, resolved_at:TEXT, muted_until:TEXT, last_seen_at:TEXT, occurrence_count:INTEGER, fingerprint:TEXT, dedup_key:TEXT\\nTABLE audit_log COLUMNS audit_id:TEXT, timestamp:TEXT, source:TEXT, action:TEXT, entity_type:TEXT, entity_id:TEXT, old_values_json:TEXT, new_values_json:TEXT, user_text_note:TEXT, original_input_text:TEXT, confirmed:INTEGER, confirmation_timestamp:TEXT, auto_parsed:INTEGER, parse_confidence:NUMERIC, created_by:TEXT, quality_status:TEXT, created_at:TEXT\\nTABLE broker_import_dry_runs COLUMNS dry_run_id:TEXT, source_name:TEXT, source_platform:TEXT, source_file_label:TEXT, source_file_type:TEXT, source_hash:TEXT, source_filename_hash:TEXT, detected_snapshot_date:TEXT, snapshot_date_status:TEXT, detected_sections_json:TEXT, field_coverage_json:TEXT, rows_total:INTEGER, rows_position_candidates:INTEGER, rows_cash_candidates:INTEGER, candidate_positions:INTEGER, candidate_cash_rows:INTEGER, mapped_positions:INTEGER, blocked_positions:INTEGER, warnings_count:INTEGER, errors_count:INTEGER, quality_flags_json:TEXT, summary_json:TEXT, created_at:TEXT, notes:TEXT, session_status:TEXT, is_current:INTEGER, archived_at:TEXT, discarded_at:TEXT\\nTABLE broker_import_execution_plans COLUMNS execution_plan_id:TEXT, dry_run_id:TEXT, review_item_id:TEXT, source_platform:TEXT, target_account_id:TEXT, target_instrument_id:TEXT, transaction_type:TEXT, snapshot_date:TEXT, payload_status:TEXT, payload_quality_flags_json:TEXT, source_row_hash:TEXT, planned_write_summary_json:TEXT, execution_status:TEXT, transaction_id:TEXT, created_at:TEXT, updated_at:TEXT, executed_at:TEXT, notes:TEXT\\nTABLE broker_import_review_items COLUMNS review_item_id:TEXT, dry_run_id:TEXT, source_platform:TEXT, source_file_type:TEXT, source_row_ref:TEXT, row_hash:TEXT, source_label:TEXT, normalized_name:TEXT, detected_asset_class:TEXT, detected_currency:TEXT, detected_quantity_present:INTEGER, detected_market_value_present:INTEGER, isin:TEXT, ticker:TEXT, exchange:TEXT, mapped_instrument_id:TEXT, mapped_account_id:TEXT, quality_flags_json:TEXT, review_status:TEXT, reviewer_note:TEXT, created_at:TEXT, updated_at:TEXT, import_readiness_status:TEXT, reviewer_confirmed:INTEGER, snapshot_date_confirmed:INTEGER, ticker_exchange_confirmed:INTEGER, account_mapping_status:TEXT\\nTABLE cash_balances COLUMNS cash_balance_id:TEXT, account_id:TEXT, balance_date:TEXT, currency:TEXT, amount_original:NUMERIC, fx_rate_to_chf:NUMERIC, amount_chf:NUMERIC, source_type:TEXT, quality_status:TEXT, notes:TEXT, created_at:TEXT\\nTABLE crypto_assets COLUMNS asset_id:TEXT, coin_name:TEXT, symbol:TEXT, coingecko_id:TEXT, network_chain_default:TEXT, is_stablecoin:INTEGER, price_provider_primary:TEXT, price_provider_fallback:TEXT, is_active:INTEGER, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE crypto_holdings COLUMNS crypto_holding_id:TEXT, asset_id:TEXT, wallet_id:TEXT, quantity:TEXT, acquisition_source:TEXT, last_verified_at:TEXT, verification_status:TEXT, legacy_snapshot_value_original:TEXT, legacy_snapshot_value_chf:TEXT, legacy_snapshot_currency:TEXT, legacy_snapshot_date:TEXT, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE crypto_prices COLUMNS crypto_price_id:TEXT, asset_id:TEXT, coingecko_id:TEXT, price_currency:TEXT, price:TEXT, provider:TEXT, provider_timestamp:TEXT, fetched_at:TEXT, quality_status:TEXT, error_message:TEXT\\nTABLE crypto_transactions COLUMNS crypto_transaction_id:TEXT, transaction_id:TEXT, transaction_type:TEXT, asset_id:TEXT, quantity:TEXT, price_original:TEXT, currency_original:TEXT, gross_amount_original:TEXT, fee_quantity:TEXT, fee_original:TEXT, fee_currency:TEXT, fx_rate_to_chf:TEXT, fx_source:TEXT, amount_chf:TEXT, from_wallet_id:TEXT, to_wallet_id:TEXT, transaction_datetime:TEXT, tx_hash:TEXT, source:TEXT, confirmation_status:TEXT, parse_confidence:NUMERIC, original_input_text:TEXT, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE crypto_wallets COLUMNS wallet_id:TEXT, wallet_name:TEXT, wallet_type:TEXT, platform_provider:TEXT, network_chain:TEXT, wallet_address:TEXT, owner:TEXT, is_active:INTEGER, last_verified_at:TEXT, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE decision_journal COLUMNS decision_id:TEXT, decision_date:TEXT, decision_type:TEXT, entity_type:TEXT, entity_id:TEXT, system_recommendation:TEXT, human_decision:TEXT, rationale:TEXT, investment_case:TEXT, risks:TEXT, exit_rule:TEXT, alternatives_considered:TEXT, sources:TEXT, review_date:TEXT, outcome_status:TEXT, outcome_return_chf:NUMERIC, created_at:TEXT, updated_at:TEXT\\nTABLE fx_rates COLUMNS fx_rate_id:TEXT, base_currency:TEXT, quote_currency:TEXT, rate_date:TEXT, rate_timestamp:TEXT, rate:TEXT, provider:TEXT, rate_type:TEXT, quality_status:TEXT, created_at:TEXT, error_status:TEXT, error_message:TEXT\\nTABLE import_sessions COLUMNS import_session_id:TEXT, import_type:TEXT, source_filename:TEXT, source_hash:TEXT, started_at:TEXT, finished_at:TEXT, status:TEXT, rows_total:INTEGER, rows_imported:INTEGER, rows_failed:INTEGER, errors_json:TEXT, notes:TEXT\\nTABLE instrument_catalog_entries COLUMNS catalog_entry_id:TEXT, asset_class:TEXT, name:TEXT, normalized_name:TEXT, isin:TEXT, ticker:TEXT, exchange:TEXT, trading_currency:TEXT, instrument_currency:TEXT, provider:TEXT, provider_symbol:TEXT, provider_market:TEXT, country:TEXT, sector:TEXT, issuer:TEXT, fund_type:TEXT, is_currency_hedged:INTEGER, hedged_to_currency:TEXT, hedge_status:TEXT, instrument_status:TEXT, valuation_policy:TEXT, source:TEXT, source_confidence:TEXT, last_verified_at:TEXT, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE instrument_import_candidates COLUMNS candidate_id:TEXT, source_file:TEXT, platform:TEXT, account:TEXT, source_row_number:TEXT, raw_name:TEXT, raw_ticker:TEXT, raw_isin:TEXT, raw_currency:TEXT, raw_quantity:TEXT, raw_asset_class:TEXT, extracted_by:TEXT, extraction_confidence:TEXT, proposed_name:TEXT, proposed_ticker:TEXT, proposed_isin:TEXT, proposed_exchange:TEXT, proposed_currency:TEXT, proposed_asset_class:TEXT, provider:TEXT, provider_symbol:TEXT, mapping_status:TEXT, review_note:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE instrument_mappings COLUMNS mapping_id:TEXT, source_name:TEXT, source_platform:TEXT, source_account:TEXT, source_label:TEXT, normalized_name:TEXT, isin:TEXT, ticker:TEXT, exchange:TEXT, currency:TEXT, asset_class:TEXT, source_instrument_name:TEXT, source_isin:TEXT, source_ticker:TEXT, source_exchange:TEXT, source_currency:TEXT, instrument_id:TEXT, mapping_status:TEXT, confidence:TEXT, quality_flags_json:TEXT, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE instrument_price_mapping_candidates COLUMNS candidate_id:TEXT, instrument_id:TEXT, isin:TEXT, candidate_provider:TEXT, candidate_provider_symbol:TEXT, candidate_exchange:TEXT, candidate_currency:TEXT, candidate_name:TEXT, candidate_is_hedged:INTEGER, candidate_hedged_to_currency:TEXT, candidate_instrument_status:TEXT, confidence:TEXT, evidence_source:TEXT, evidence_note:TEXT, review_status:TEXT, created_at:TEXT, updated_at:TEXT, candidate_asset_class:TEXT, candidate_hedge_status:TEXT, candidate_valuation_policy:TEXT, ranking_score:INTEGER, ranking_reason:TEXT, risk_flags:TEXT, recommended_action:TEXT\\nTABLE instrument_price_mappings COLUMNS mapping_id:TEXT, instrument_id:TEXT, isin:TEXT, ticker:TEXT, exchange:TEXT, currency:TEXT, provider:TEXT, provider_symbol:TEXT, provider_market:TEXT, mapping_status:TEXT, confidence:TEXT, notes:TEXT, created_at:TEXT, updated_at:TEXT, hedge_status:TEXT, is_currency_hedged:INTEGER, hedged_to_currency:TEXT, instrument_status:TEXT, valuation_policy:TEXT, trading_currency:TEXT, base_exposure_currency:TEXT\\nTABLE instruments COLUMNS instrument_id:TEXT, asset_class:TEXT, name:TEXT, ticker:TEXT, isin:TEXT, exchange:TEXT, currency:TEXT, country:TEXT, sector:TEXT, industry:TEXT, provider_symbol:TEXT, data_provider_primary:TEXT, data_provider_fallback:TEXT, is_active:INTEGER, notes:TEXT, created_at:TEXT, updated_at:TEXT, position_category:TEXT, ter:TEXT, distribution_policy:TEXT, index_name:TEXT, fund_domicile:TEXT, benchmark:TEXT, is_currency_hedged:INTEGER, hedged_to_currency:TEXT, hedge_status:TEXT, base_exposure_currency:TEXT, trading_currency:TEXT, instrument_status:TEXT, valuation_policy:TEXT, corporate_action_status:TEXT, split_or_corporate_action_review_required:INTEGER\\nTABLE market_prices COLUMNS market_price_id:TEXT, instrument_id:TEXT, price_date:TEXT, price_timestamp:TEXT, open:TEXT, high:TEXT, low:TEXT, close:TEXT, adjusted_close:TEXT, currency:TEXT, provider:TEXT, provider_symbol:TEXT, quality_status:TEXT, created_at:TEXT, provider_market:TEXT, error_message:TEXT, corporate_action_status:TEXT\\nTABLE platform_account_mappings COLUMNS mapping_id:TEXT, source_name:TEXT, source_platform:TEXT, source_platform_label:TEXT, source_account_label:TEXT, normalized_platform:TEXT, normalized_account_name:TEXT, source_account_type:TEXT, account_type:TEXT, source_currency:TEXT, currency:TEXT, platform_id:TEXT, account_id:TEXT, internal_platform_id:TEXT, internal_account_id:TEXT, mapping_status:TEXT, quality_flags_json:TEXT, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE platforms COLUMNS platform_id:TEXT, name:TEXT, platform_type:TEXT, country:TEXT, default_currency:TEXT, is_active:INTEGER, notes:TEXT, created_at:TEXT, updated_at:TEXT\\nTABLE positions_snapshot COLUMNS position_snapshot_id:TEXT, snapshot_date:TEXT, account_id:TEXT, platform_id:TEXT, instrument_id:TEXT, quantity:NUMERIC, average_cost_original:NUMERIC, cost_basis_original:NUMERIC, cost_basis_chf:NUMERIC, market_price_original:NUMERIC, market_value_original:NUMERIC, market_fx_rate_to_chf:NUMERIC, market_value_chf:NUMERIC, unrealized_price_pnl_chf:NUMERIC, unrealized_fx_pnl_chf:NUMERIC, realized_pnl_chf:NUMERIC, income_chf:NUMERIC, fees_chf:NUMERIC, taxes_chf:NUMERIC, total_return_chf:NUMERIC, portfolio_weight_pct:NUMERIC, category:TEXT, data_quality_status:TEXT, created_at:TEXT\\nTABLE reports COLUMNS report_id:TEXT, report_type:TEXT, title:TEXT, period_start:TEXT, period_end:TEXT, generated_at:TEXT, file_path:TEXT, format:TEXT, data_quality_status:TEXT, summary_json:TEXT, created_at:TEXT\\nTABLE schema_migrations COLUMNS version:INTEGER, name:TEXT, applied_at:TEXT, checksum:TEXT\\nTABLE transactions COLUMNS transaction_id:TEXT, transaction_type:TEXT, account_id:TEXT, instrument_id:TEXT, trade_date:TEXT, settlement_date:TEXT, quantity:TEXT, price_original:TEXT, gross_amount_original:TEXT, fee_original:TEXT, tax_original:TEXT, net_amount_original:TEXT, currency_original:TEXT, fx_rate_to_chf:TEXT, fx_source:TEXT, fx_status:TEXT, gross_amount_chf:TEXT, fee_chf:TEXT, tax_chf:TEXT, net_amount_chf:TEXT, source_type:TEXT, source_id:TEXT, external_transaction_id:TEXT, row_hash:TEXT, is_confirmed:INTEGER, quality_status:TEXT, notes:TEXT, created_at:TEXT, updated_at:TEXT, is_voided:INTEGER, voided_at:TEXT, void_reason:TEXT, voided_by:TEXT, correction_of_transaction_id:TEXT, correction_reason:TEXT\\nTABLE watchlist COLUMNS watchlist_id:TEXT, instrument_id:TEXT, crypto_asset_id:TEXT, name:TEXT, asset_class:TEXT, reason:TEXT, target_entry_price:NUMERIC, target_entry_currency:TEXT, desired_position_size_chf:NUMERIC, desired_weight_pct:NUMERIC, 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"id": "rs_0b13374bcd43d06e016a08c6e8d33c8191955ec6dae9288813", "summary": [] } ], "tool_calls": [ { "id": "call_qcH9A95P6mmmK40BaItPpzPh", "call_id": "call_qcH9A95P6mmmK40BaItPpzPh", "response_item_id": "fc_0b13374bcd43d06e016a08c6ed1ee881919f5ddad30940fd91", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"python3 - <<'PY'\\nimport sqlite3, pathlib, re\\nDB='/home/agent/jarvis_runtime/finance-system/data/finance.sqlite3'\\npatterns=[\\n ('TRUE_WEALTH_REVIEW_BROKERAGE', \\\"%true wealth review brokerage%\\\"),\\n ('REVIEW_BROKERAGE', \\\"%review brokerage%\\\"),\\n ('TEST', \\\"%test%\\\"),\\n ('REVIEW', \\\"%review%\\\"),\\n]\\nexclude_tables=set(['crypto_assets','crypto_holdings','crypto_prices','crypto_transactions','crypto_wallets'])\\ncon=sqlite3.connect(f'file:{DB}?mode=ro', uri=True)\\ncur=con.cursor()\\ntables=[r[0] for r in cur.execute(\\\"select name from sqlite_master where type='table' and name not like 'sqlite_%' order by name\\\")]\\nprint('DB', DB)\\nprint('TEXT_MATCH_COUNTS')\\nfor t in tables:\\n if t in exclude_tables: continue\\n cols=cur.execute(f\\\"pragma table_info({t})\\\").fetchall()\\n textcols=[c[1] for c in cols if ('TEXT' in (c[2] or '').upper() or not c[2])]\\n pk=cols[0][1] if cols else 'rowid'\\n any_table=False\\n rows=[]\\n for pname, pat in patterns:\\n ors=[]; params=[]\\n for c in textcols:\\n ors.append(f\\\"lower(coalesce(\\\\\\\"{c}\\\\\\\",'')) like ?\\\")\\n params.append(pat)\\n if not ors: continue\\n sql=f\\\"select count(*) from {t} where \\\" + ' or '.join(ors)\\n cnt=cur.execute(sql, params).fetchone()[0]\\n if cnt:\\n # per-column counts\\n col_hits=[]\\n for c in textcols:\\n cc=cur.execute(f\\\"select count(*) from {t} where lower(coalesce(\\\\\\\"{c}\\\\\\\",'')) like ?\\\", (pat,)).fetchone()[0]\\n if cc: col_hits.append(c)\\n rows.append((pname,cnt,col_hits))\\n if rows:\\n print('TABLE', t)\\n for pname,cnt,col_hits in rows:\\n print(' ', pname, 'rows=', cnt, 'columns=', ','.join(col_hits))\\nprint('\\\\nFKS')\\nfor t in tables:\\n if t in exclude_tables: continue\\n fks=cur.execute(f\\\"pragma foreign_key_list({t})\\\").fetchall()\\n if fks:\\n print(t, fks)\\ncon.close()\\nPY\",\"timeout\":60,\"workdir\":\"/home/agent\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"DB /home/agent/jarvis_runtime/finance-system/data/finance.sqlite3\\nTEXT_MATCH_COUNTS\\nTABLE accounts\\n TRUE_WEALTH_REVIEW_BROKERAGE rows= 1 columns= account_name\\n REVIEW_BROKERAGE rows= 1 columns= account_name\\n REVIEW rows= 1 columns= account_id,account_name,notes\\nTABLE alerts\\n REVIEW rows= 69 columns= rule_id,message,evidence_json\\nTABLE audit_log\\n TEST rows= 24 columns= action,entity_id,user_text_note\\n REVIEW rows= 61 columns= source,action,entity_type,entity_id,old_values_json,new_values_json,user_text_note\\nTABLE broker_import_dry_runs\\n REVIEW rows= 3 columns= quality_flags_json\\nTABLE broker_import_execution_plans\\n REVIEW rows= 3 columns= target_account_id,planned_write_summary_json,notes\\nTABLE broker_import_review_items\\n REVIEW rows= 59 columns= mapped_account_id,quality_flags_json,reviewer_note,import_readiness_status\\nTABLE instrument_catalog_entries\\n REVIEW rows= 3 columns= source\\nTABLE instrument_import_candidates\\n REVIEW rows= 23 columns= mapping_status,review_note\\nTABLE instrument_price_mapping_candidates\\n REVIEW rows= 57 columns= evidence_note,recommended_action\\nTABLE instrument_price_mappings\\n REVIEW rows= 3 columns= notes\\nTABLE instruments\\n REVIEW rows= 3 columns= notes\\nTABLE platforms\\n REVIEW rows= 1 columns= notes\\nTABLE schema_migrations\\n REVIEW rows= 3 columns= name\\nTABLE transactions\\n REVIEW rows= 3 columns= account_id\\n\\nFKS\\naccounts [(0, 0, 'platforms', 'platform_id', 'platform_id', 'NO ACTION', 'NO ACTION', 'NONE')]\\nbroker_import_execution_plans [(0, 0, 'transactions', 'transaction_id', 'transaction_id', 'NO ACTION', 'NO ACTION', 'NONE'), (1, 0, 'instruments', 'target_instrument_id', 'instrument_id', 'NO ACTION', 'NO ACTION', 'NONE'), (2, 0, 'accounts', 'target_account_id', 'account_id', 'NO ACTION', 'NO ACTION', 'NONE'), (3, 0, 'broker_import_review_items', 'review_item_id', 'review_item_id', 'NO ACTION', 'NO ACTION', 'NONE'), (4, 0, 'broker_import_dry_runs', 'dry_run_id', 'dry_run_id', 'NO ACTION', 'NO ACTION', 'NONE')]\\nbroker_import_review_items [(0, 0, 'accounts', 'mapped_account_id', 'account_id', 'NO ACTION', 'NO ACTION', 'NONE'), (1, 0, 'instruments', 'mapped_instrument_id', 'instrument_id', 'NO ACTION', 'NO ACTION', 'NONE'), (2, 0, 'broker_import_dry_runs', 'dry_run_id', 'dry_run_id', 'NO ACTION', 'NO ACTION', 'NONE')]\\ncash_balances [(0, 0, 'accounts', 'account_id', 'account_id', 'NO ACTION', 'NO ACTION', 'NONE')]\\ninstrument_mappings [(0, 0, 'instruments', 'instrument_id', 'instrument_id', 'NO ACTION', 'NO ACTION', 'NONE')]\\ninstrument_price_mapping_candidates [(0, 0, 'instruments', 'instrument_id', 'instrument_id', 'NO ACTION', 'NO ACTION', 'NONE')]\\ninstrument_price_mappings [(0, 0, 'instruments', 'instrument_id', 'instrument_id', 'NO ACTION', 'NO ACTION', 'NONE')]\\nplatform_account_mappings [(0, 0, 'accounts', 'internal_account_id', 'account_id', 'NO ACTION', 'NO ACTION', 'NONE'), (1, 0, 'platforms', 'internal_platform_id', 'platform_id', 'NO ACTION', 'NO ACTION', 'NONE'), (2, 0, 'accounts', 'account_id', 'account_id', 'NO ACTION', 'NO ACTION', 'NONE'), (3, 0, 'platforms', 'platform_id', 'platform_id', 'NO ACTION', 'NO ACTION', 'NONE')]\\npositions_snapshot [(0, 0, 'instruments', 'instrument_id', 'instrument_id', 'NO ACTION', 'NO ACTION', 'NONE'), (1, 0, 'platforms', 'platform_id', 'platform_id', 'NO ACTION', 'NO ACTION', 'NONE'), (2, 0, 'accounts', 'account_id', 'account_id', 'NO ACTION', 'NO ACTION', 'NONE')]\\ntransactions [(0, 0, 'transactions', 'correction_of_transaction_id', 'transaction_id', 'NO ACTION', 'NO ACTION', 'NONE')]\\nwatchlist [(0, 0, 'crypto_assets', 'crypto_asset_id', 'asset_id', 'NO ACTION', 'NO ACTION', 'NONE'), (1, 0, 'instruments', 'instrument_id', 'instrument_id', 'NO ACTION', 'NO ACTION', 'NONE')]\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_qcH9A95P6mmmK40BaItPpzPh" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqCMb8SmvenYKYTFQuqAoHDktcUcTWZmG4eR89u8YzercNNUyolguV6lcJpt1367QKWrJrrmL_dZjLbPNgzhrsZezZkzy4sdQZpbOhYo0aQBZEtYxbjx8FIefM0IrosTC2MkCr5cS6QJrKXTsS2EI5OSVusGj-uOCWnU13SDAG429R7E-av93l3cFT4YFDT_TlignTHwKpMUf51jV8KAqQq-NeB8iBN-oLHiaVjRBQSSc5zUyJBCHJIibYF54m0qGUQL84dGbmJYbtQ1wTc3X-co8FW_xJ1EUGnvYi3ZeCF7xPe_srgEZWaMZw1MpN3HaUMhle-3cFVKELje-WM6P_PL4dUjxIJnMBQh_CctxFKM41IzFxWZ54tHw7M0yPXOUWZIBCX1h_JEPaxKO95V-FFKtXiHQVhAZfDloldmiTIVaWbi7qKgEiF2UeCn1cpjcHDwHffC-NoelO6yW9nJ-Y_8Nccz0wc5ZM4lDDqHfWI7wJdzETuyx9Usipura-OlOxjECTZ8FtKzBCR-WtWt3tTbqUj_ICJXiqOaEU7s2s2-F94vv9wIcKVG1ADycoP0OVVgGRTraK1DBVoGijLv5gHyFucTAMh0bYQkAbY11nR4P1K1N0MlsAUlVODC99nqoKbByEG2W-ITmKxDS7OlLTPabe1gOBWEXnrVrb6L2eodF88mJEIRHsCadujm9t8BgVwlEcBi3GTo8gkdbS27nXoBg_6m12M5U8PbEPH9dBy7sMzwGJfwh-mt0JyrJZJ8MrDvx1hjrKIxA8GaSwz4I-V2SGgGfhUtsGP2dFu73Bk9-K5CPsS_ctlon6B9EHIcXrc2kyNeKPm0NClQh7wGNkEfkwejbrfoLm7hBGYqwUKw1-AaaUkEfAEk5aHqm5vbgIHibhl3V0XRDGYlxU_A-NoM_zYxxwFxc33603z0CDAVa2KDKi5nUggl8EgnOdjvZXKhcYcIG5pykyxizDoSiOy06jsAPS_rieG7_ACyx4ZldzheiLpNWztsCmAcZv8TBeDOGbmb6CZSY5n_vXX7oT3cCtjWrqAvjiT6qQasWMsRgLcaM4VawGcMCenkuKO5zwdf4AZiCsUY3Zk0PnvSNZviuwgapVNIU7G3GuJUgbt_7mmz7FUc35DVV7p_e1lMPImraKH5-Eib_njHjP5sSpTFek9JZXKaHxpC9GRjc6xu8DbP_-_0Ly32N200x_2mAtSVo8N5jU-k84droYSRk9PrN4rFhRbMRfAchfoCxZkgtiEGKWsE31Ezq3l0RBXoB7bOLP70FuxWaJx3UvooE4Hm4hpbgOA1itRXSoL8Ij6lcvpA0CLKfWOD_jkjon1C2APtRPPbkumoYeNpRUefOL1sX0gbEwGHwzYuE-rqGuIgcZqtq45AGu8AYn2JGAk-QRPB7IJsbnLeAuuZrKTJftqDKLp1P7U8XBqegD01t6pmXqJ_L7BFhVcSfL6woo7Owm98NNAKWi6xdYtJLy9RIDxJh2bH3djeZ9kqu3ESzy6HiiVVSnhsR8a_puKP91T1Hhlivpo5xJAXi4V8fwinTGy8-7SHsmMyL-njf5voY2u_IbjJHG39wwJ7aofAsZMp9SfGiiseDeEV1NTBlkG7b449hUT1n-mpDUOB8UrVog_NNf2KXHmGYT92OtnlBmX1QgXJ2LiM6R5gw9X-6tua-14dpXwhk6g37oD0HslkGYBl2XTvuOGzgz2WXfhJlrmBAKwjMM2cNZfaivp4s7ANcUk7YS9FWibeXrHay7bYQfOvw7GlXo0_mTLtTOe1Lq1ugzbirPMR9OeGPAHddcSnhKSddm_fmwU5kNv77VZiIwlw1EW_3ErSUnh0Ss7Fp5DjUeYJ13_qV4vmqa6O9U8GUUFmK2E1I3pyguO9HGzy8Sg4baObUzqkI3-r8SW_cQdjkV-D4t", "id": "rs_04d5c5fdfec19789016a08c6f9b1b4819193657afca57f896b", "summary": [] } ], "tool_calls": [ { "id": "call_QdlrlLv5aLc14YJ2aT7iOq3P", "call_id": "call_QdlrlLv5aLc14YJ2aT7iOq3P", "response_item_id": "fc_04d5c5fdfec19789016a08c6fcaee48191b8985692dfa68639", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"python3 - <<'PY'\\nimport sqlite3, hashlib\\nDB='/home/agent/jarvis_runtime/finance-system/data/finance.sqlite3'\\ncon=sqlite3.connect(f'file:{DB}?mode=ro', uri=True)\\ncur=con.cursor()\\n# find account(s) named True Wealth Review Brokerage without printing ids/names\\naccounts=cur.execute(\\\"select account_id, platform_id from accounts where lower(account_name) like '%true wealth review brokerage%'\\\").fetchall()\\nprint('target_accounts_count', len(accounts))\\nfor idx,(aid,pid) in enumerate(accounts,1):\\n print('target', idx, 'account_hash', hashlib.sha256(aid.encode()).hexdigest()[:8], 'platform_hash', hashlib.sha256((pid or '').encode()).hexdigest()[:8])\\n refs=[\\n ('cash_balances','account_id'),('positions_snapshot','account_id'),('transactions','account_id'),\\n ('broker_import_review_items','mapped_account_id'),('broker_import_execution_plans','target_account_id'),\\n ('platform_account_mappings','account_id'),('platform_account_mappings','internal_account_id')]\\n for t,c in refs:\\n cnt=cur.execute(f\\\"select count(*) from {t} where {c}=?\\\",(aid,)).fetchone()[0]\\n if cnt: print(' ref',t,c,cnt)\\n pcnt=cur.execute(\\\"select count(*) from positions_snapshot where platform_id=?\\\",(pid,)).fetchone()[0]\\n if pcnt: print(' platform_ref','positions_snapshot.platform_id',pcnt)\\n# exact pattern in non-crypto text columns, per table row count\\nprint('exact_pattern_rows_by_table')\\nfor (t,) in cur.execute(\\\"select name from sqlite_master where type='table' and name not like 'sqlite_%' order by name\\\"):\\n if t.startswith('crypto_'): continue\\n cols=cur.execute(f\\\"pragma table_info({t})\\\").fetchall()\\n textcols=[c[1] for c in cols if 'TEXT' in (c[2] or '').upper()]\\n if not textcols: continue\\n wh=' or '.join([f\\\"lower(coalesce(\\\\\\\"{c}\\\\\\\",'')) like '%true wealth review brokerage%'\\\" for c in textcols])\\n cnt=cur.execute(f\\\"select count(*) from {t} where {wh}\\\").fetchone()[0]\\n if cnt: print(t,cnt)\\ncon.close()\\nPY\",\"timeout\":60,\"workdir\":\"/home/agent\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"target_accounts_count 1\\ntarget 1 account_hash 8de62952 platform_hash e16b08d7\\n ref transactions account_id 3\\n ref broker_import_review_items mapped_account_id 3\\n ref broker_import_execution_plans target_account_id 3\\nexact_pattern_rows_by_table\\naccounts 1\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_QdlrlLv5aLc14YJ2aT7iOq3P" }, { "role": "assistant", "content": "", "reasoning": null, "finish_reason": "tool_calls", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqCMcKTnY-oxOnDxlAxBtnmMvg-aaklu_PTNyVD4XYOCcr3DKKuryUuoxblZUqkYmEoEF3cPwfhBQTScY3l59Q78gItZTLEXN8-lkIsBGaqIm1VsBKLUAwI_8sR5yd7AkNRHIDT5X7C-lph-YK2cQ4pYmnt2h2nRYwPtHPKl8T2aKcP5JQ5utVMPL_0B5yabCErTqx2wiKTVu0o64M8jKCGaoMA66ACRH6ZGVhG-qMwwx8JM_u5CuYYNpc3N25XWm-IISf-IMnLgtsNrtJtu-2yxrkYAup2i18EcryXdu-dO9K44dxQbgtADIT6d3lmrjgF2kwxct4uR-mk6B3e9KZGD36EHi9DZCGKJj1x0nBy3gFZNNA6H6dGG7UiPa1B0PzdadEDVy8sUq_Uubr9t_G4u9RhLvJgS8_dd0_nS0DkdaqAP92pmgPsCziK0VYtbfhmKGs0nmQ1tp1_Ugg978v06FIJX-n1Quu6TfYNS0Xy2lSGnXTDvb0VqnKIzjaCGb55DAOW6T-_U2Q846m-4I7725959kvW3s-t3wVtNimWwHhmx0mK4XQa22bG20PYE_14Skk7cTX_X5jmkul-nAW53uWFbWulDEMka_hodJA0rnXPRwSa_Qt_KJdUgPZ0oKhbC0j-0v0L0vmUK08M_I4ynQy83ETtcUJ5FINfAcktVbOqLWyzdRZ5nMspojtadsplXc6W0OXL0GCmXT0gTfvTsudpHkIh9PQW3LqUmlqsPurdtjsiTxz842KPiCr7RXxzIFX6IAI3pleuhKvTQrjMY-LOLpOQ9YFfZyPglop4KvtzjnuFm9jI5NRFDlV9d6FQUVbmsxaJ3cr9MqfmRoX5LmGmKowoov-Vxf9fV2Zt-OQ0BGbyrhgo2DVhzQDWNiLi9GzjOl8q6s3eh7lvck4bxoaZHUkDTUcEx5Q7SmIVYC4gZs6-RkJO5ZcbXssi5rGHhBIVrgurt7N7Ok4HWAi3Pwa_kmnhb8uiW03XBbyAGttDVJEcFuiDGmgm_h5Ybj74frDWqXm8yeirxygO1SfNcFfOxB5Hk6r4ERCIu0s5BNZ1d6dbGGQ90vZ9cmcHJ2gwHBd_cPumcmgaBYIQNyWY2EvhPqmyCNVKR7U3EX3yUuCi589weMsdMIgEX2MHAGjk2ouJ5ldJWBhfdjhLAGpSUDxDKkHFmHGSde-sg0jgoN2Gp1qEPXcaSpHx2cDmPVa9rB0zvUG_k8v1HflHOhlh2GRyZapP0TdeoeF3Q7BwYdaB8BiK2uE-Sp9A3XzgCGXV1DjKIBoNa7KSIBEpfvhlZDHTgJd8Dr64VKtpyr0MB9w7sWahFvtkYN7T4QPfb_J42hL6sCcq2qGiccsHH_PlpGIbt8_OxiJvIEndr6GW0LSRHuKGn715pHUSQVooitfJTh2Z2Gi3jbRAg0HPtZXkjZtFBG46KhstmNh0hjEklWBYeG7oYQvaOpX6bgv1WdGf_P7adUG9J2JKbiPyRq7HILwMBhm57R4dsGbE80GN-3AgH6aY9sdq9x89mHxZ6oiRsluzJ3n73ifThXFA89_WPx3AxX0OUiVVFx5l7_Wnmwkf8H33zo-Om7RUcGE3-ZGO1R_", "id": "rs_0c83c0b42fd3f8b7016a08c708aa3881919943f0df7cd4ed96", "summary": [] } ], "tool_calls": [ { "id": "call_n3og8gzgHQhACOWpPqyLVZjq", "call_id": "call_n3og8gzgHQhACOWpPqyLVZjq", "response_item_id": "fc_0c83c0b42fd3f8b7016a08c70afbc0819185128d26e0d63c78", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"python3 - <<'PY'\\nimport sqlite3\\nDB='/home/agent/jarvis_runtime/finance-system/data/finance.sqlite3'\\ncon=sqlite3.connect(f'file:{DB}?mode=ro', uri=True)\\ncur=con.cursor()\\nterms=[('TRUE_WEALTH','%true wealth%'),('BROKERAGE','%brokerage%'),('REVIEW_BROKERAGE','%review brokerage%'),('TRUE_WEALTH_REVIEW','%true wealth review%'),('TEST','%test%')]\\nfor label,pat in terms:\\n print('TERM',label)\\n for (t,) in cur.execute(\\\"select name from sqlite_master where type='table' and name not like 'sqlite_%' order by name\\\"):\\n if t.startswith('crypto_'): continue\\n cols=cur.execute(f\\\"pragma table_info({t})\\\").fetchall()\\n textcols=[c[1] for c in cols if 'TEXT' in (c[2] or '').upper()]\\n hits=[]; row_where=[]; params=[]\\n for c in textcols:\\n cnt=cur.execute(f\\\"select count(*) from {t} where lower(coalesce(\\\\\\\"{c}\\\\\\\",'')) like ?\\\",(pat,)).fetchone()[0]\\n if cnt: hits.append(c)\\n if hits:\\n wh=' or '.join([f\\\"lower(coalesce(\\\\\\\"{c}\\\\\\\",'')) like ?\\\" for c in textcols])\\n cnt=cur.execute(f\\\"select count(*) from {t} where {wh}\\\",[pat]*len(textcols)).fetchone()[0]\\n print(' ',t,'rows',cnt,'cols',','.join(hits))\\ncon.close()\\nPY\",\"timeout\":60,\"workdir\":\"/home/agent\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"TERM TRUE_WEALTH\\n accounts rows 1 cols account_name\\nTERM BROKERAGE\\n accounts rows 5 cols account_id,account_name,account_type\\nTERM REVIEW_BROKERAGE\\n accounts rows 1 cols account_name\\nTERM TRUE_WEALTH_REVIEW\\n accounts rows 1 cols account_name\\nTERM TEST\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_n3og8gzgHQhACOWpPqyLVZjq" }, { "role": "assistant", "content": "", "reasoning": "**Analyzing cursor issues**\n\nI find it interesting that there seems to be a potential bug with the cursor reuse. The audit log test may have been impacted by the cursor inside the same iteration. Actually, it looks like using nested `cur.execute` commands might destroy the outer cursor, resulting in only fetching from the first table. However, since there’s no output from the test, it definitely points to a bug. I should work on writing a more robust function to fetch the table list first.", "finish_reason": "tool_calls", "reasoning_content": "**Analyzing cursor issues**\n\nI find it interesting that there seems to be a potential bug with the cursor reuse. The audit log test may have been impacted by the cursor inside the same iteration. Actually, it looks like using nested `cur.execute` commands might destroy the outer cursor, resulting in only fetching from the first table. However, since there’s no output from the test, it definitely points to a bug. I should work on writing a more robust function to fetch the table list first.", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqCMcVuSRbIVz34sR1uT9LMi4CIAQIAI8498DcscXMre00R2x9-wBUSrE9z12Ux74n3TWj0QnkUAtpTVGXa7qAQO4N8RHPZc8V3RT13Ps3Ad4cnxk7A2IyKACsCxxVU-FK2Vru-rUbvXLKIbOOMhNMAe5UCAdqXlZnfbGaNE4ayGTDqrslbJL9ECSibcm6SQ0KGRB7Vyng5vS7_ZAgdvSzkFstpW1lVVceWmRCUYp3pEJlk0l2k1z_4Lio28SQVu8iA0Ypa0iaHqCOp5HYylRqIB3ZX_jMkIZZlzQ6BMZJRKCLGdVy2qdANoMr5aRQxbD-HDRBV6Y1Zxv3RNDuhgr1gVhPeZe-gx4HHD5NVSQnBS10xYSuJacwajmUbKis9A-zlzyAXidpakzCsOK9nz6Gmuj1I8kos06GnvQIECkW_FAZmIfz7TZzOy5OjQqtO673vQfjAsjS87IPoNiCAc1_KRs1_UnorlyXA9swfRkr5_8Qb9q-UxropqtSiFqVn8vn6S5BbFF7CdHlfotMbqtFKIAh78JQdHYg-3vboaCYb1ouzPoBuKHBAypYF-aCLH_6BFCYT-zUo8_r_ricAbVsTnqSfterCAqRI2228MRvwIDTzAdFixE8JzhXBcIZXqXwkoKTW0T7H2iK8bcbK5Dm10tl1zfYPFHQcz4m-WQ7uFakBPZpyT4ssfjqWOFP0dcLEAOMLAaBNGD7xuxJSZlWfQgxlNdBi8Y2K0ogQ2mzd8NPBeACpHYLt69CaIgczhKXJCR8ieOdPV8oFn01p7nwjVPtr4yl0lGu1EKJb-TDr-vuK5_wKfvTgykqkBNonhzhPVn8P3G7kRelVDrcJbLUxpctdBwwGBEt15Aci-V2ap9wDpwrPGg60rwlMFhjSLPvgPfoKWMT_h2RbAnGBLvlsrBnIlQauBzzL9JA__WDk_Kuh7PE6ZsNROLFf1f40nRtF6XyFzH0Mhs3mug1pltcDHYS7tIYSLABxoZ9wd4XlsfJw7U6qWjpjww_eaFDBmC1fhYoWYJJkDobcwqzsNdhmSClxDcuWHiWwuEcpD6sWgC1atf3Mxj-eXUn688BWkB3llXn--zq0GxuD5o6_i5jUc5OwEjZR4NTo2yY0FLmhwrLK_42f0argjHIcWE08jR6GsIskjN5puouAYn5sEbyuz1i7YXHFouGuQ7SKhedJBOouhvpS8y9TS8myBqsmVV5FnBlmUUxGLGFF_ShTLV0R38PB4POjMLEjG0bW7zh-9X1CJIgW1xagIIEDg1g8hSad8m5", "id": "rs_080111851d69ca07016a08c713b7d48191abc11e60619aad8a", "summary": [ { "type": "summary_text", "text": "**Analyzing cursor issues**\n\nI find it interesting that there seems to be a potential bug with the cursor reuse. The audit log test may have been impacted by the cursor inside the same iteration. Actually, it looks like using nested `cur.execute` commands might destroy the outer cursor, resulting in only fetching from the first table. However, since there’s no output from the test, it definitely points to a bug. I should work on writing a more robust function to fetch the table list first." } ] } ], "tool_calls": [ { "id": "call_gELn4JNdXRxlIE79Rzg7xiud", "call_id": "call_gELn4JNdXRxlIE79Rzg7xiud", "response_item_id": "fc_080111851d69ca07016a08c715fa3c8191b01726a6b91253f4", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"python3 - <<'PY'\\nimport sqlite3\\nDB='/home/agent/jarvis_runtime/finance-system/data/finance.sqlite3'\\ncon=sqlite3.connect(f'file:{DB}?mode=ro', uri=True)\\ncur=con.cursor()\\ntables=[r[0] for r in cur.execute(\\\"select name from sqlite_master where type='table' and name not like 'sqlite_%' order by name\\\").fetchall()]\\nterms=[('TRUE_WEALTH','%true wealth%'),('BROKERAGE','%brokerage%'),('REVIEW_BROKERAGE','%review brokerage%'),('TRUE_WEALTH_REVIEW','%true wealth review%'),('TEST','%test%')]\\nfor label,pat in terms:\\n print('TERM',label)\\n for t in tables:\\n if t.startswith('crypto_'): continue\\n cols=cur.execute(f\\\"pragma table_info({t})\\\").fetchall()\\n textcols=[c[1] for c in cols if 'TEXT' in (c[2] or '').upper()]\\n hits=[]\\n for c in textcols:\\n cnt=cur.execute(f\\\"select count(*) from {t} where lower(coalesce(\\\\\\\"{c}\\\\\\\",'')) like ?\\\",(pat,)).fetchone()[0]\\n if cnt: hits.append(c)\\n if hits:\\n wh=' or '.join([f\\\"lower(coalesce(\\\\\\\"{c}\\\\\\\",'')) like ?\\\" for c in textcols])\\n cnt=cur.execute(f\\\"select count(*) from {t} where {wh}\\\",[pat]*len(textcols)).fetchone()[0]\\n print(' ',t,'rows',cnt,'cols',','.join(hits))\\ncon.close()\\nPY\",\"timeout\":60,\"workdir\":\"/home/agent\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"TERM TRUE_WEALTH\\n accounts rows 1 cols account_name\\n audit_log rows 13 cols new_values_json,user_text_note\\n broker_import_dry_runs rows 1 cols source_name,source_platform,summary_json\\n broker_import_execution_plans rows 3 cols source_platform,notes\\n broker_import_review_items rows 18 cols source_platform,reviewer_note\\n platforms rows 1 cols name\\nTERM BROKERAGE\\n accounts rows 5 cols account_id,account_name,account_type\\n alerts rows 15 cols evidence_json\\n audit_log rows 10 cols entity_id,old_values_json,new_values_json,user_text_note\\n broker_import_execution_plans rows 3 cols target_account_id,planned_write_summary_json\\n broker_import_review_items rows 3 cols mapped_account_id\\n transactions rows 3 cols account_id\\nTERM REVIEW_BROKERAGE\\n accounts rows 1 cols account_name\\nTERM TRUE_WEALTH_REVIEW\\n accounts rows 1 cols account_name\\n audit_log rows 4 cols user_text_note\\nTERM TEST\\n audit_log rows 24 cols action,entity_id,user_text_note\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_gELn4JNdXRxlIE79Rzg7xiud" }, { "role": "assistant", "content": "", "reasoning": "**Considering SQL practices**\n\nI need to be careful about my approach here. If IDs aren’t outputted, I could use Common Table Expressions (CTE) in SQL. For handling alerts, if the evidence_json contains the ID, I might not have a foreign key. To delete specific artifact-related logs, I can use entity_id in the target account ID or apply filters like user_text_note. Audit logs can also include actual notes, although that could be optional. I'm thinking through these details!", "finish_reason": "tool_calls", "reasoning_content": "**Considering SQL practices**\n\nI need to be careful about my approach here. If IDs aren’t outputted, I could use Common Table Expressions (CTE) in SQL. For handling alerts, if the evidence_json contains the ID, I might not have a foreign key. To delete specific artifact-related logs, I can use entity_id in the target account ID or apply filters like user_text_note. Audit logs can also include actual notes, although that could be optional. I'm thinking through these details!", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": 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"id": "rs_01f1d05eb63bcea4016a08c71e0eb08191897b1e12ac1602db", "summary": [ { "type": "summary_text", "text": "**Considering SQL practices**\n\nI need to be careful about my approach here. If IDs aren’t outputted, I could use Common Table Expressions (CTE) in SQL. For handling alerts, if the evidence_json contains the ID, I might not have a foreign key. To delete specific artifact-related logs, I can use entity_id in the target account ID or apply filters like user_text_note. Audit logs can also include actual notes, although that could be optional. I'm thinking through these details!" } ] } ], "tool_calls": [ { "id": "call_1EuRQLR5Iq7wxgfMZ2EQDs0e", "call_id": "call_1EuRQLR5Iq7wxgfMZ2EQDs0e", "response_item_id": "fc_01f1d05eb63bcea4016a08c72ab9048191b5462a4984063fac", "type": "function", "function": { "name": "terminal", "arguments": "{\"command\":\"python3 - <<'PY'\\nimport sqlite3\\nDB='/home/agent/jarvis_runtime/finance-system/data/finance.sqlite3'\\ncon=sqlite3.connect(f'file:{DB}?mode=ro', uri=True)\\ncur=con.cursor()\\nprint('foreign_keys', cur.execute('PRAGMA foreign_keys').fetchone()[0])\\n# dependent preview with temp? can't create read-only; use CTE counts\\nq='''\\nWITH target_account AS (\\n SELECT account_id FROM accounts WHERE lower(account_name)=lower(?)\\n)\\nSELECT 'accounts' table_name, 'account_name' column_name, COUNT(*) FROM accounts WHERE account_id IN (SELECT account_id FROM target_account)\\nUNION ALL SELECT 'transactions','account_id',COUNT(*) FROM transactions WHERE account_id IN (SELECT account_id FROM target_account)\\nUNION ALL SELECT 'broker_import_review_items','mapped_account_id',COUNT(*) FROM broker_import_review_items WHERE mapped_account_id IN (SELECT account_id FROM target_account)\\nUNION ALL SELECT 'broker_import_execution_plans','target_account_id',COUNT(*) FROM broker_import_execution_plans WHERE target_account_id IN (SELECT account_id FROM target_account)\\nUNION ALL SELECT 'positions_snapshot','account_id',COUNT(*) FROM positions_snapshot WHERE account_id IN (SELECT account_id FROM target_account)\\nUNION ALL SELECT 'cash_balances','account_id',COUNT(*) FROM cash_balances WHERE account_id IN (SELECT account_id FROM target_account)\\nUNION ALL SELECT 'platform_account_mappings','account_id/internal_account_id',COUNT(*) FROM platform_account_mappings WHERE account_id IN (SELECT account_id FROM target_account) OR internal_account_id IN (SELECT account_id FROM target_account)\\n'''\\nfor r in cur.execute(q, ('True Wealth Review Brokerage',)):\\n print('|'.join(map(str,r)))\\ncon.close()\\nPY\",\"timeout\":60,\"workdir\":\"/home/agent\"}" } } ] }, { "role": "tool", "name": "terminal", "content": "{\"output\": \"foreign_keys 0\\naccounts|account_name|1\\ntransactions|account_id|3\\nbroker_import_review_items|mapped_account_id|3\\nbroker_import_execution_plans|target_account_id|3\\npositions_snapshot|account_id|0\\ncash_balances|account_id|0\\nplatform_account_mappings|account_id/internal_account_id|0\", \"exit_code\": 0, \"error\": null}", "tool_call_id": "call_1EuRQLR5Iq7wxgfMZ2EQDs0e" }, { "role": "assistant", "content": "## Ergebnis: Runtime-Schema geprüft, DB nicht verändert\n\n**Geprüft:**\n- Runtime-DB: `/home/agent/jarvis_runtime/finance-system/data/finance.sqlite3`\n- UAT-DB Schema ebenfalls kurz gegengeprüft: gleiche relevante Tabellenstruktur\n- Zugriff nur read-only; keine Writes, keine Dateien geändert\n- Crypto-Tabellen bewusst ausgeschlossen/ignoriert\n\n## Relevante Treffer für Cleanup-Artefakt\n\nZiel-Label: `True Wealth Review Brokerage`\n\nDirekt betroffen im Runtime-DB:\n\n- `accounts`\n - Spalte: `account_name`\n - Treffer: 1 Account\n\nAbhängige Treffer über diesen Account:\n\n- `transactions`\n - Spalte: `account_id`\n - Treffer: 3\n\n- `broker_import_review_items`\n - Spalte: `mapped_account_id`\n - Treffer: 3\n\n- `broker_import_execution_plans`\n - Spalte: `target_account_id`\n - Treffer: 3\n\nKeine Treffer über diesen Account:\n\n- `positions_snapshot.account_id`\n- `cash_balances.account_id`\n- `platform_account_mappings.account_id`\n- `platform_account_mappings.internal_account_id`\n\n## Weitere Suchbefunde\n\nBreite Textsuche nach `review` erzeugt viele legitime/technische Treffer, z.B.:\n\n- `broker_import_review_items`\n- `instrument_import_candidates`\n- `instrument_price_mapping_candidates`\n- `alerts`\n- `audit_log`\n- `schema_migrations`\n\nDiese sollten **nicht pauschal** per `%review%` gelöscht werden.\n\n`test`-Treffer gefunden nur in:\n\n- `audit_log`\n - Spalten: `action`, `entity_id`, `user_text_note`\n - Treffer: 24\n\nEmpfehlung: `audit_log` separat behandeln, nicht im primären Finanzdaten-Cleanup löschen, außer gewünscht.\n\n## Sichere SQL-Vorgehensweise\n\nErst Backup, dann Preview, dann Löschung in Transaktion. Keine Crypto-Tabellen anfassen.\n\n```sql\n-- 1) Preview: nur Aggregate prüfen\nWITH target_account AS (\n SELECT account_id\n FROM accounts\n WHERE lower(account_name) = lower(:artifact_account_name)\n)\nSELECT 'accounts' AS table_name, COUNT(*) AS rows\nFROM accounts\nWHERE account_id IN (SELECT account_id FROM target_account)\n\nUNION ALL\nSELECT 'broker_import_execution_plans', COUNT(*)\nFROM broker_import_execution_plans\nWHERE target_account_id IN (SELECT account_id FROM target_account)\n\nUNION ALL\nSELECT 'broker_import_review_items', COUNT(*)\nFROM broker_import_review_items\nWHERE mapped_account_id IN (SELECT account_id FROM target_account)\n\nUNION ALL\nSELECT 'transactions', COUNT(*)\nFROM transactions\nWHERE account_id IN (SELECT account_id FROM target_account)\n\nUNION ALL\nSELECT 'positions_snapshot', COUNT(*)\nFROM positions_snapshot\nWHERE account_id IN (SELECT account_id FROM target_account)\n\nUNION ALL\nSELECT 'cash_balances', COUNT(*)\nFROM cash_balances\nWHERE account_id IN (SELECT account_id FROM target_account);\n```\n\n```sql\n-- 2) Cleanup nach Backup, innerhalb einer Transaktion\nBEGIN IMMEDIATE;\n\nWITH target_account AS (\n SELECT account_id\n FROM accounts\n WHERE lower(account_name) = lower(:artifact_account_name)\n)\nDELETE FROM broker_import_execution_plans\nWHERE target_account_id IN (SELECT account_id FROM target_account);\n\nWITH target_account AS (\n SELECT account_id\n FROM accounts\n WHERE lower(account_name) = lower(:artifact_account_name)\n)\nDELETE FROM broker_import_review_items\nWHERE mapped_account_id IN (SELECT account_id FROM target_account);\n\nWITH target_account AS (\n SELECT account_id\n FROM accounts\n WHERE lower(account_name) = lower(:artifact_account_name)\n)\nDELETE FROM transactions\nWHERE account_id IN (SELECT account_id FROM target_account);\n\nWITH target_account AS (\n SELECT account_id\n FROM accounts\n WHERE lower(account_name) = lower(:artifact_account_name)\n)\nDELETE FROM accounts\nWHERE account_id IN (SELECT account_id FROM target_account);\n\nCOMMIT;\n```\n\nOptional nur falls Audit/Alerts ebenfalls bereinigt werden sollen:\n\n```sql\n-- Nicht automatisch empfohlen:\n-- audit_log / alerts nur über exakt geprüfte artifact-bezogene Kriterien löschen,\n-- nicht über pauschales '%review%' oder '%test%'.\n```\n\n## Hinweise\n\n- `PRAGMA foreign_keys` ist in der Runtime-Verbindung aktuell aus (`0`), daher Löschreihenfolge trotzdem bewusst defensiv: erst abhängige Import-Pläne/Review-Items/Transaktionen, dann Account.\n- Kein Betrag, keine Position, keine reale Menge wurde ausgegeben.\n- Keine Dateien erstellt oder geändert.\n- Keine DB-Modifikation durchgeführt.", "reasoning": null, "finish_reason": "stop", "codex_reasoning_items": [ { "type": "reasoning", "encrypted_content": "gAAAAABqCMc2-SCSJVhkPgzXa6drjF5BvJkEkmKiKzftWPGtkRkv3s4vR-Mqz8AFay6bWUJ3CSz1iihsYEbpn__hwitJYxOcu4-dUGSKAFVPpi38DkrdZWkVby5FR1u-4r8OggQK3RHkoUsJSj2huEGaggcEtq5ivmXDOpyY1r5TAY7RouS8Jg0qTxK1DVC9ewhEg5-Y3AWAfvqzEDRghSGYgOLX3pkHjNfdAtUErI8bUFHffO7XYzDQXyDBoIWDe61Uvh6m_z_vjfdKQ3beDo6muJRntoNd3EZLyQeh-O2ORwIbNqLiYvEL4vUGLzDM0NJ3sgex3onCtmgc108Nf-gQZbFbGOfztgo2MzlfWNDZPPUaOnEbTBcsOb5HrDq-MfoAbEFtniSmgBXGW8-xpXC42dw95NeHuokSwrg48EKtFZpviqlLLX4HoafVARfgtvLi9l6fvWnzVRKqtDa8dt-W155iyTdUOQXlgJqMBPImcUwGrDazy8HUsSl06l4D0HtJ1JsY0gtHxhiVrQ_-XgmcK-BH3IA3Hl0CXZVdiZhAzyFcR22ajWdX6JO-9PiHf4yI96XqS-7D99RHSm41nhbd897yQPwfy__lijNUb3ESUUyCvWUW4KB_aMua92wAZFWog9t34kGJ88Sy4vFRGO-uJayNJC3RcRMiXZnEerkSi3vyPawdkxSVOsXbKFldGVFwI9NyfSHqzBChk9h1cu3qxDby5kaPWtWfNalWD-t4j0kUzWBFnkd9HPyClOFlyZ38iDGDE7gFLh55jGNNB2YBckyTdY6c5JZS4QN4kGGuKkMKAY94uJYt5faauC4sCME1TGwIZKFFRiyolLS1q22Tzn3Y8vpa42nPUo7uOEbGtIJRRDFfbw7-X_i3SxejDfleWfCg76S5iQjopdNwOBwj5k4oADTtQtVHTGpiGCoLzKZkO3VS2brN26UKSQ8bcVqUs9MMiJqUSlL5zsqEovfI4IT3uStcgyFkFWDuIXNxW46SYPT0VD2TiF9OGS5_PfXy9FmIjlvhd5rsLDa4UOwNT6lSmMT10SmXXPzuArJmmOrVqgOgJFlpjDLI07WUO1719V4rmvnc5tQRKliihtCD90zxhybn2mVqt-FNiJsgCRicQhBHnqHrTg2M3kZOgceCY9LtWB9y7fnPAPEAaHNRBrnGfNCBqJEQ4Hwu6jEQsO6VNkQonN_MjeuUtIZzICjzCUJR_VfPunwk8TfMInAFTTzrKTjuSd8Pjs2M9-uiIHuoXsk93RstSXLmjgyCP4_0wmN12sMFrCatmMkkcVWdV1_U_qv4DsjcKR0vW--8pyDd_QrmsDhIrk-2Ln9gzZ-Bvz14TvBJJlOhLiHuYtfQnJJB1ek7KcvPMMtfhlkrqWG-0q_twx16NZI327nE-cmrIipeU_cEl4HiJStF63iNN14mc1q35R5l85i0Mk92qV3oXhopv_1Ku-Y04OzCX2OUy57H_9_gWKGy_d2Mgmd3cQukLGUYn6vKJ61BdPm7iQcQ-Pk3qyu3tKh2OO1ylXeHwcPO-XiPu0d-D9PPsbSFpq3jFbfEn4RQNtdWS8_-IKfaRuqBho3acLFFYR8T8gT55Vs1sJPQFwANKGggZNjgn_jFPFmNx5q8hQ0kt6RjBgnP1HFvdbAoA86os-l0Onln64y9-yvfSU8stGo3kVoq4u9PBXdLB6l1mOQ6Na100Cxfwmx7OFw=", "id": "rs_046071ead5cfc9ed016a08c733ff888191b8792974054a4209", "summary": [] } ], "codex_message_items": [ { "type": "message", "role": "assistant", "status": "completed", "content": [ { "type": "output_text", "text": "## Ergebnis: Runtime-Schema geprüft, DB nicht verändert\n\n**Geprüft:**\n- Runtime-DB: `/home/agent/jarvis_runtime/finance-system/data/finance.sqlite3`\n- UAT-DB Schema ebenfalls kurz gegengeprüft: gleiche relevante Tabellenstruktur\n- Zugriff nur read-only; keine Writes, keine Dateien geändert\n- Crypto-Tabellen bewusst ausgeschlossen/ignoriert\n\n## Relevante Treffer für Cleanup-Artefakt\n\nZiel-Label: `True Wealth Review Brokerage`\n\nDirekt betroffen im Runtime-DB:\n\n- `accounts`\n - Spalte: `account_name`\n - Treffer: 1 Account\n\nAbhängige Treffer über diesen Account:\n\n- `transactions`\n - Spalte: `account_id`\n - Treffer: 3\n\n- `broker_import_review_items`\n - Spalte: `mapped_account_id`\n - Treffer: 3\n\n- `broker_import_execution_plans`\n - Spalte: `target_account_id`\n - Treffer: 3\n\nKeine Treffer über diesen Account:\n\n- `positions_snapshot.account_id`\n- `cash_balances.account_id`\n- `platform_account_mappings.account_id`\n- `platform_account_mappings.internal_account_id`\n\n## Weitere Suchbefunde\n\nBreite Textsuche nach `review` erzeugt viele legitime/technische Treffer, z.B.:\n\n- `broker_import_review_items`\n- `instrument_import_candidates`\n- `instrument_price_mapping_candidates`\n- `alerts`\n- `audit_log`\n- `schema_migrations`\n\nDiese sollten **nicht pauschal** per `%review%` gelöscht werden.\n\n`test`-Treffer gefunden nur in:\n\n- `audit_log`\n - Spalten: `action`, `entity_id`, `user_text_note`\n - Treffer: 24\n\nEmpfehlung: `audit_log` separat behandeln, nicht im primären Finanzdaten-Cleanup löschen, außer gewünscht.\n\n## Sichere SQL-Vorgehensweise\n\nErst Backup, dann Preview, dann Löschung in Transaktion. Keine Crypto-Tabellen anfassen.\n\n```sql\n-- 1) Preview: nur Aggregate prüfen\nWITH target_account AS (\n SELECT account_id\n FROM accounts\n WHERE lower(account_name) = lower(:artifact_account_name)\n)\nSELECT 'accounts' AS table_name, COUNT(*) AS rows\nFROM accounts\nWHERE account_id IN (SELECT account_id FROM target_account)\n\nUNION ALL\nSELECT 'broker_import_execution_plans', COUNT(*)\nFROM broker_import_execution_plans\nWHERE target_account_id IN (SELECT account_id FROM target_account)\n\nUNION ALL\nSELECT 'broker_import_review_items', COUNT(*)\nFROM broker_import_review_items\nWHERE mapped_account_id IN (SELECT account_id FROM target_account)\n\nUNION ALL\nSELECT 'transactions', COUNT(*)\nFROM transactions\nWHERE account_id IN (SELECT account_id FROM target_account)\n\nUNION ALL\nSELECT 'positions_snapshot', COUNT(*)\nFROM positions_snapshot\nWHERE account_id IN (SELECT account_id FROM target_account)\n\nUNION ALL\nSELECT 'cash_balances', COUNT(*)\nFROM cash_balances\nWHERE account_id IN (SELECT account_id FROM target_account);\n```\n\n```sql\n-- 2) Cleanup nach Backup, innerhalb einer Transaktion\nBEGIN IMMEDIATE;\n\nWITH target_account AS (\n SELECT account_id\n FROM accounts\n WHERE lower(account_name) = lower(:artifact_account_name)\n)\nDELETE FROM broker_import_execution_plans\nWHERE target_account_id IN (SELECT account_id FROM target_account);\n\nWITH target_account AS (\n SELECT account_id\n FROM accounts\n WHERE lower(account_name) = lower(:artifact_account_name)\n)\nDELETE FROM broker_import_review_items\nWHERE mapped_account_id IN (SELECT account_id FROM target_account);\n\nWITH target_account AS (\n SELECT account_id\n FROM accounts\n WHERE lower(account_name) = lower(:artifact_account_name)\n)\nDELETE FROM transactions\nWHERE account_id IN (SELECT account_id FROM target_account);\n\nWITH target_account AS (\n SELECT account_id\n FROM accounts\n WHERE lower(account_name) = lower(:artifact_account_name)\n)\nDELETE FROM accounts\nWHERE account_id IN (SELECT account_id FROM target_account);\n\nCOMMIT;\n```\n\nOptional nur falls Audit/Alerts ebenfalls bereinigt werden sollen:\n\n```sql\n-- Nicht automatisch empfohlen:\n-- audit_log / alerts nur über exakt geprüfte artifact-bezogene Kriterien löschen,\n-- nicht über pauschales '%review%' oder '%test%'.\n```\n\n## Hinweise\n\n- `PRAGMA foreign_keys` ist in der Runtime-Verbindung aktuell aus (`0`), daher Löschreihenfolge trotzdem bewusst defensiv: erst abhängige Import-Pläne/Review-Items/Transaktionen, dann Account.\n- Kein Betrag, keine Position, keine reale Menge wurde ausgegeben.\n- Keine Dateien erstellt oder geändert.\n- Keine DB-Modifikation durchgeführt." } ], "id": "msg_046071ead5cfc9ed016a08c7369a9c8191ba6a57d26c9c7d09", "phase": "final_answer" } ] } ] }