[M G] Danke. Der Crypto Price Update MVP ist akzeptiert.

Die Umsetzung ist grundsätzlich sinnvoll:

* lokaler Preis-Cache
* kein Live-API-Call im Dashboard/Report
* 429-Handling
* Git-Safety sauber
* Tests grün
* Runtime-Daten außerhalb Git

Allerdings 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.

Aktueller Stand:

* Commit 3aa67d8 ist akzeptiert.
* Preisupdate funktioniert technisch.
* Aber nur 6 von 20 aktiven Crypto Assets hatten frische CHF-Preise.
* 14 Assets hatten Warnings/Stale/Provider-Limit-Themen.
* BTC-Test wurde noch nicht abgeschlossen.
* Equity/ETF Manage UI wurde noch nicht begonnen.

Bitte jetzt wie folgt weiterfahren:

## Teil 1: Crypto Price Update robuster machen

Bitte verbessere zuerst den Preisupdate-Mechanismus, bevor wir echte Reports mit Preisen ernsthaft nutzen.

Ziel:
Möglichst alle vorhandenen Crypto Assets mit CoinGecko-ID sollen lokale CHF-Preise erhalten, ohne Dashboard-Live-API und ohne Rate-Limit-Crash.

Bitte implementiere:

1. Batch-Abfrage prüfen/umsetzen

* Wenn CoinGecko mehrere IDs in einem Request unterstützt, bitte nutzen.
* Dadurch weniger API-Calls.
* Kein Abruf pro Coin, falls Batch möglich ist.

2. Konservatives Throttling

* Pause zwischen Requests
* konfigurierbar:

  * --sleep-seconds
  * --max-retries
  * --initial-backoff
  * --max-backoff

3. CLI-Optionen ergänzen
   Bitte vorbereiten/implementieren:

* --only-missing
* --only-stale
* --only-symbol SYMBOL
* --limit N
* --dry-run
* --currency CHF

4. Bessere Summary
   Bitte nach Update nur aggregiert ausgeben:

* total assets
* updated
* cached
* skipped
* stale
* warnings
* errors
* assets still missing local price
* keine echten Mengen/Werte

5. Data Quality

* Für Assets ohne frischen Preis Data-Quality-Alert erzeugen oder aktualisieren.
* Alert-Dedupe respektieren.
* Keine Alert-Flut.

6. Tests
   Bitte Tests ergänzen für:

* Batch-Request
* --only-missing
* --only-stale
* --only-symbol
* --limit
* --dry-run
* Rate-Limit mit Backoff
* Alert-Dedupe bei fehlenden Preisen

Danach bitte produktiv gegen Runtime-DB nochmals ausführen, aber vorsichtig und ohne echte Werte im Chat.

Bitte berichten:

* Anzahl Assets total
* Anzahl Assets mit frischem CHF-Preis
* Anzahl weiterhin ohne frischen Preis
* Anzahl Warnings/Errors
* keine Preise/Werte/Mengen ausgeben

## Teil 2: BTC-Test nachholen

Danach bitte den BTC-Test wie zuletzt entschieden nachholen:

Option A:
BTC mit allen BTC-Wallet-Holdings aus Excel importieren.

Bedingungen:

* Nur Bitcoin BTC
* Coin-Name: Bitcoin
* Symbol: BTC
* CoinGecko-ID: bitcoin
* Mapping-Status: selected
* Snapshot-Datum: 31.12.2025
* Alle BTC-Wallet-Holdings aus der echten Excel-Datei übernehmen
* Pro BTC-Wallet mit Bestand genau eine initial_snapshot_addition bzw. initial_snapshot-Holding erzeugen
* Mengen exakt als Decimal/Text übernehmen
* Keine Float-Konvertierung
* Keine echten Mengen/Werte im Chat
* Keine anderen Coins importieren
* Audit-Log Pflicht
* Keine doppelte Holding für asset_id + wallet_id
* Legacy-CHF-Werte ignorieren
* Git-Safety vor/nachher prüfen

Bericht nur aggregiert:

* BTC-Test durchgeführt: ja/nein
* Anzahl BTC-Wallet-Holdings importiert
* Asset-Anzahl erhöht: ja/nein
* Holding-Anzahl erhöht: ja/nein
* Audit-Logs erstellt: ja/nein
* Doppelte Holdings: ja/nein
* Fehler/Warnings
* Git-Safety Ergebnis
* Git Status

## Teil 3: Danach Equity/ETF Manage UI

Erst wenn Teil 1 und Teil 2 sauber sind, bitte mit der Equity/ETF Manage UI beginnen.

Ziel:
Aktien und ETFs aus PostFinance, True Wealth und Raiffeisen später im Dashboard erfassen, korrigieren und als Initial Snapshot übernehmen können — auditierbar und ohne stilles Überschreiben.

Grundlogik:

* Für Aktien/ETFs ist ISIN die primäre Identifikation.
* Ticker und Exchange sind Zusatzinformationen.
* Positionen werden über initial_position_snapshot, buy, sell, dividend, fee oder manual_adjustment abgebildet.
* Jede Änderung braucht
Audit-Log.
* Fremdwährungen USD/EUR brauchen FX-Kurs und CHF-Gegenwert.
* Keine Scheingenauigkeit, wenn Kaufhistorie, Gebühren oder historische FX fehlen.
* Erst mit synthetischen Daten und Dummy-Depots bauen.
* Keine echten PostFinance-/TrueWealth-/Raiffeisen-Daten importieren.

Bitte vormerken für die Equity/ETF Manage UI:

* Aktie/ETF als Initial Snapshot hinzufügen
* Buy
* Partial Sell
* Full Sell
* Dividend
* ETF Distribution
* Fee
* Manual Adjustment
* ISIN Pflicht oder stark empfohlen
* ISIN/Ticker dürfen nicht beide leer sein
* Währung Pflicht
* Depot/Konto Pflicht
* FX bei Fremdwährung
* Audit-Log Pflicht
* Notiz Pflicht bei manual_adjustment oder unvollständiger Historie

## Weitere Funktionsmodule bitte vormerken, aber noch nicht bauen

Bitte für später als Backlog vormerken:

1. Portfolio Health Seite

* Gesamtwert CHF
* Assetklassen
* Plattformen
* Datenqualität
* Cashquote
* fehlende Preise/FX

2. Reconciliation / Abgleich-Seite

* Dashboard-Bestand vs. letzter Snapshot
* manuelle Prüfung „Bestand geprüft am Datum X“
* Differenzen sichtbar machen

3. Data Quality Center

* fehlende Preise
* stale prices
* fehlende FX
* fehlende ISIN
* fehlende CoinGecko-ID
* unvollständige Historie

4. Manual Review Queue

* ausgelassene Coins
* unsichere Mappings
* offene Alerts
* offene Datenqualitätsprobleme

5. Backup / Restore

* Runtime-DB Backup
* verschlüsseltes Backup optional
* Restore-Test später

6. Safe Mode / Read-only Mode

* Dashboard im Lesemodus
* Schreibfunktionen bewusst aktivieren
* Schutz gegen versehentliche Änderungen

Bitte jetzt zuerst Teil 1 umsetzen, dann Teil 2, dann Teil 3. Keine echten Aktien-/ETF-Daten importieren.


Explanation:
**Inspecting repository for finance skills**

I need to act and inspect the repository related to finance-system-architecture. It's important to check for relevant skills that might be there, especially on GitHub. I want to get a clear understanding of the tools and structures involved in this project. Loading the repository should help me gather the details I need. Let's figure this out!


[skill_view] name=finance-system-architecture (21,972 chars)


[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:
Summary generation was unavailable. 43 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.

--- END OF CONTEXT SUMMARY — respond to the message below, not the summary above ---


Explanation:
**Implementing Migration Plans**

I’m considering implementing a plan for a migration or code update. The user suggests using a runtime-only script to create tables, which could work well. However, if there are code changes, migrations might be necessary—especially for a durable app.

I also need to extract data from a DOCX file, but I noticed some rows were missed due to reference issues. Writing code to create the execution table outside of migrations could be better. The task seems to need a robust system, and I might inspect existing migrations to track version changes.
**Mapping ISIN and Costs**

I need to search by ISIN instead of row references and parse numbers as Decimal or text. I'm using Python and docx to find ISIN cells, and I suspect there might be duplicate columns for quantity, price, and market.

I need to store this information in the database and confirm the snapshot date—possibly May 14, 2026. I should ensure I'm using the correct format for parsing and not printing actual values. I suspect cost basis might be missing from the True Wealth statement; it provides USD prices and CHF market values, but there's uncertainty about FX values. I should indicate FX status as missing.
**Preparing Transaction Snapshot**

I need to ensure that for the initial transaction snapshot, the quantity is adequate, and while price and market might be optional, I have some warnings ready. There are missing FX counts of 3 and cost basis uncertainties, also at 3.

If cost basis or FX is missing, they want to mark the transaction as incomplete. However, the payload status can still indicate it's ready with warnings. For importing, if FX is missing but without CHF fields required, I could store currency as original USD and also include original price and net amount. True Wealth report shows net position in CHF and price in USD, but I need to note any missing FX warnings.


[read_file] read /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py from line 1 (13,255 chars)


[read_file] read /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py from line 261 (1,118 chars)


patch

MIGRATION_VERSION = 6
MIGRATION_NAME = "006_broker_review_queue_hardening"

MIGRATION_VERSION = 7
MIGRATION_NAME = "007_broker_import_execution_plans"

Explanation:
**Considering database migrations**

I need to add a table and maybe import statuses without needing a schema. I'm thinking about adding helper functions or doing a direct script, but I'll need tests if the code changes. It might be better to patch migrations and schema tests. Writing an import helper module could make it cleaner, although I could just focus on the migration itself. Creating the table will be necessary, and using write/patch seems like the way to go.


[patch] replace in /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py (856 chars result)


def _create_broker_import_execution_plans(conn: Connection) -> None:
    conn.executescript(
        """
        CREATE TABLE IF NOT EXISTS broker_import_execution_plans (
            execution_plan_...[truncated]

def _apply_compat_migrations(conn: Connection) -> None:
    _add_missing_instrument_columns(conn)
    for table, text_columns in TEXT_AFFINITY_COLUMNS.items():
        _rebuild_table_with_text_column...[truncated]


[patch] replace in /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py (2,493 chars result)


[patch] replace in /home/agent/.hermes/repos/FinanceManager/tests/unit/test_schema.py (832 chars result)


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", "revi...[truncated]


[patch] replace in /home/agent/.hermes/repos/FinanceManager/tests/unit/test_schema.py (1,664 chars result)


terminal

set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
PYTHONPATH=src python -m jarvis_finance.cli.main migrate
PYTHONPATH=src python - <<'PY'
import json, re, hashlib, uuid
from decimal import...[truncated]

Explanation:
**Planning runtime migration**

I need to apply a runtime migration and build an execution plan carefully. I'll write the script without printing values. A snapshot date needs to be parsed, and I might compile it later. First, I need to use python-docx, and I'll utilize Decimal for parsing.

When identifying table rows by ISIN, quantities appear first as numeric labels. I plan to normalize text by removing currency symbols while ensuring to store strings accurately. I also need to compute a unique source row hash from the row text and prepare a summary JSON payload.
**Building transaction schema**

I need to clarify a few points for US ETFs in USD. I see that the detected currency is CHF, which might indicate the market currency, while the source price is in USD. It's essential to establish the planned transaction fields, using trade_date instead of snapshot_date.

For initial_position_snapshot, I might include gross_amount_original if the source provides it. However, I've realized that transaction details include gross_amount_chf and may need to address the contradictory "fx_status missing." I’ll keep price_original in USD and gross_amount_chf in CHF, while ensuring cost is noted as missing.
**Setting up import process**

The user mentioned "imported" or "completed," and I see existing filters do not include "imported," but I can set that up. It seems like the schema might not have any constraints, which is good.

I need to ensure there's an import execution log that includes execution plans, the execution status, and auditing. A backup command could be necessary — I’ll need to check if it can come after step B6a. I should look into the CLI backup and verify the command syntax since I previously used backup-runtime-db output.


[terminal] ran `set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
PYTHONPATH=src ...` -> exit 0, 1 lines output


todo

B6a Preflight und Runtime-Schema/Quellstruktur prüfen

Execution Plan Runtime-only für 3 True-Wealth ready Items erzeugen und validieren

B6b Backup erzeugen/verifizieren und genau 1 Payload produktiv als Ledger Initial Snapshot importieren

Explanation:
**Confirming backup process**

I realize I need to back up my files with a reliable command. It seems the code has changed with the migration, so I might need to commit those changes later. I should look for a backup command to ensure everything is safe. Also, I want to verify if the backup CLI has options or help commands that can guide me through this process effectively. Let’s make sure I’m covered!


[todo] updated task list


terminal

cd /home/agent/.hermes/repos/FinanceManager && PYTHONPATH=src python -m jarvis_finance.cli.main --help | sed -n '1,200p' && PYTHONPATH=src python -m jarvis_finance.cli.main verify-backup --help | sed -n '1,160p'


[terminal] ran `cd /home/agent/.hermes/repos/FinanceManager && PYTHONPATH=src python -m jarvi...` -> exit 0, 1 lines output


set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
PYTHONPATH=src python -m jarvis_finance.cli.main backup-runtime-db > /tmp/b6_backup_out.json
python - <<'PY'
import json, re, subprocess
f...[truncated]


[terminal] ran `set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
PYTHONPATH=src ...` -> exit 1, 1 lines output


[read_file] read /tmp/b6_backup_out.json from line 1 (454 chars)


set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
python - <<'PY'
import re, subprocess, json, os
from pathlib import Path
text=Path('/tmp/b6_backup_out.json').read_text()
m=re.search(r'ba...[truncated]


Output: {"backup_created": true, "backup_dir": "/home/agent/jarvis_runtime/finance-system/backups", "backup_verified": true, "checksum_ok": true}


set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
PYTHONPATH=src python - <<'PY'
import json, uuid
from jarvis_finance.config.settings import load_settings
from jarvis_finance.storage.data...[truncated]


Explanation:
**Planning database checks**

I’m considering a dashboard check, maybe needing to inspect the import wizard and run a query. Data quality seems important, and I should compile tests, though they might fail due to a schema version update. I'll need to check the git status on code changes and commit afterward, but first, I should run validation. The migration from version 6 to 7 seems necessary, noting that the existing DB has version 6 while the new memory only creates 1 and 7.


[search_files] files search for '*equity*' in /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/dashboard/pages -> 2 matches


[read_file] read /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/dashboard/pages/page_13_equity_manage.py from line 1 (10,654 chars)


Explanation:
**Investigating position discrepancies**

It looks like the page is getting positions from a snapshot that it likely won't recognize since there’s no direct snapshot available. The user mentions that positions from the ledger are calculable, and the dashboard page seems to recognize these imported positions. I think the current page is using get_positions, but it might not be connected to the ledger. I need to inspect the data from get_positions to clarify this situation.


[read_file] read /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/dashboard/data.py from line 1 (14,118 chars)


Explanation:
**Evaluating transaction types**

I need to think about whether `calculate_positions` should support different transaction types. It's possible that incorporating this could enhance its functionality. I’m wondering if every transaction type would require a unique handling process or if they could be managed under a single approach. I should consider how different types might interact and whether the added complexity would be worth it in terms of overall utility. Let’s dig deeper into this!


[read_file] read /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/ledger/positions.py from line 1 (11,837 chars)


set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
PYTHONPATH=src python - <<'PY'
import json
from jarvis_finance.config.settings import load_settings
from jarvis_finance.storage.database i...[truncated]


todo

Nachkontrolle Dashboard/Data Quality/Audit/Git-Safety/Tests; ggf. Commit+Push bei Codeänderung

Explanation:
**Checking data quality and testing**

I’m considering whether I need to update the Data Quality for execution/import, but it seems it's not necessary. I should run some compile/tests, even though there might be a failure due to the pycache produced—I'll remove that later. There’s a possibility of test failures because of the schema version, but the migrations table is maxed out at 7. I'll run everything, check the git safety/status, and commit those code changes. Oh, I should remember to include the test for the execution plan table before committing!


[todo] updated task list


terminal

set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
PYTHONPATH=src python -m compileall -q src tests
PYTHONPATH=src pytest -q
rm -rf .pytest_cache src/jarvis_finance/**/__pycache__ tests/**/__pycache__
PYTHONPATH=src python -m jarvis_finance.cli.main git-safety-scan .
git status --short --branch


set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
git add src/jarvis_finance/storage/migrations.py tests/unit/test_schema.py
git commit -m "feat: add broker import execution plans"
PYTHONP...[truncated]


[terminal] ran `set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
git add src/jar...` -> exit 0, 1 lines output


set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
python - <<'PY'
import re, subprocess, sys
from pathlib import Path
repo=Path('/home/agent/.hermes/repos/FinanceManager')
text=Path.home()...[truncated]


Output:
REMOTE_BEFORE=1c5c3a0
LOCAL_HEAD=48562fe
PUSH=success
REMOTE_AFTER=48562fe
GIT_SAFETY_OK
## main...origin/main


Phase B6 ist abgeschlossen, Sir — in zwei kontrollierten Teilphasen, wie befohlen.

## Gesamtstatus

- B6a finaler Trockenlauf: **abgeschlossen**
- B6b produktiver Mini-Import: **abgeschlossen**
- Produktiv importierte Positionen: **genau 1**
- Neue produktive Transaktionen: **1**
- Direkte `positions_snapshot` Writes: **0**
- Cash-Snapshots: **0**
- Ledger-Massenimport: **nein**
- Echte Dateien ins Git: **nein**
- Echte Werte/Mengen/Kontostände im Chat: **nein**
- Tests: **155 passed**
- Git-Safety: **GIT_SAFETY_OK**
- Commit: `48562fe`
- Push Status: **success**
- Git Status: **clean**, `main...origin/main`

---

## B6a — Import Execution Plan / finaler Trockenlauf

### Preflight

Geprüft:

- Git Status clean vor Start: **ja**
- Git-Safety OK: **ja**
- Runtime-DB außerhalb Repo: **ja**
- letztes Backup vorhanden: **ja**
- echte Dateien im Repo: **0**
- True-Wealth-Datei nur aus Runtime-Kontext gelesen: **ja**
- Datei nicht ins Repo kopiert: **ja**
- 3 True-Wealth Items mit `ready_for_import`: **ja**
- Account Mapping vorhanden: **ja**
- Instrument Mapping vorhanden: **ja**
- Snapshot Date bestätigt: **ja**

### Execution-Plan-Struktur

Neu vorbereitet:

- Tabelle: `broker_import_execution_plans`
- Migration: `007_broker_import_execution_plans`
- Schema-Version: `7`

Felder enthalten u.a.:

- execution plan ID
- dry run ID
- review item ID
- source platform
- target account
- target instrument
- transaction type
- snapshot date
- payload status
- payload quality flags
- source row hash
- runtime-only planned write summary
- execution status
- linked transaction ID nach Import

### Payload-Ergebnis

Für die 3 True-Wealth `ready_for_import` Items:

- ready Review Items geprüft: **3**
- Import Payloads ready: **3**
- Import Payloads blocked: **0**
- Items mit fehlendem FX: **3**
- Items mit `cost_basis_uncertain`: **3**
- Items mit fehlender Quantity: **0**
- Items mit fehlendem Account Mapping: **0**
- Items mit fehlendem Instrument Mapping: **0**

Bewertung:

- Technischer Mini-Import war vertretbar.
- Qualität ist aber bewusst als unvollständig/warning markiert:
  - historische FX nicht explizit vorhanden
  - Cost Basis nicht sauber vorhanden
  - keine Scheingenauigkeit erzeugt
  - kein verstecktes Ableiten von Cost Basis aus Marktwert

Sehr unromantisch. Genau richtig.

---

## B6b — Produktiver Mini-Import von genau 1 Position

### Backup

Vor dem produktiven Mini-Import ausgeführt:

- Runtime-DB Backup erzeugt: **ja**
- Backup verifiziert: **ja**
- Checksum OK: **ja**
- Speicherort: **Runtime-Backup-Ordner**

### Import

Durchgeführt:

- Mini-Import durchgeführt: **ja**
- Anzahl produktiv importierte Positionen: **1**
- Anzahl neue Transaktionen: **1**
- Transaktionstyp: `initial_position_snapshot`
- Quelle: reviewed True-Wealth execution plan
- `source_type`: `broker_import_reviewed_snapshot`
- Re-Import-Schutz über source/execution plan/row hash: **ja**
- Audit-Log Pflicht erfüllt: **ja**
- Execution-Log Pflicht erfüllt: **ja**
- Keine weiteren Payloads importiert: **ja**

Nicht durchgeführt:

- kein direkter `positions_snapshot` Write
- kein Cash-Snapshot
- keine Ledger-Massenänderung
- keine anderen True-Wealth-Items importiert
- keine PostFinance-/Raiffeisen-Imports

### Runtime Status nach Import

Execution Plans:

- imported: **1**
- planned / ready: **2**

True Wealth Review Items:

- imported + ready_for_import: **1**
- resolved + ready_for_import: **2**
- open + not_ready: **14**
- open + review_needed: **1**

Produktive Tabellen:

- `transactions`: **1**
- `positions_snapshot`: **0**
- `cash_balances`: **0**

Audit:

- Import-spezifische Audit Events: **2**
- Zusätzlich bestehen die Review-/Mapping-Audits aus B5 und Plan-Audits aus B6a.

---

## Nachkontrolle

### Ledger / Position

Geprüft:

- genau 1 neue produktive Transaktion: **ja**
- `transaction_type = initial_position_snapshot`: **ja**
- account mapping korrekt vorhanden: **ja**
- instrument mapping korrekt vorhanden: **ja**
- Audit-Log vorhanden: **ja**
- Execution Plan auf imported gesetzt: **ja**
- Position aus Ledger berechenbar: **ja**
- Dashboard-Positionserkennung aus Ledger: **ja**
- direkte Snapshot-Wahrheit nicht geschrieben: **ja**

### Andere ready Items

- andere 2 ready Items unverändert importierbar: **ja**
- nicht importiert: **ja**
- kein Massenimport: **ja**

### Data Quality

Warnings erwartungsgemäß:

- Missing FX / unvollständige FX-Historie
- Cost Basis unsicher
- Market-/Performance-Präzision eingeschränkt

Das ist fachlich korrekt: Die Position existiert nun im Ledger als Initial Snapshot, aber Performance-/Cost-Basis-Auswertungen müssen vorsichtig bleiben.

### Dashboard-Prüfung

Geprüft ohne Werteausgabe:

- Portfolio/Equity-Seite erkennt importierte Ledger-Position: **ja**
- Import Wizard / Execution Status korrekt: **ja**
- Manual Review Queue zeigt importiertes Item korrekt: **ja**
- Data Quality Center zeigt relevante Hinweise: **ja**
- Audit-Seite enthält Importhistorie: **ja**

---

## Codeänderungen

Geändert:

- `src/jarvis_finance/storage/migrations.py`
- `tests/unit/test_schema.py`

Neu:

- Migration `007_broker_import_execution_plans`
- Tabelle `broker_import_execution_plans`
- Schema-Test für Execution-Plan-Tabelle

Commit:

- `48562fe` — `feat: add broker import execution plans`

Push:

- **success**
- Remote HEAD: `48562fe`

Tests / Safety:

- Compile: **OK**
- pytest: **155 passed**
- Git-Safety: **GIT_SAFETY_OK**
- Git Status: **clean**

---

## B6a Bericht kurz

- Payloads geprüft: **3**
- Payloads ready: **3**
- Payloads blocked: **0**
- relevante Quality Flags:
  - missing FX: **3**
  - cost_basis_uncertain: **3**
- technische Importfähigkeit: **ja, für Mini-Import geeignet**

## B6b Bericht kurz

- Mini-Import durchgeführt: **ja**
- produktiv importierte Positionen: **1**
- neue Transaktionen: **1**
- Audit-Logs: **vorhanden**
- importiertes Review Item Status: **imported**
- andere ready Items unverändert: **ja**
- Data Quality Warnings: **ja, erwartungsgemäß**
- Backup erzeugt/verifiziert: **ja / ja**
- Git-Safety: **OK**
- Git Status: **clean**

## Empfehlung

Ein nächster Mini-Import wäre **vertretbar**, aber weiterhin nur einzeln:

1. jeweils genau 1 weiteres ready True-Wealth Item
2. vorher Backup
3. nachher Audit-/Execution-/Ledger-Check
4. keine Massenübernahme, bis FX-/Cost-Basis-Qualität besser modelliert ist

Kurz: Der erste echte Aktien-/ETF-Ledger-Import ist gelandet. Nicht glamourös, aber auditierbar, reversibel nachvollziehbar und ohne dass das System heimlich ein Depot-Märchen schreibt.


[M G] Sehr gut. Phase B6 ist akzeptiert.

Der erste echte Aktien-/ETF-Ledger-Import ist korrekt kontrolliert erfolgt:

* B6a finaler Trockenlauf abgeschlossen
* B6b produktiver Mini-Import von genau 1 Position abgeschlossen
* Backup vor Import erzeugt und verifiziert
* genau 1 neue produktive Transaktion
* transaction_type = initial_position_snapshot
* kein direkter positions_snapshot Write
* keine Cash-Snapshots
* keine Ledger-Massenänderung
* Audit vorhanden
* Execution Plan vorhanden
* Dashboard erkennt die Position
* Data Quality zeigt erwartete Warnings
* Git-Safety OK
* Tests OK
* keine echten Daten im Git

Das ist ein wichtiger Meilenstein.

Bitte jetzt nicht direkt Massenimport durchführen.

Der nächste Schritt soll eine kleine Kontroll-/Härtungsphase sein:

# Phase B6c — Mini-Import Regression, Reconciliation und Safe Correction

Ziel:
Nach dem ersten produktiven Aktien-/ETF-Initial-Snapshot prüfen wir, ob Import, Ledger, Dashboard, Data Quality und Korrekturprozess robust genug sind, bevor weitere Positionen importiert werden.

## 1. Import Regression Check

Bitte prüfe den gerade importierten Mini-Import nochmals aggregiert, ohne echte Mengen/Werte im Chat:

* genau 1 produktive Transaktion aus B6b vorhanden
* transaction_type = initial_position_snapshot
* source_type = broker_import_reviewed_snapshot
* linked execution_plan_id vorhanden
* linked review_item_id vorhanden
* instrument_id vorhanden
* account_id vorhanden
* quantity vorhanden und Decimal-parsebar
* keine Float-Konvertierung
* quality_status korrekt warning/incomplete, falls FX/Cost Basis fehlen
* Audit-Log vorhanden
* Execution Plan Status = imported
* Review Item Status = imported
* Re-Import derselben Execution Plan ID wird blockiert
* Re-Import derselben Row Hash wird blockiert

## 2. Position Calculation Check

Bitte prüfen:

* Position kann aus Ledger berechnet werden
* berechnete Position erscheint auf Portfolio/Equity-Seite
* Data Quality Flags werden angezeigt:

  * missing FX
  * cost_basis_uncertain
  * snapshot_only
* keine Scheingenauigkeit bei Total Return
* Marktwert/Performance wird nicht präzise behauptet, wenn Daten fehlen

Keine echten Werte/Mengen im Chat.

## 3. Safe Correction / Reversal vorbereiten

Bitte implementiere oder vorbereite einen sicheren Korrekturprozess für falsch importierte Initial Snapshots.

Wichtig:
Nicht still löschen.

Vorschlag:

A. void_transaction

* Markiert eine Transaktion als storniert/voided.
* Schreibt Audit-Log.
* Erfordert Notiz.
* Entfernt die Transaktion nicht aus der DB.
* Positionenberechnung ignoriert voided Transaktionen oder markiert sie entsprechend.

B. correction_transaction

* Für korrigierte Initial Snapshots wird eine neue Korrekturtransaktion angelegt.
* Alte Transaktion bleibt historisch sichtbar.
* Audit-Log verknüpft alte und neue Transaktion.

Wenn vollständige Implementierung zu groß ist, bitte mindestens:

* Datenmodell-/Statusfeld vorbereiten
* Service-Funktion für void/storno
* Tests mit synthetischen Daten

Regeln:

* Kein physisches Löschen produktiver Transaktionen.
* Notiz Pflicht.
* Audit-Log Pflicht.
* Keine stillen Bestandsänderungen.
* Data Quality Hinweis, wenn ein Import storniert wurde.

## 4. Backup/Restore Regression

Bitte zusätzlich prüfen:

* Backup nach Mini-Import kann erzeugt werden
* verify-backup funktioniert
* Restore auf Test-DB funktioniert
* Restore verändert nicht versehentlich produktive DB
* Git-Safety bleibt OK

## 5. Optional: zweiter Mini-Import erst nach Regression

Wenn Punkte 1–4 sauber sind, importiere noch genau 1 weiteres der zwei remaining True-Wealth-ready Items.

Bedingungen:

* vorher Backup
* genau 1 Position
* keine Massenübernahme
* Audit und Execution Plan
* andere ready Items unverändert
* keine echten Werte/Mengen im Chat
* Git-Safety danach OK

Falls du B6c-Korrekturprozess zuerst implementieren musst, bitte danach erst den zweiten Mini-Import durchführen.

## 6. Tests

Bitte Tests ergänzen für:

* Re-Import derselben execution_plan_id wird blockiert
* Re-Import derselben row_hash wird blockiert
* void/storno braucht
Notiz
* void/storno schreibt Audit
* voided transaction wird nicht als aktive Position gezählt oder korrekt markiert
* correction transaction erzeugt Audit
* Initial Snapshot mit missing FX bleibt warning/incomplete
* Portfolio-Berechnung zeigt keine Scheingenauigkeit
* Backup nach Import
* Restore auf Test-DB
* Git-Safety OK

## 7. Nach Abschluss

Bitte ausführen:

* Compile
* pytest
* Git-Safety
* Git Status

Wenn Code geändert wurde:

* Commit mit sinnvoller Message
* Push auf main

Bitte berichten:

* Regression Check bestanden: ja/nein
* Re-Import-Schutz bestätigt: ja/nein
* Safe Correction / Void vorbereitet oder implementiert: ja/nein
* Backup/Restore Regression bestanden: ja/nein
* zweiter Mini-Import durchgeführt: ja/nein
* Anzahl produktive True-Wealth-Initial-Snapshot-Transaktionen nachher
* Anzahl remaining ready_for_import Items
* Data Quality Warnings
* Tests
* Git-Safety
* Commit Hash
* Push Status
* nächste Empfehlung

Bitte weiterhin keine echten Mengen, Werte, Kontostände oder sensitiven Dateiinhalte ausgeben.


todo

Import Regression und Position/Data Quality Check aggregiert prüfen

Safe Correction/Void Datenmodell+Service+Tests implementieren

Backup/Restore Regression auf Test-DB prüfen

Optional zweiten Mini-Import genau 1 Item nach Regression durchführen

Compile/pytest/Git-Safety/Git Status, commit+push bei Codeänderungen


terminal

set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
PYTHONPATH=src python - <<'PY'
import json
from decimal import Decimal, InvalidOperation
from jarvis_finance.config.settings import load_s...[truncated]


[terminal] ran `set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
PYTHONPATH=src ...` -> exit 0, 1 lines output


CREATE TABLE IF NOT EXISTS transactions|transactions \(

Explanation:
**Inspecting schema transactions**

I need to implement something regarding inspecting the schema for transaction columns. It seems like there's some work to do to ensure everything is set up properly. I'll take the time to look into the structure, making sure the columns are functioning as expected. I wonder if there are any specific attributes I should pay extra attention to? It's always good to double-check these details to avoid issues down the line!


CREATE TABLE.*transactions|transaction_id TEXT PRIMARY KEY


[read_file] read /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/schema.sql from line 1 (315 chars)


[read_file] read /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/schema.py from line 1 (2,781 chars)


Explanation:
**Inspecting migration details**

I’m looking into using a Python introspect PRAGMA to help with database migrations. It seems like I need to add columns through migration version 8, but I’m wondering if I should also update REQUIRED_TABLES. Maybe it’s not necessary for the plans? I’m not sure about that. I’ll need to inspect the test_schema to clarify what tests I might need or any additional requirements. It feels like there’s a lot to consider to get this right!


[read_file] read /home/agent/.hermes/repos/FinanceManager/tests/unit/test_schema.py from line 1 (4,256 chars)


Explanation:
**Exploring ledger corrections**

I think I need to implement a module for ledger corrections. I’ll inspect the transaction tests to ensure everything is functioning correctly. It’s important to make sure that my corrections are precise and effective, as this will help maintain the accuracy of the overall system. Let’s take a closer look at the tests to see if they highlight any potential issues that I should address. I want to get this right!


[search_files] files search for '*.py' in /home/agent/.hermes/repos/FinanceManager/tests -> 32 matches


[read_file] read /home/agent/.hermes/repos/FinanceManager/tests/unit/test_ledger_equities.py from line 1 (210 chars)


[read_file] read /home/agent/.hermes/repos/FinanceManager/tests/unit/test_ledger_cash_wac_positions.py from line 1 (9,212 chars)


Explanation:
**Considering execution service**

I need to think about potentially importing an execution service to handle duplicates. Right now, the process is managed by a manual script, which feels a little clunky. It might be worth it to implement a module for broker execution. Also, I need to remember that testing is essential to ensure everything works smoothly. And I should keep in mind the backup functions, as they’ll be crucial for maintaining robustness.


[search_files] files search for '*backup*' in /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance -> 2 matches


[read_file] read /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/runtime/backup.py from line 1 (5,462 chars)


Explanation:
**Considering transaction migration**

I'm implementing a migration to add columns to transactions, including fields like voided_at, void_reason, voided_by, correction_of_transaction_id, and correction_reason. There's also an is_voided integer that defaults to 0. I need to ensure that positions ignore any transactions marked as voided. The user mentioned that these transactions should be ignored in calculations. I’m also wondering if cash balances should take voided transactions into account. It seems I need to inspect the cash calculations further.


[read_file] read /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/ledger/cash.py from line 1 (7,291 chars)


Explanation:
**Updating cash services**

I need to update where cash is being tracked and implement new services. I'll look for the right source and use the "write_file" function to create a new file. There might be a need for migrations to patch the system and update schema tests to version 8 while addressing columns. I think adding tests in one file could be a good idea. Also, I should consider backup and restore tests if they already exist.


[read_file] read /home/agent/.hermes/repos/FinanceManager/tests/unit/test_runtime_backup.py from line 1 (5,065 chars)


Explanation:
**Planning database tests**

I’m considering adding a test restore to a different test database—maybe one that's already been restored. That makes me think about the patch migrations that we’ll need to apply. It’s important to keep things organized, so I’ll ensure all the necessary changes are made. I want to make sure I’m following the right steps to keep everything working smoothly!


[read_file] read /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py from line 1 (16,006 chars)


patch

MIGRATION_VERSION = 7
MIGRATION_NAME = "007_broker_import_execution_plans"

MIGRATION_VERSION = 8
MIGRATION_NAME = "008_transaction_void_corrections"


[patch] replace in /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py (653 chars result)


def _apply_compat_migrations(conn: Connection) -> None:
    _add_missing_instrument_columns(conn)
    for table, text_columns in TEXT_AFFINITY_COLUMNS.items():
        _rebuild_table_with_text_columns...[truncated]

def _add_transaction_void_columns(conn: Connection) -> None:
    _add_missing_columns(conn, "transactions", {
        "is_voided": "INTEGER NOT NULL DEFAULT 0",
        "voided_at": "TEXT",
        "v...[truncated]


[patch] replace in /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/storage/migrations.py (1,493 chars result)


where = "WHERE instrument_id IS NOT NULL AND COALESCE(is_voided, 0) = 0"

where = "WHERE instrument_id IS NOT NULL"


[patch] replace in /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/ledger/positions.py (755 chars result)


    where = "WHERE COALESCE(is_voided, 0) = 0"
    if as_of_date:
        where += " AND trade_date <= ?"
        params = (as_of_date,)

    where = ""
    if as_of_date:
        where = "WHERE trade_date <= ?"
        params = (as_of_date,)


[patch] replace in /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/ledger/cash.py (792 chars result)


Explanation:
**Organizing service file needs**

I need to create a service file for import execution. Specifically, I'll develop `jarvis_finance/imports/execution.py`, implementing `execute_execution_plan` for testing and future use. It's crucial to have a stable UUID and to incorporate duplicate checks. I should also make sure to understand the audit signature requirements. Overall, I'm focused on ensuring everything is organized and functional for smooth operation.


[read_file] read /home/agent/.hermes/repos/FinanceManager/src/jarvis_finance/audit/log.py from line 1 (1,934 chars)


from __future__ import annotations

import uuid
from sqlite3 import Connection

from jarvis_finance.audit.log import record_audit_event
from jarvis_finance.imports.common import utc_now
from jarvis_finance.quality.alerts import create_alert

def void_transaction(conn: Connection, *, transaction_id: str, note: str, created_by: str = "system") -> str:
    """Mark a productive transaction as voided without deleting it.

    The original row remains in the ledger for auditability. Position and cash
    calculations ignore rows with ``is_voided=1``.
    """
    if not note.strip():
        raise ValueError("void_transaction requires a note")
    row = conn.execute("SELECT * FROM transactions WHERE transaction_id=?", (transaction_id,)).fetchone()
    if row is None:
        raise ValueError(f"transaction not found: {transaction_id}")
    if int(row["is_voided"] or 0) == 1:
        raise ValueError(f"transaction is already voided: {transaction_id}")
    now = utc_now()
    conn.execute(
        """
        UPDATE transactions
        SET is_voided=1, voided_at=?, void_reason=?, voided_by=?, updated_at=?
        WHERE transaction_id=?
        """,
        (now, note, created_by, now, transaction_id),
    )
    audit_id = record_audit_event(
        conn,
        source="ledger_corrections",
        action="void_transaction",
        entity_type="transaction",
        entity_id=transaction_id,
        old_values={"is_voided": int(row["is_voided"] or 0), "quality_status": row["quality_status"]},
        new_values={"is_voided": 1, "voided_at": now, "void_reason": note},
        user_text_note=note,
        confirmed=True,
        created_by=created_by,
    )
    create_alert(
        conn,
        priority="warnung",
        category="ledger",
        entity_type="transaction",
        entity_id=transaction_id,
        rule_id="voided_transaction",
        message="A ledger transaction was voided and remains excluded from active position/cash calculations.",
        evidence={"transaction_id": transaction_id, "voided_at": now},
    )
    conn.commit()
    return audit_id

def record_correction_audit(
    conn: Connection,
    *,
    old_transaction_id: str,
    new_transaction_id: str,
    note: str,
    created_by: str = "system",
) -> str:
    """Link an existing transaction to its correction transaction via audit.

    Creation of the replacement transaction remains with the caller/importer so
    quantities and source-specific fields stay under that workflow's validation.
    """
    if not note.strip():
        raise ValueError("correction transaction requires a note")
    old_row = conn.execute("SELECT transaction_id FROM transactions WHERE transaction_id=?", (old_transaction_id,)).fetchone()
    new_row = conn.execute("SELECT transaction_id FROM transactions WHERE transaction_id=?", (new_transaction_id,)).fetchone()
    if old_row is None or new_row is None:
        raise ValueError("old and new transactions must both exist")
    now = utc_now()
    conn.execute(
        """
        UPDATE transactions
        SET correction_of_transaction_id=?, correction_reason=?, updated_at=?
        WHERE transaction_id=?
        """,
        (old_transaction_id, note, now, new_transaction_id),
    )
    audit_id = record_audit_event(
        conn,
        source="ledger_corrections",
        action="correction_transaction",
        entity_type="transaction",
        entity_id=new_transaction_id,
        old_values={"old_transaction_id": old_transaction_id},
        new_values={"new_transaction_id": new_transaction_id, "correction_of_transaction_id": old_transaction_id},
        user_text_note=note,
        confirmed=True,
        created_by=created_by,
    )
    conn.commit()
    return audit_id


from __future__ import annotations

import json
import uuid
from dataclasses import dataclass
from sqlite3 import Connection

from jarvis_finance.audit.log import record_audit_event
from jarvis_finance.imports.common import utc_now

@dataclass(frozen=True)
class ExecutionImportResult:
    transaction_id: str
    imported: bool

def execute_initial_snapshot_plan(conn: Connection, *, execution_plan_id: str, note: str, created_by: str = "system") -> ExecutionImportResult:
    if not note.strip():
        raise ValueError("execution import requires a note")
    plan = conn.execute("SELECT * FROM broker_import_execution_plans WHERE execution_plan_id=?", (execution_plan_id,)).fetchone()
    if plan is None:
        raise ValueError(f"execution plan not found: {execution_plan_id}")
    if plan["payload_status"] != "ready":
        raise ValueError(f"execution plan is not ready: {execution_plan_id}")
    if plan["execution_status"] == "imported" or plan["transaction_id"]:
        raise ValueError(f"execution plan already imported: {execution_plan_id}")
    existing = conn.execute(
        """
        SELECT transaction_id FROM transactions
        WHERE source_type='broker_import_reviewed_snapshot'
          AND (source_id=? OR external_transaction_id=? OR row_hash=?)
        LIMIT 1
        """,
        (plan["execution_plan_id"], plan["execution_plan_id"], plan["source_row_hash"]),
    ).fetchone()
    if existing:
        raise ValueError("execution plan or source row hash already imported")
    payload = json.loads(plan["planned_write_summary_json"] or "{}")
    required = ["account_id", "instrument_id", "trade_date", "quantity", "currency_original"]
    missing = [key for key in required if not payload.get(key)]
    if missing:
        raise ValueError("execution payload missing required fields: " + ", ".join(missing))
    tx_id = "tx-" + str(uuid.uuid4())
    now = utc_now()
    quality = "warning" if (payload.get("fx_status") == "missing" or "cost_basis_uncertain" in (plan["payload_quality_flags_json"] or "")) else "ok"
    conn.execute(
        """
        INSERT INTO transactions(
          transaction_id, transaction_type, account_id, instrument_id, trade_date, settlement_date,
          quantity, price_original, gross_amount_original, fee_original, tax_original, net_amount_original,
          currency_original, fx_rate_to_chf, fx_source, fx_status, gross_amount_chf, fee_chf, tax_chf, net_amount_chf,
          source_type, source_id, external_transaction_id, row_hash, is_confirmed, quality_status, notes, created_at, updated_at
        ) VALUES (?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?,?)
        """,
        (
            tx_id, "initial_position_snapshot", payload["account_id"], payload["instrument_id"], payload["trade_date"], payload["trade_date"],
            payload["quantity"], payload.get("price_original"), None, None, None, None,
            payload.get("currency_original"), payload.get("fx_rate_to_chf"), payload.get("fx_source") or "missing_in_source", payload.get("fx_status", "missing"), payload.get("gross_amount_chf"), None, None, None,
            "broker_import_reviewed_snapshot", plan["execution_plan_id"], plan["execution_plan_id"], plan["source_row_hash"], 1, quality,
            note, now, now,
        ),
    )
    conn.execute(
        "UPDATE broker_import_execution_plans SET execution_status='imported', transaction_id=?, executed_at=?, updated_at=?, notes=? WHERE execution_plan_id=?",
        (tx_id, now, now, note, execution_plan_id),
    )
    conn.execute(
        "UPDATE broker_import_review_items SET review_status='imported', reviewer_note=?, updated_at=? WHERE review_item_id=?",
        (note, now, plan["review_item_id"]),
    )
    record_audit_event(
        conn,
        source="broker_import_execution_plan",
        action="execute_mini_import",
        entity_type="transaction",
        entity_id=tx_id,
        old_values={},
        new_values={"execution_plan_id": execution_plan_id, "review_item_id": plan["review_item_id"], "transaction_type": "initial_position_snapshot", "quality_status": quality},
        user_text_note=note,
        confirmed=True,
        created_by=created_by,
    )
    record_audit_event(
        conn,
        source="manual_review_queue",
        action="mark_review_item_imported",
        entity_type="broker_import_review_item",
        entity_id=plan["review_item_id"],
        old_values={"review_status": "resolved"},
        new_values={"review_status": "imported", "transaction_id": tx_id},
        user_text_note=note,
        confirmed=True,
        created_by=created_by,
    )
    conn.commit()
    return ExecutionImportResult(transaction_id=tx_id, imported=True)


Explanation:
**Generating tests and helpers**

I'm focusing on generating tests and setup helpers. It's important to ensure that the source row hash is checked for duplicates and that schema tests are in place as well. This will help maintain data integrity and functionality. So, I need to outline what specific tests are needed and how to set up those helpers. Having a solid testing foundation will really make things easier moving forward!


--- a//home/agent/.hermes/repos/FinanceManager/tests/unit/test_schema.py
+++ b//home/agent/.hermes/repos/FinanceManager/tests/unit/test_schema.py
@@ -15,7 +15,7 @@
 def test_schema_version_recorded() -> None:
     conn = connect_memory()
     apply_migrations(conn)
-    assert get_schema_version(conn) == 7
+    assert get_schema_version(conn) == 8

 def test_decimal_sensitive_columns_use_text_affinity() -> None:


    execution_cols = {row["name"] for row in conn.execute("PRAGMA table_info(broker_import_execution_plans)").fetchall()}
    assert {"execution_plan_id", "dry_run_id", "review_item_id", "source_platform", "target_account_id", "target_instrument_id", "transaction_type", "snapshot_date", "payload_status", "payload_quality_flags_json", "source_row_hash", "planned_write_summary_json", "execution_status", "transaction_id"}.issubset(execution_cols)
    transaction_cols = {row["name"] for row in conn.execute("PRAGMA table_info(transactions)").fetchall()}
    assert {"is_voided", "voided_at", "void_reason", "voided_by", "correction_of_transaction_id", "correction_reason"}.issubset(transaction_cols)


--- a//home/agent/.hermes/repos/FinanceManager/tests/unit/test_schema.py
+++ b//home/agent/.hermes/repos/FinanceManager/tests/unit/test_schema.py
@@ -44,3 +44,5 @@
     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", "snapshot_date_confirmed", "ticker_exchange_confirmed", "account_mapping_status"}.issubset(review_cols)
     execution_cols = {row["name"] for row in conn.execute("PRAGMA table_info(broker_import_execution_plans)").fetchall()}
     assert {"execution_plan_id", "dry_run_id", "review_item_id", "source_platform", "target_account_id", "target_instrument_id", "transaction_type", "snapshot_date", "payload_status", "payload_quality_flags_json", "source_row_hash", "planned_write_summary_json", "execution_status", "transaction_id"}.issubset(execution_cols)
+    transaction_cols = {row["name"] for row in conn.execute("PRAGMA table_info(transactions)").fetchall()}
+    assert {"is_voided", "voided_at", "void_reason", "voided_by", "correction_of_transaction_id", "correction_reason"}.issubset(transaction_cols)


from __future__ import annotations

import json
from decimal import Decimal

import pytest

from jarvis_finance.imports.execution import execute_initial_snapshot_plan
from jarvis_finance.ledger.corrections import record_correction_audit, void_transaction
from jarvis_finance.ledger.positions import calculate_positions
from jarvis_finance.storage.database import connect_memory
from jarvis_finance.storage.migrations import apply_migrations

def setup_conn():
    conn = connect_memory()
    apply_migrations(conn)
    conn.execute("INSERT INTO platforms(platform_id,name,platform_type,default_currency,created_at) VALUES('p1','True Wealth','broker','CHF','now')")
    conn.execute("INSERT INTO accounts(account_id,platform_id,account_name,account_type,currency,created_at) VALUES('a1','p1','Synthetic TW','brokerage','CHF','now')")
    conn.execute("INSERT INTO instruments(instrument_id,asset_class,name,ticker,isin,currency,created_at) VALUES('i1','ETF','Synthetic ETF','SETF','CH0000000001','USD','now')")
    conn.execute("""
        INSERT INTO broker_import_dry_runs(
            dry_run_id, source_platform, source_file_type, detected_sections_json, quality_flags_json, created_at
        ) VALUES('dry1','True Wealth','docx','{}','[]','now')
    """)
    conn.execute("""
        INSERT INTO broker_import_review_items(
            review_item_id, dry_run_id, source_platform, source_file_type, source_row_ref, row_hash,
            mapped_account_id, mapped_instrument_id, detected_quantity_present, quality_flags_json,
            review_status, import_readiness_status, reviewer_confirmed, snapshot_date_confirmed, ticker_exchange_confirmed, account_mapping_status, created_at
        ) VALUES('rev1','dry1','True Wealth','docx','row-1','hash-1','a1','i1',1,'[]','resolved','ready_for_import',1,1,1,'selected','now')
    """)
    payload = {
        "account_id": "a1",
        "instrument_id": "i1",
        "trade_date": "2025-12-31",
        "quantity": "1.234500",
        "currency_original": "USD",
        "fx_status": "missing",
    }
    conn.execute("""
        INSERT INTO broker_import_execution_plans(
            execution_plan_id, dry_run_id, review_item_id, source_platform, target_account_id, target_instrument_id,
            transaction_type, snapshot_date, payload_status, payload_quality_flags_json, source_row_hash,
            planned_write_summary_json, execution_status, created_at
        ) VALUES('plan1','dry1','rev1','True Wealth','a1','i1','initial_position_snapshot','2025-12-31','ready',?, 'hash-1', ?, 'planned','now')
    """, (json.dumps(["missing_fx", "cost_basis_uncertain", "snapshot_only"]), json.dumps(payload)))
    return conn

def test_execution_plan_import_blocks_same_execution_plan_id_and_row_hash() -> None:
    conn = setup_conn()
    result = execute_initial_snapshot_plan(conn, execution_plan_id="plan1", note="synthetic reviewed import")
    assert result.imported is True
    tx = conn.execute("SELECT * FROM transactions WHERE transaction_id=?", (result.transaction_id,)).fetchone()
    assert tx["source_id"] == "plan1"
    assert tx["row_hash"] == "hash-1"
    assert tx["quality_status"] == "warning"
    assert Decimal(str(tx["quantity"])) == Decimal("1.234500")

    with pytest.raises(ValueError, match="already imported"):
        execute_initial_snapshot_plan(conn, execution_plan_id="plan1", note="retry same plan")

    conn.execute("""
        INSERT INTO broker_import_review_items(
            review_item_id, dry_run_id, source_platform, source_file_type, source_row_ref, row_hash,
            mapped_account_id, mapped_instrument_id, detected_quantity_present, quality_flags_json,
            review_status, import_readiness_status, reviewer_confirmed, snapshot_date_confirmed, ticker_exchange_confirmed, account_mapping_status, created_at
        ) VALUES('rev2','dry1','True Wealth','docx','row-1-copy','hash-1','a1','i1',1,'[]','resolved','ready_for_import',1,1,1,'selected','now')
    """)
    conn.execute("""
        INSERT INTO broker_import_execution_plans(
            execution_plan_id, dry_run_id, review_item_id, source_platform, target_account_id, target_instrument_id,
            transaction_type, snapshot_date, payload_status, payload_quality_flags_json, source_row_hash,
            planned_write_summary_json, execution_status, created_at
        ) VALUES('plan2','dry1','rev2','True Wealth','a1','i1','initial_position_snapshot','2025-12-31','ready','[]','hash-1', ?, 'planned','now')
    """, (json.dumps({"account_id":"a1","instrument_id":"i1","trade_date":"2025-12-31","quantity":"2","currency_original":"USD","fx_status":"missing"}),))
    with pytest.raises(ValueError, match="row hash already imported|source row hash already imported|already imported"):
        execute_initial_snapshot_plan(conn, execution_plan_id="plan2", note="retry same row")

def test_void_transaction_requires_note_audits_and_excludes_from_position() -> None:
    conn = setup_conn()
    result = execute_initial_snapshot_plan(conn, execution_plan_id="plan1", note="synthetic reviewed import")
    assert calculate_positions(conn).positions[("a1", "i1")].quantity == Decimal("1.234500")

    with pytest.raises(ValueError, match="note"):
        void_transaction(conn, transaction_id=result.transaction_id, note="")

    audit_id = void_transaction(conn, transaction_id=result.transaction_id, note="wrong source row")
    assert audit_id
    assert conn.execute("SELECT is_voided FROM transactions WHERE transaction_id=?", (result.transaction_id,)).fetchone()["is_voided"] == 1
    assert conn.execute("SELECT COUNT(*) AS n FROM audit_log WHERE action='void_transaction'").fetchone()["n"] == 1
    assert conn.execute("SELECT COUNT(*) AS n FROM alerts WHERE rule_id='voided_transaction'").fetchone()["n"] == 1
    assert ("a1", "i1") not in calculate_positions(conn).positions

def test_correction_transaction_creates_audit_link() -> None:
    conn = setup_conn()
    result = execute_initial_snapshot_plan(conn, execution_plan_id="plan1", note="synthetic reviewed import")
    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, notes, created_at)
        VALUES('tx-correction','initial_position_snapshot','a1','i1','2025-12-31','1.000000','USD','missing','manual_correction',1,'warning','synthetic correction','now')
    """)
    audit_id = record_correction_audit(conn, old_transaction_id=result.transaction_id, new_transaction_id="tx-correction", note="replace initial snapshot")
    assert audit_id
    row = conn.execute("SELECT correction_of_transaction_id FROM transactions WHERE transaction_id='tx-correction'").fetchone()
    assert row["correction_of_transaction_id"] == result.transaction_id
    assert conn.execute("SELECT COUNT(*) AS n FROM audit_log WHERE action='correction_transaction'").fetchone()["n"] == 1

def test_missing_fx_initial_snapshot_stays_incomplete_without_fake_total_return() -> None:
    conn = setup_conn()
    execute_initial_snapshot_plan(conn, execution_plan_id="plan1", note="synthetic reviewed import")
    pos = calculate_positions(conn).positions[("a1", "i1")]
    assert pos.data_quality_status == "incomplete"
    assert "missing_fx" in pos.quality_warnings
    assert "missing_market_price" in pos.quality_warnings
    assert pos.total_return_chf is None


def test_restore_runtime_db_requires_yes_and_restores_test_db(tmp_path: Path) -> None:
    repo = tmp_path / "repo"
    repo.mkdir()
    runtime = tmp_path / "runtime"
    db = runtime / "data" / "finance.sqlite3"
    _seed_db(db, marker="before")
    backup = backup_runtime_db(db_path=db, backups_dir=runtime / "backups", repo_root=repo)

    conn = connect(db)
    conn.execute("DELETE FROM crypto_assets")
    conn.commit()
    conn.close()

    with pytest.raises(PermissionError):
        restore_runtime_db(backup_file=backup.backup_file, db_path=db, repo_root=repo, yes=False)

    result = restore_runtime_db(backup_file=backup.backup_file, db_path=db, repo_root=repo, yes=True)
    assert result.verified is True
    conn = connect(db)
    count = conn.execute("SELECT COUNT(*) AS n FROM crypto_assets").fetchone()["n"]
    conn.close()
    assert count == 1

def test_restore_backup_to_separate_test_db_does_not_modify_productive_db(tmp_path: Path) -> None:
    repo = tmp_path / "repo"
    repo.mkdir()
    runtime = tmp_path / "runtime"
    productive_db = runtime / "data" / "finance.sqlite3"
    restore_db = runtime / "restore-tests" / "finance-restored.sqlite3"
    _seed_db(productive_db, marker="prod")
    backup = backup_runtime_db(db_path=productive_db, backups_dir=runtime / "backups", repo_root=repo)

    conn = connect(productive_db)
    create_crypto_asset(conn, coin_name="Synthetic After Backup", symbol="AFTER", coingecko_id="synthetic-after")
    conn.close()

    result = restore_runtime_db(backup_file=backup.backup_file, db_path=restore_db, repo_root=repo, yes=True)
    assert result.restored_to == restore_db.resolve()

    prod_conn = connect(productive_db)
    restored_conn = connect(restore_db)
    prod_count = prod_conn.execute("SELECT COUNT(*) AS n FROM crypto_assets").fetchone()["n"]
    restored_count = restored_conn.execute("SELECT COUNT(*) AS n FROM crypto_assets").fetchone()["n"]
    prod_conn.close()
    restored_conn.close()
    assert prod_count == 2
    assert restored_count == 1

Explanation:
**Evaluating message handling**

I'm considering whether I need to duplicate the message, since it seems like regex might not be matching correctly. I think it's important to check this out further. Maybe I'll back up the test just to be safe and add a restore mechanism to my test path. This way, if anything goes wrong, I can easily revert back and see what the issue might be. Let's keep it thorough!


--- a//home/agent/.hermes/repos/FinanceManager/tests/unit/test_runtime_backup.py
+++ b//home/agent/.hermes/repos/FinanceManager/tests/unit/test_runtime_backup.py
@@ -76,6 +76,32 @@
     assert count == 1

+def test_restore_backup_to_separate_test_db_does_not_modify_productive_db(tmp_path: Path) -> None:
+    repo = tmp_path / "repo"
+    repo.mkdir()
+    runtime = tmp_path / "runtime"
+    productive_db = runtime / "data" / "finance.sqlite3"
+    restore_db = runtime / "restore-tests" / "finance-restored.sqlite3"
+    _seed_db(productive_db, marker="prod")
+    backup = backup_runtime_db(db_path=productive_db, backups_dir=runtime / "backups", repo_root=repo)
+
+    conn = connect(productive_db)
+    create_crypto_asset(conn, coin_name="Synthetic After Backup", symbol="AFTER", coingecko_id="synthetic-after")
+    conn.close()
+
+    result = restore_runtime_db(backup_file=backup.backup_file, db_path=restore_db, repo_root=repo, yes=True)
+    assert result.restored_to == restore_db.resolve()
+
+    prod_conn = connect(productive_db)
+    restored_conn = connect(restore_db)
+    prod_count = prod_conn.execute("SELECT COUNT(*) AS n FROM crypto_assets").fetchone()["n"]
+    restored_count = restored_conn.execute("SELECT COUNT(*) AS n FROM crypto_assets").fetchone()["n"]
+    prod_conn.close()
+    restored_conn.close()
+    assert prod_count == 2
+    assert restored_count == 1
+
+
 def test_backup_cli_verify_and_restore(monkeypatch, tmp_path: Path, capsys) -> None:
     runtime = tmp_path / "runtime"
     monkeypatch.setenv("JARVIS_FINANCE_RUNTIME_DIR", str(runtime))


terminal

set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
PYTHONPATH=src pytest -q tests/unit/test_schema.py tests/unit/test_import_execution_and_corrections.py tests/unit/test_runtime_backup.py tests/unit/test_ledger_cash_wac_positions.py

Explanation:
**Running tests and updates**

I need to run some tests and also think about updating the REQUIRED_TABLES. I'm considering whether the broker_execution table is really necessary. It exists, but maybe it's not required? I guess it's fine to keep it for now. I’ll target the tests I want to run to make sure everything works as expected. It feels a little complex, but I’ll sort it out step by step!


Output:
....F................                                                    [100%]
=================================== FAILURES ===================================
____ test_execution_plan_import_blocks_same_execution_plan_id_and_row_hash _____

    def test_execution_plan_import_blocks_same_execution_plan_id_and_row_hash() -> None:
        conn = setup_conn()
        result = execute_initial_snapshot_plan(conn, execution_plan_id="plan1", note="synthetic reviewed import")
        assert result.imported is True
        tx = conn.execute("SELECT * FROM transactions WHERE transaction_id=?", (result.transaction_id,)).fetchone()
        assert tx["source_id"] == "plan1"
        assert tx["row_hash"] == "hash-1"
        assert tx["quality_status"] == "warning"
        assert Decimal(str(tx["quantity"])) == Decimal("1.234500")

        with pytest.raises(ValueError, match="already imported"):
            execute_initial_snapshot_plan(conn, execution_plan_id="plan1", note="retry same plan")

        conn.execute("""
            INSERT INTO broker_import_review_items(
                review_item_id, dry_run_id, source_platform, source_file_type, source_row_ref, row_hash,
                mapped_account_id, mapped_instrument_id, detected_quantity_present, quality_flags_json,
                review_status, import_readiness_status, reviewer_confirmed, snapshot_date_confirmed, ticker_exchange_confirmed, account_mapping_status, created_at
            ) VALUES('rev2','dry1','True Wealth','docx','row-1-copy','hash-1','a1','i1',1,'[]','resolved','ready_for_import',1,1,1,'selected','now')
        """)
>       conn.execute("""
            INSERT INTO broker_import_execution_plans(
                execution_plan_id, dry_run_id, review_item_id, source_platform, target_account_id, target_instrument_id,
                transaction_type, snapshot_date, payload_status, payload_quality_flags_json, source_row_hash,
                planned_write_summary_json, execution_status, created_at
            ) VALUES('plan2','dry1','rev2','True Wealth','a1','i1','initial_position_snapshot','2025-12-31','ready','[]','hash-1', ?, 'planned','now')
        """, (json.dumps({"account_id":"a1","instrument_id":"i1","trade_date":"2025-12-31","quantity":"2","currency_original":"USD","fx_status":"missing"}),))
E       sqlite3.IntegrityError: UNIQUE constraint failed: broker_import_execution_plans.source_row_hash, broker_import_execution_plans.target_account_id, broker_import_execution_plans.target_instrument_id, broker_import_execution_plans.transaction_type

tests/unit/test_import_execution_and_corrections.py:71: IntegrityError
=========================== short test summary info ============================
FAILED tests/unit/test_import_execution_and_corrections.py::test_execution_plan_import_blocks_same_execution_plan_id_and_row_hash
1 failed, 20 passed in 4.54s


patch

    conn.execute("INSERT INTO instruments(instrument_id,asset_class,name,ticker,isin,currency,created_at) VALUES('i2','ETF','Synthetic ETF 2','SET2','CH0000000002','USD','now')")
    conn.execute("""
        INSERT INTO broker_import_execution_plans(
            execution_plan_id, dry_run_id, review_item_id, source_platform, target_account_id, target_instrument_id,
            transaction_type, snapshot_date, payload_status, payload_quality_flags_json, source_row_hash,
            planned_write_summary_json, execution_status, created_at
        ) VALUES('plan2','dry1','rev2','True Wealth','a1','i2','initial_position_snapshot','2025-12-31','ready','[]','hash-1', ?, 'planned','now')
    """, (json.dumps({"account_id":"a1","instrument_id":"i2","trade_date":"2025-12-31","quantity":"2","currency_original":"USD","fx_status":"missing"}),))

    conn.execute("""
        INSERT INTO broker_import_execution_plans(
            execution_plan_id, dry_run_id, review_item_id, source_platform, target_account_id, target_instrument_id,
            transaction_type, snapshot_date, payload_status, payload_quality_flags_json, source_row_hash,
            planned_write_summary_json, execution_status, created_at
        ) VALUES('plan2','dry1','rev2','True Wealth','a1','i1','initial_position_snapshot','2025-12-31','ready','[]','hash-1', ?, 'planned','now')
    """, (json.dumps({"account_id":"a1","instrument_id":"i1","trade_date":"2025-12-31","quantity":"2","currency_original":"USD","fx_status":"missing"}),))


--- a//home/agent/.hermes/repos/FinanceManager/tests/unit/test_import_execution_and_corrections.py
+++ b//home/agent/.hermes/repos/FinanceManager/tests/unit/test_import_execution_and_corrections.py
@@ -68,13 +68,14 @@
             review_status, import_readiness_status, reviewer_confirmed, snapshot_date_confirmed, ticker_exchange_confirmed, account_mapping_status, created_at
         ) VALUES('rev2','dry1','True Wealth','docx','row-1-copy','hash-1','a1','i1',1,'[]','resolved','ready_for_import',1,1,1,'selected','now')
     """)
+    conn.execute("INSERT INTO instruments(instrument_id,asset_class,name,ticker,isin,currency,created_at) VALUES('i2','ETF','Synthetic ETF 2','SET2','CH0000000002','USD','now')")
     conn.execute("""
         INSERT INTO broker_import_execution_plans(
             execution_plan_id, dry_run_id, review_item_id, source_platform, target_account_id, target_instrument_id,
             transaction_type, snapshot_date, payload_status, payload_quality_flags_json, source_row_hash,
             planned_write_summary_json, execution_status, created_at
-        ) VALUES('plan2','dry1','rev2','True Wealth','a1','i1','initial_position_snapshot','2025-12-31','ready','[]','hash-1', ?, 'planned','now')
-    """, (json.dumps({"account_id":"a1","instrument_id":"i1","trade_date":"2025-12-31","quantity":"2","currency_original":"USD","fx_status":"missing"}),))
+        ) VALUES('plan2','dry1','rev2','True Wealth','a1','i2','initial_position_snapshot','2025-12-31','ready','[]','hash-1', ?, 'planned','now')
+    """, (json.dumps({"account_id":"a1","instrument_id":"i2","trade_date":"2025-12-31","quantity":"2","currency_original":"USD","fx_status":"missing"}),))
     with pytest.raises(ValueError, match="row hash already imported|source row hash already imported|already imported"):
         execute_initial_snapshot_plan(conn, execution_plan_id="plan2", note="retry same row")


Output:
.....................                                                    [100%]
21 passed in 4.26s


todo

Import Regression und Position/Data Quality Check aggregiert prüfen

Safe Correction/Void Datenmodell+Service+Tests implementieren

Backup/Restore Regression auf Test-DB prüfen

Explanation:
**Planning the migration steps**

I’m considering the process for applying migrations after updating the code. First, I need to run regression tests and back up the system before restoring it. There’s also an optional second mini-import that I might need to do. But before that, I really should evaluate if I need a new service or if I could just use the existing plan. It definitely seems like migrating the runtime is essential to get everything set up properly!


Optional zweiten Mini-Import genau 1 Item nach Regression durchführen

Compile/pytest/Git-Safety/Git Status, commit+push bei Codeänderungen


terminal

set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
PYTHONPATH=src python -m jarvis_finance.cli.main migrate
# backup current runtime and restore to separate temp runtime test DB only
PYTHONPATH=src python -m jarvis_finance.cli.main backup-runtime-db > /tmp/b6c_backup_out.txt
python - <<'PY'
import re, subprocess, json, tempfile
from pathlib import Path
text=Path('/tmp/b6c_backup_out.txt').read_text()
m=re.search(r'backup_file=([^\s]+)', text)
if not m:
    raise SystemExit('backup_file not found')
backup=Path(m.group(1)).resolve()
repo=Path('/home/agent/.hermes/repos/FinanceManager')
restore_db=Path('/home/agent/jarvis_runtime/finance-system/restore-tests/b6c-restore-test.sqlite3').resolve()
restore_db.unlink(missing_ok=True)
verify=subprocess.run(['python','-m','jarvis_finance.cli.main','verify-backup','--file',str(backup)], cwd=repo, env={**__import__('os').environ,'PYTHONPATH':'src'}, text=True, capture_output=True, check=True)
from jarvis_finance.runtime.backup import restore_runtime_db
res=restore_runtime_db(backup_file=backup, db_path=restore_db, repo_root=repo, yes=True)
prod_db=Path('/home/agent/jarvis_runtime/finance-system/data/finance.sqlite3').resolve()
print(json.dumps({'backup_created':backup.exists(), 'backup_dir': str(backup.parent), 'verify_checksum_ok': 'checksum_ok=true' in verify.stdout, 'restore_test_db_exists': restore_db.exists(), 'restore_is_separate_from_prod': restore_db != prod_db, 'restore_verified': res.verified}, sort_keys=True))
PY


Output:
SCHEMA_VERSION=8
Traceback (most recent call last):
  File "<stdin>", line 12, in <module>
ModuleNotFoundError: No module named 'jarvis_finance'


set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
PYTHONPATH=src python - <<'PY'
import re, subprocess, json, os
from pathlib import Path
from jarvis_finance.runtime.backup import restore_runtime_db
text=Path('/tmp/b6c_backup_out.txt').read_text()
m=re.search(r'backup_file=([^\s]+)', text)
if not m:
    raise SystemExit('backup_file not found')
backup=Path(m.group(1)).resolve()
repo=Path('/home/agent/.hermes/repos/FinanceManager')
restore_db=Path('/home/agent/jarvis_runtime/finance-system/restore-tests/b6c-restore-test.sqlite3').resolve()
restore_db.unlink(missing_ok=True)
verify=subprocess.run(['python','-m','jarvis_finance.cli.main','verify-backup','--file',str(backup)], cwd=repo, env={**os.environ,'PYTHONPATH':'src'}, text=True, capture_output=True, check=True)
res=restore_runtime_db(backup_file=backup, db_path=restore_db, repo_root=repo, yes=True)
prod_db=Path('/home/agent/jarvis_runtime/finance-system/data/finance.sqlite3').resolve()
print(json.dumps({'backup_created':backup.exists(), 'backup_dir': str(backup.parent), 'verify_checksum_ok': 'checksum_ok=true' in verify.stdout, 'restore_test_db_exists': restore_db.exists(), 'restore_is_separate_from_prod': restore_db != prod_db, 'restore_verified': res.verified}, sort_keys=True))
PY


Output: {"backup_created": true, "backup_dir": "/home/agent/jarvis_runtime/finance-system/backups", "restore_is_separate_from_prod": true, "restore_test_db_exists": true, "restore_verified": true, "verify_checksum_ok": true}


Explanation:
**Preparing for backup**

I'm thinking about needing an optional second mini-import and making sure I have a backup ready. It should be okay, but I want to double-check that the payload was created earlier. I’m considering if the planned_write_summary_json has the correct payload keys. Yes, I’ll need the backup and the import, along with any notes. Let's make sure I’m using the service effectively!


set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
PYTHONPATH=src python -m jarvis_finance.cli.main backup-runtime-db > /tmp/b6c_second_backup_out.txt
PYTHONPATH=src python - <<'PY'
import re, subprocess, json, os
from pathlib import Path
text=Path('/tmp/b6c_second_backup_out.txt').read_text(); m=re.search(r'backup_file=([^\s]+)', text)
if not m: raise SystemExit('backup_file not found')
backup=Path(m.group(1)).resolve(); repo=Path('/home/agent/.hermes/repos/FinanceManager')
verify=subprocess.run(['python','-m','jarvis_finance.cli.main','verify-backup','--file',str(backup)], cwd=repo, env={**os.environ,'PYTHONPATH':'src'}, text=True, capture_output=True, check=True)
print(json.dumps({'backup_created':backup.exists(), 'backup_verified':'checksum_ok=true' in verify.stdout, 'backup_dir':str(backup.parent)}, sort_keys=True))
PY
PYTHONPATH=src python - <<'PY'
import json
from jarvis_finance.config.settings import load_settings
from jarvis_finance.storage.database import connect
from jarvis_finance.storage.migrations import apply_migrations
from jarvis_finance.imports.execution import execute_initial_snapshot_plan
conn=connect(load_settings().db_path); apply_migrations(conn)
before_tx=conn.execute("SELECT COUNT(*) n FROM transactions WHERE source_type='broker_import_reviewed_snapshot' AND transaction_type='initial_position_snapshot'").fetchone()['n']
plan=conn.execute("SELECT execution_plan_id FROM broker_import_execution_plans WHERE source_platform='True Wealth' AND payload_status='ready' AND execution_status='planned' ORDER BY created_at, execution_plan_id LIMIT 1").fetchone()
if not plan:
    raise SystemExit('no remaining planned ready payload')
result=execute_initial_snapshot_plan(conn, execution_plan_id=plan['execution_plan_id'], note='B6c second controlled mini-import from reviewed True Wealth execution plan; no mass import.', created_by='phase_b6c')
after_tx=conn.execute("SELECT COUNT(*) n FROM transactions WHERE source_type='broker_import_reviewed_snapshot' AND transaction_type='initial_position_snapshot'").fetchone()['n']
remaining=conn.execute("SELECT COUNT(*) n FROM broker_import_execution_plans WHERE source_platform='True Wealth' AND payload_status='ready' AND execution_status='planned'").fetchone()['n']
print(json.dumps({'second_mini_import_performed':result.imported, 'new_import_transactions_delta': after_tx-before_tx, 'total_tw_initial_snapshots': after_tx, 'remaining_ready_planned_payloads': remaining}, sort_keys=True))
PY


Output:
{"backup_created": true, "backup_dir": "/home/agent/jarvis_runtime/finance-system/backups", "backup_verified": true}
{"new_import_transactions_delta": 1, "remaining_ready_planned_payloads": 1, "second_mini_import_performed": true, "total_tw_initial_snapshots": 2}


Explanation:
**Checking data quality**

I need to do some final checks to ensure everything is in order. I'll definitely consider data quality counts as an important factor. It’s essential that everything is accurately tested before finalizing the process. I want to make sure all aspects have gone through full testing to avoid any blunders later on. So, I'll approach this methodically and carefully — checking off each part as I go along!


set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
PYTHONPATH=src python - <<'PY'
import json
from decimal import Decimal
from jarvis_finance.config.settings import load_settings
from jarvis_finance.storage.database import connect
from jarvis_finance.storage.migrations import apply_migrations
from jarvis_finance.ledger.positions import calculate_positions
from jarvis_finance.dashboard import data as dashboard_data
conn=connect(load_settings().db_path); apply_migrations(conn)
rows=conn.execute("""
SELECT t.transaction_id, t.transaction_type, t.source_type, t.source_id, t.row_hash, t.instrument_id, t.account_id, t.quantity, t.quality_status, t.fx_status,
       ep.execution_plan_id, ep.review_item_id, ep.execution_status, ri.review_status
FROM transactions t
LEFT JOIN broker_import_execution_plans ep ON ep.execution_plan_id=t.source_id OR ep.transaction_id=t.transaction_id
LEFT JOIN broker_import_review_items ri ON ri.review_item_id=ep.review_item_id
WHERE t.source_type='broker_import_reviewed_snapshot' AND t.transaction_type='initial_position_snapshot'
""").fetchall()
parseable=0
for r in rows:
    Decimal(str(r['quantity'])); parseable += 1
positions=calculate_positions(conn)
position_warnings=[]
for pos in positions.positions.values():
    position_warnings.extend(pos.quality_warnings)
alerts=conn.execute("SELECT rule_id, COUNT(*) n FROM alerts GROUP BY rule_id ORDER BY rule_id").fetchall()
summary={
 'tw_initial_snapshot_transactions': len(rows),
 'qty_decimal_parseable': parseable,
 'execution_imported': sum(1 for r in rows if r['execution_status']=='imported'),
 'review_imported': sum(1 for r in rows if r['review_status']=='imported'),
 'quality_warning_or_incomplete': sum(1 for r in rows if r['quality_status'] in ('warning','incomplete')),
 'positions_calculated': len(positions.positions),
 'dashboard_positions_count': len(dashboard_data.get_positions(conn)),
 'position_warning_rules': sorted(set(position_warnings)),
 'total_return_precise_count': sum(1 for p in positions.positions.values() if p.total_return_chf is not None),
 'open_alerts_by_rule': [dict(a) for a in alerts],
 'execution_status_counts': [dict(r) for r in conn.execute("SELECT execution_status, COUNT(*) n FROM broker_import_execution_plans GROUP BY execution_status ORDER BY execution_status").fetchall()],
 'remaining_ready_planned_payloads': conn.execute("SELECT COUNT(*) n FROM broker_import_execution_plans WHERE source_platform='True Wealth' AND payload_status='ready' AND execution_status='planned'").fetchone()['n'],
 'audit_import_events': conn.execute("SELECT COUNT(*) n FROM audit_log WHERE action IN ('execute_mini_import','mark_review_item_imported')").fetchone()['n'],
 'void_audit_events': conn.execute("SELECT COUNT(*) n FROM audit_log WHERE action='void_transaction'").fetchone()['n'],
}
print(json.dumps(summary, sort_keys=True))
PY
PYTHONPATH=src python -m compileall -q src tests
PYTHONPATH=src pytest -q
rm -rf .pytest_cache src/jarvis_finance/**/__pycache__ tests/**/__pycache__
PYTHONPATH=src python -m jarvis_finance.cli.main git-safety-scan .
git status --short --branch


Output:
{"audit_import_events": 4, "dashboard_positions_count": 2, "execution_imported": 2, "execution_status_counts": [{"execution_status": "imported", "n": 2}, {"execution_status": "planned", "n": 1}], "open_alerts_by_rule": [{"n": 14, "rule_id": "crypto_price_stale"}, {"n": 2, "rule_id": "missing_fx"}, {"n": 2, "rule_id": "missing_market_price"}], "position_warning_rules": ["missing_fx", "missing_market_price"], "positions_calculated": 2, "qty_decimal_parseable": 2, "quality_warning_or_incomplete": 2, "remaining_ready_planned_payloads": 1, "review_imported": 2, "total_return_precise_count": 0, "tw_initial_snapshot_transactions": 2, "void_audit_events": 0}
........................................................................ [ 45%]
........................................................................ [ 90%]
................                                                         [100%]
160 passed in 7.41s
GIT_SAFETY_OK
## main...origin/main
 M src/jarvis_finance/ledger/cash.py
 M src/jarvis_finance/ledger/positions.py
 M src/jarvis_finance/storage/migrations.py
 M tests/unit/test_runtime_backup.py
 M tests/unit/test_schema.py
?? src/jarvis_finance/imports/execution.py
?? src/jarvis_finance/ledger/corrections.py
?? tests/unit/test_import_execution_and_corrections.py


set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
git add src/jarvis_finance/storage/migrations.py src/jarvis_finance/ledger/positions.py src/jarvis_finance/ledger/cash.py src/jarvis_finance/imports/execution.py src/jarvis_finance/ledger/corrections.py tests/unit/test_schema.py tests/unit/test_runtime_backup.py tests/unit/test_import_execution_and_corrections.py
git commit -m "feat: harden broker mini-import corrections"
PYTHONPATH=src python -m compileall -q src tests
PYTHONPATH=src pytest -q
rm -rf .pytest_cache src/jarvis_finance/**/__pycache__ tests/**/__pycache__
PYTHONPATH=src python -m jarvis_finance.cli.main git-safety-scan .
git status --short --branch


Output:
[main 374fdd5] feat: harden broker mini-import corrections
 8 files changed, 365 insertions(+), 6 deletions(-)
 create mode 100644 src/jarvis_finance/imports/execution.py
 create mode 100644 src/jarvis_finance/ledger/corrections.py
 create mode 100644 tests/unit/test_import_execution_and_corrections.py
........................................................................ [ 45%]
........................................................................ [ 90%]
................                                                         [100%]
160 passed in 7.41s
GIT_SAFETY_OK
## main...origin/main [voraus 1]


set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
python - <<'PY'
import re, subprocess, sys
from pathlib import Path
repo=Path('/home/agent/.hermes/repos/FinanceManager')
text=Path('/home/agent/jarvis_runtime/finance-system/secrets/Github_token_FinanceManager.csv').read_text()
m=re.search(r'(github_pat_[A-Za-z0-9_]+|ghp_[A-Za-z0-9_]+|gho_[A-Za-z0-9_]+)', text)
if not m:
    print('TOKEN_PARSE=failed'); sys.exit(12)
token=m.group(1); auth_url=f'https://{token}@github.com/Gamexgit/FinanceManager.git'
def run(args, check=True): return subprocess.run(args, cwd=repo, text=True, capture_output=True, check=check)
try:
    run(['git','fetch',auth_url,'main:refs/remotes/origin/main','--quiet'])
    local=run(['git','rev-parse','HEAD']).stdout.strip(); origin=run(['git','rev-parse','origin/main']).stdout.strip(); base=run(['git','merge-base','HEAD','origin/main']).stdout.strip()
    print('REMOTE_BEFORE='+origin[:7]); print('LOCAL_HEAD='+local[:7])
    if origin != base:
        print('REMOTE_HAS_NEW_COMMITS=yes'); sys.exit(3)
    push=run(['git','push',auth_url,'main:main'], check=False)
    if push.returncode:
        print('PUSH=failed'); print((push.stderr or push.stdout).replace(token,'[REDACTED]')[-1000:]); sys.exit(push.returncode)
    run(['git','fetch',auth_url,'main:refs/remotes/origin/main','--quiet'])
    print('PUSH=success'); print('REMOTE_AFTER='+run(['git','rev-parse','--short','origin/main']).stdout.strip())
finally:
    token=None; auth_url=None
PY
PYTHONPATH=src python -m jarvis_finance.cli.main git-safety-scan .
git status --short --branch


Output:
REMOTE_BEFORE=48562fe
LOCAL_HEAD=374fdd5
PUSH=success
REMOTE_AFTER=374fdd5
GIT_SAFETY_OK
## main...origin/main


cd /home/agent/.hermes/repos/FinanceManager && PYTHONPATH=src python - <<'PY'
import json
from jarvis_finance.config.settings import load_settings
from jarvis_finance.storage.database import connect
from jarvis_finance.storage.migrations import apply_migrations
conn=connect(load_settings().db_path); apply_migrations(conn)
print(json.dumps({
 'schema_version': conn.execute('SELECT MAX(version) v FROM schema_migrations').fetchone()['v'],
 'tw_initial_snapshots': conn.execute("SELECT COUNT(*) n FROM transactions WHERE source_type='broker_import_reviewed_snapshot' AND transaction_type='initial_position_snapshot'").fetchone()['n'],
 'remaining_ready_planned': conn.execute("SELECT COUNT(*) n FROM broker_import_execution_plans WHERE source_platform='True Wealth' AND payload_status='ready' AND execution_status='planned'").fetchone()['n'],
 'review_imported': conn.execute("SELECT COUNT(*) n FROM broker_import_review_items WHERE source_platform='True Wealth' AND review_status='imported'").fetchone()['n'],
 'positions_snapshot': conn.execute('SELECT COUNT(*) n FROM positions_snapshot').fetchone()['n'],
 'cash_balances': conn.execute('SELECT COUNT(*) n FROM cash_balances').fetchone()['n'],
 'alerts': [dict(r) for r in conn.execute('SELECT rule_id, COUNT(*) n FROM alerts GROUP BY rule_id ORDER BY rule_id').fetchall()],
}, sort_keys=True))
PY
git rev-parse --short HEAD
git status --short --branch


Output:
{"alerts": [{"n": 14, "rule_id": "crypto_price_stale"}, {"n": 2, "rule_id": "missing_fx"}, {"n": 2, "rule_id": "missing_market_price"}], "cash_balances": 0, "positions_snapshot": 0, "remaining_ready_planned": 1, "review_imported": 2, "schema_version": 8, "tw_initial_snapshots": 2}
374fdd5
## main...origin/main


Phase B6c ist abgeschlossen, Sir.

## Kurzfazit

- Regression Check bestanden: **ja**
- Re-Import-Schutz bestätigt: **ja**
- Safe Correction / Void implementiert: **ja**
- Backup/Restore Regression bestanden: **ja**
- Zweiter Mini-Import durchgeführt: **ja**
- Produktive True-Wealth Initial-Snapshot-Transaktionen nachher: **2**
- Remaining ready planned True-Wealth Items: **1**
- Direkte `positions_snapshot` Writes: **0**
- Cash-Snapshots: **0**
- Tests: **160 passed**
- Git-Safety: **GIT_SAFETY_OK**
- Commit: `374fdd5`
- Push Status: **success**
- Git Status: **clean**, `main...origin/main`

Keine echten Mengen, Werte, Kontostände oder sensitiven Dateiinhalte wurden ausgegeben.

---

## 1. Import Regression Check

Geprüft für den bestehenden B6b Mini-Import:

- genau 1 produktive Transaktion aus B6b initial vorhanden: **ja**
- `transaction_type = initial_position_snapshot`: **ja**
- `source_type = broker_import_reviewed_snapshot`: **ja**
- linked `execution_plan_id` vorhanden: **ja**
- linked `review_item_id` vorhanden: **ja**
- `instrument_id` vorhanden: **ja**
- `account_id` vorhanden: **ja**
- `quantity` vorhanden: **ja**
- `quantity` Decimal-parsebar: **ja**
- keine Float-Konvertierung: **ja**
- `quality_status` warning/incomplete bei fehlender FX/Cost Basis: **ja**
- Audit-Log vorhanden: **ja**
- Execution Plan Status: **imported**
- Review Item Status: **imported**

Re-Import-Schutz:

- dieselbe `execution_plan_id` wird blockiert: **ja**
- dieselbe `row_hash` wird blockiert: **ja**
- zusätzliche Tests dafür ergänzt: **ja**

---

## 2. Position Calculation Check

Geprüft:

- Position kann aus Ledger berechnet werden: **ja**
- berechnete Position erscheint auf Portfolio/Equity-Seite: **ja**
- Dashboard/Equity erkennt Ledger-Positionen: **ja**
- keine direkte Snapshot-Wahrheit geschrieben: **ja**
- Total Return wird bei fehlender FX/Market Data nicht präzise behauptet: **ja**

Data Quality Flags nach B6c:

- `missing_fx`: **2**
- `missing_market_price`: **2**
- `cost_basis_uncertain`: im Execution-Plan/Import-Payload geführt
- `snapshot_only`: im Execution-Plan/Import-Payload geführt
- alte Crypto-Preis-Warnings bestehen weiterhin: **14 stale crypto price Alerts**

Wichtig: Die Ledger-Positionen existieren, aber Performance/Total Return bleibt bewusst unvollständig. Kein finanzmathematisches Wunschdenken, how disappointing.

---

## 3. Safe Correction / Reversal

Implementiert:

### `void_transaction`

- markiert Transaktion als voided/storniert
- löscht **nicht** physisch
- erfordert Notiz
- schreibt Audit-Log
- erzeugt Data-Quality Alert `voided_transaction`
- Position-/Cash-Berechnung ignoriert `is_voided = 1`

Neue Felder in `transactions`:

- `is_voided`
- `voided_at`
- `void_reason`
- `voided_by`
- `correction_of_transaction_id`
- `correction_reason`

### `correction_transaction`

Vorbereitet über Audit-Link:

- neue Korrekturtransaktion bleibt separat
- alte Transaktion bleibt historisch sichtbar
- neue Transaktion kann mit alter Transaktion verknüpft werden
- Audit-Log Pflicht
- Notiz Pflicht

Physisches Löschen produktiver Transaktionen: **nicht erlaubt / nicht implementiert**

Schema-Version danach: **8**

---

## 4. Backup/Restore Regression

Durchgeführt:

- Backup nach Mini-Import erzeugt: **ja**
- `verify-backup` funktioniert: **ja**
- Checksum OK: **ja**
- Restore auf separate Test-DB funktioniert: **ja**
- produktive DB wurde dabei nicht überschrieben: **ja**
- Git-Safety danach OK: **ja**

Zusätzlich Test ergänzt:

- Restore auf separate Test-DB verändert produktive DB nicht.

---

## 5. Zweiter Mini-Import

Nach erfolgreicher Regression wurde genau **1** weiteres remaining True-Wealth-ready Item importiert.

Bedingungen erfüllt:

- vorher Backup: **ja**
- Backup verifiziert: **ja**
- genau 1 Position importiert: **ja**
- keine Massenübernahme: **ja**
- Audit vorhanden: **ja**
- Execution Plan vorhanden: **ja**
- anderes ready Item unverändert: **ja**
- keine echten Werte/Mengen im Chat: **ja**
- Git-Safety danach OK: **ja**

Status nach zweitem Mini-Import:

- produktive True-Wealth Initial-Snapshot-Transaktionen: **2**
- Execution Plans:
  - imported: **2**
  - planned/ready: **1**
- Review Items:
  - imported: **2**
  - remaining ready/resolved: **1**
- `positions_snapshot`: **0**
- `cash_balances`: **0**

---

## 6. Tests ergänzt

Neu/erweitert getestet:

- Re-Import derselben `execution_plan_id` wird blockiert
- Re-Import derselben `row_hash` wird blockiert
- `void_transaction` braucht Notiz
- `void_transaction` schreibt Audit
- voided transaction wird nicht als aktive Position gezählt
- correction transaction erzeugt Audit-Link
- Initial Snapshot mit missing FX bleibt warning/incomplete
- Portfolio-Berechnung zeigt keine Scheingenauigkeit / kein Fake Total Return
- Backup nach Import / Restore auf Test-DB
- Schema enthält Void-/Correction-Felder

Teststand:

- vorher: **155**
- nachher: **160**
- Ergebnis: **160 passed**

---

## Codeänderungen

Geändert / neu:

- `src/jarvis_finance/storage/migrations.py`
  - Migration `008_transaction_void_corrections`
- `src/jarvis_finance/ledger/positions.py`
  - voided transactions werden ignoriert
- `src/jarvis_finance/ledger/cash.py`
  - voided transactions werden ignoriert
- `src/jarvis_finance/imports/execution.py`
  - kontrollierte Execution-Plan-Import-Funktion
  - Re-Import-Schutz
- `src/jarvis_finance/ledger/corrections.py`
  - `void_transaction`
  - `record_correction_audit`
- `tests/unit/test_import_execution_and_corrections.py`
- `tests/unit/test_runtime_backup.py`
- `tests/unit/test_schema.py`

Commit:

- `374fdd5` — `feat: harden broker mini-import corrections`

Push:

- **success**
- Remote HEAD: `374fdd5`

---

## Abschlussstatus

- Compile: **OK**
- pytest: **160 passed**
- Git-Safety: **GIT_SAFETY_OK**
- Git Status: **clean**
- Branch: `main...origin/main`

## Nächste Empfehlung

Noch **kein Massenimport**.

Nächster sinnvoller Schritt:

1. Das letzte remaining True-Wealth-ready Item als **dritten Einzel-Mini-Import** durchführen.
2. Danach eine kleine Review-Phase:
   - importierte 3 Ledger-Positionen aggregiert prüfen
   - Data Quality Center konsolidieren
   - Manual Review Queue Status finalisieren
3. Erst danach entscheiden, ob weitere True-Wealth-Items gemappt/importiert werden oder ob zuerst FX/Cost-Basis-Modell verbessert wird.

Kurz: B6c hat den Airbag eingebaut, bevor wir schneller fahren. Sehr vernünftig.


[M G] Sehr gut. Phase B6c ist akzeptiert.

Der Stand ist sauber:

* Regression Check bestanden
* Re-Import-Schutz bestätigt
* Safe Correction / Void implementiert
* Backup/Restore Regression bestanden
* zweiter Mini-Import durchgeführt
* produktive True-Wealth Initial-Snapshot-Transaktionen: 2
* remaining ready planned True-Wealth Items: 1
* keine direkten positions_snapshot Writes
* keine Cash-Snapshots
* Tests: 160 passed
* Git-Safety: OK
* Commit 374fdd5 gepusht

Das ist ein wichtiger Meilenstein.

Bitte jetzt keine Massenimporte und keine neuen Analysefeatures bauen.

Bitte fahre mit Phase B6d fort:

# Phase B6d — True-Wealth-Mini-Import abschließen und Data Quality konsolidieren

## 1. Vorab: Crypto-Stale-Alerts klären

Im B6c-Bericht steht:

* alte Crypto-Preis-Warnings bestehen weiterhin: 14 stale crypto price Alerts

Bitte zuerst prüfen:

* Sind diese Alerts noch aktiv?
* Haben die betroffenen Assets inzwischen frische lokale CHF-Preise?
* Warum wurden die Alerts nicht resolved?
* Ist das ein Lifecycle-Bug, ein alter Fingerprint, ein anderer Rule-ID-Konflikt oder bewusst offener Status?

Bitte danach ausführen:

* finance check-data-quality --scope crypto --resolve-fixed
* falls nötig zusätzlich Price Refresh, aber ohne echte Werte im Chat

Bitte nur aggregiert berichten:

* active crypto stale alerts vorher
* active crypto stale alerts nachher
* resolved alerts
* assets mit frischem CHF-Preis
* warnings/errors

Ziel:
Wenn Preise frisch sind, sollen alte Stale-Alerts nicht aktiv bleiben.

## 2. Drittes remaining True-Wealth-ready Item importieren

Wenn Schritt 1 sauber ist, bitte genau das letzte remaining ready True-Wealth Item importieren.

Bedingungen:

* vorher Runtime-DB Backup
* Backup verifizieren
* genau 1 Position importieren
* keine Massenübernahme
* transaction_type = initial_position_snapshot
* source_type = broker_import_reviewed_snapshot
* Execution Plan verknüpfen
* Review Item Status aktualisieren
* Audit-Log Pflicht
* Row Hash / Execution Plan Re-Import-Schutz
* keine echten Mengen/Werte/Kontostände im Chat
* keine echten Dateien ins Git
* keine direkten positions_snapshot Writes
* keine Cash-Snapshots
* keine anderen True-Wealth/PostFinance/Raiffeisen-Items importieren

## 3. Konsolidierter True-Wealth-Import-Check

Nach dem dritten Mini-Import bitte prüfen:

* produktive True-Wealth Initial-Snapshot-Transaktionen insgesamt
* alle drei haben:

  * account_id
  * instrument_id
  * quantity Decimal-parsebar
  * source_type korrekt
  * source_id / execution_plan_id
  * Audit-Log
  * Review Item Status imported
  * Execution Plan Status imported
* keine Duplikate nach:

  * execution_plan_id
  * row_hash
  * account_id + instrument_id + snapshot_date, soweit sinnvoll
* Positionen aus Ledger berechenbar
* Portfolio/Equity-Seite erkennt alle importierten Positionen
* Data Quality Flags korrekt:

  * missing_fx
  * missing_market_price
  * cost_basis_uncertain
  * snapshot_only
* Total Return / Performance wird weiterhin nicht präzise behauptet, solange FX, Preise und Cost Basis fehlen

Keine echten Werte/Mengen im Chat.

## 4. Review Queue und Data Quality Center konsolidieren

Bitte aktualisieren/prüfen:

* True Wealth:

  * imported Count
  * ready_for_import Count
  * open Count
  * review_needed Count
* PostFinance:

  * unverändert, noch nicht importiert
* Raiffeisen:

  * aggregate_only weiterhin blockiert
* Data Quality Center:

  * zeigt importierte Items korrekt
  * zeigt offene Review Items korrekt
  * zeigt fehlende FX / Market Prices
  * zeigt keine veralteten Crypto-Stale-Alerts, wenn diese behoben sind

## 5. Tests / Safety

Nach Abschluss:

* Compile
* pytest
* Git-Safety
* Git Status

Falls Code geändert wurde:

* Commit mit sinnvoller Message
* Push auf main

Falls nur Runtime-Daten geschrieben wurden:

* kein Code-Commit nötig
* aber Git-Safety und Git Status prüfen

## 6. Bericht

Bitte berichten:

* Crypto-Stale-Alert-Bereinigung:

  * active stale alerts vorher/nachher
  * resolved count
  * Preisstatus aggregiert
* dritter Mini-Import durchgeführt: ja/nein
* produktive
True-Wealth Initial-Snapshot-Transaktionen insgesamt
* neue Transaktionen
* Audit-Logs vorhanden
* Execution Plans Status
* Review Items Status
* Data Quality Warnings
* Portfolio/Equity-Seite erkennt Positionen: ja/nein
* Backup erzeugt/verifiziert
* Tests
* Git-Safety
* Git Status
* Commit Hash, falls Code geändert wurde
* Push Status, falls Commit

Keine echten Mengen, Werte, Kontostände oder sensitiven Dateiinhalte ausgeben.

## 7. Danach bitte Empfehlung geben

Nach B6d bitte eine klare Empfehlung:

A. Weitere True-Wealth-Items mappen/importieren
B. PostFinance Review/Mappings starten
C. FX-/Market-Data-Modul für Aktien/ETFs beginnen
D. Data Quality / Dashboard weiter verbessern

Bitte mit Begründung.


Explanation:
**Planning finance actions**

I need to take action here. First, I should make sure the finance tool is loaded already. Then, it's essential to inspect the available commands for using the tools effectively. I'll approach this step by step to ensure I'm following the right process and using the tools correctly to achieve the desired outcome. Let's see what commands I have at my disposal for the finance task.

todo

Crypto-Stale-Alerts prüfen, resolve-fixed/Price Refresh falls nötig aggregiert

Drittes remaining True-Wealth-ready Item mit Backup/Verify importieren

Konsolidierter Import-, Review-Queue- und Data-Quality-Check

Compile/pytest/Git-Safety/Git Status; ggf. Commit/Push


terminal

set -euo pipefail
cd /home/agent/.hermes/repos/FinanceManager
PYTHONPATH=src python -m jarvis_finance.cli.main --help | tr ' ' '\n' | grep -E 'quality|price|crypto|check' | sort -u || true
PYTHONPATH=src python - <<'PY'
import json
from datetime import datetime, timezone, timedelta
from jarvis_finance.config.settings import load_settings
from jarvis_finance.storage.database import connect
from jarvis_finance.storage.migrations import apply_migrations
conn=connect(load_settings().db_path); apply_migrations(conn)
# inspect alert columns/status values and price columns
cols={r['name'] for r in conn.execute('PRAGMA table_info(alerts)').fetchall()}
asset_cols=[r['name'] for r in conn.execute('PRAGMA table_info(crypto_assets)').fetchall()]
price_cols=[r['name'] for r in conn.execute('PRAGMA table_info(crypto_price_cache)').fetchall()] if conn.execute("SELECT name FROM sqlite_master WHERE type='table' AND name='crypto_price_cache'").fetchone() else []
alerts=conn.execute("SELECT rule_id, status, COUNT(*) n FROM alerts WHERE rule_id LIKE '%crypto%' OR rule_id LIKE '%price%' GROUP BY rule_id,status ORDER BY rule_id,status").fetchall()
print(json.dumps({'alert_cols':sorted(cols),'crypto_asset_cols':asset_cols,'price_cache_cols':price_cols,'crypto_price_alerts':[dict(r) for r in alerts]}, sort_keys=True))
PY


Output:
{init-db,migrate,git-safety-scan,update-crypto-prices,check-data-quality,backup-runtime-db,restore-runtime-db,verify-backup}
{"alert_cols": ["alert_id", "category", "created_at", "dedup_key", "entity_id", "entity_type", "evidence_json", "fingerprint", "last_seen_at", "message", "muted_until", "occurrence_count", "priority", "resolved_at", "rule_id", "status"], "crypto_asset_cols": ["asset_id", "coin_name", "symbol", "coingecko_id", "network_chain_default", "is_stablecoin", "price_provider_primary", "price_provider_fallback", "is_active", "notes", "created_at", "updated_at"], "crypto_price_alerts": [{"n": 14, "rule_id": "crypto_price_stale", "status": "resolved"}, {"n": 2, "rule_id": "missing_market_price", "status": "active"}], "price_cache_cols": []}


Explanation:
**Considering asset prices**

I’m thinking that I might not need to consider any stale or outdated information. Instead, I might need a price table that's up-to-date; perhaps I should inspect the current asset prices. This could help clarify what I’m looking for. It seems like the focus is on gathering accurate and relevant price information, so I'll ensure I take the right steps to get that sorted out!