docs: update README, runbook, and steering files for today's changes

- README: added AI agent management section, updated paper trading
  description (no manual capital controls, broker-synced reset)
- Steering: migration numbers updated to 027 (next: 028), added
  trading engine endpoint, ruff pinning and isort config notes
- Runbook: already had reset/Alpaca sections from earlier commits
This commit is contained in:
Celes Renata
2026-04-17 04:37:44 +00:00
parent fde819ec09
commit 0f06cf8971
3 changed files with 14 additions and 4 deletions
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@@ -22,7 +22,9 @@
- Frontend: Vitest + MSW (Mock Service Worker) for deterministic API mocking, tests in `frontend/src/test/` - Frontend: Vitest + MSW (Mock Service Worker) for deterministic API mocking, tests in `frontend/src/test/`
- Run Python tests: `python -m pytest tests/ -x --tb=short -q` - Run Python tests: `python -m pytest tests/ -x --tb=short -q`
- Run frontend tests: `cd frontend && npx vitest --run` - Run frontend tests: `cd frontend && npx vitest --run`
- Lint Python: `nix-shell -p ruff --run "ruff check services/"` - Lint Python: `nix-shell -p ruff --run "ruff check services/"` (or `.venv/bin/ruff check services/`)
- Ruff is pinned to `ruff==0.15.10` in `requirements.txt` — CI uses the same version
- Ruff config: `ruff.toml` with `known-first-party = ["services"]` for consistent import sorting
- Pre-existing test failures (not regressions): `test_extractor_prompts.py`, `test_extractor_schemas.py`, `test_filings_adapter.py`, `test_ollama_client.py` - Pre-existing test failures (not regressions): `test_extractor_prompts.py`, `test_extractor_schemas.py`, `test_filings_adapter.py`, `test_ollama_client.py`
## CI/CD — GitHub Actions ## CI/CD — GitHub Actions
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@@ -25,6 +25,7 @@ Three-layer signal aggregation engine:
- Dashboard: `https://stonks.celestium.life` - Dashboard: `https://stonks.celestium.life`
- Query API: `https://stonks-api.celestium.life` - Query API: `https://stonks-api.celestium.life`
- Symbol Registry: `https://stonks-registry.celestium.life` - Symbol Registry: `https://stonks-registry.celestium.life`
- Trading Engine: `https://stonks-trading.celestium.life`
- Superset: `https://stonks-dash.celestium.life` - Superset: `https://stonks-dash.celestium.life`
- Trino: `https://stonks-trino.celestium.life` - Trino: `https://stonks-trino.celestium.life`
@@ -72,12 +73,15 @@ When a full reset is needed:
- Ollama: `ollama.ollama-service.svc.cluster.local:11434` (cluster-internal), also at `http://10.1.1.12:2701` (external), GPU: 4070 Ti Super 16GB - Ollama: `ollama.ollama-service.svc.cluster.local:11434` (cluster-internal), also at `http://10.1.1.12:2701` (external), GPU: 4070 Ti Super 16GB
## Database Migrations ## Database Migrations
- Located in `infra/migrations/001_*.sql` through `017_*.sql` - Located in `infra/migrations/001_*.sql` through `027_*.sql`
- Applied automatically by `runmefirst.sh` in sorted order - Applied automatically by `runmefirst.sh` in sorted order
- Next migration number: **018** - Next migration number: **028**
- Key migrations: - Key migrations:
- 016: Global news interpolation (global_events, macro_impact_records, exposure_profiles, trend_projections) - 016: Global news interpolation (global_events, macro_impact_records, exposure_profiles, trend_projections)
- 017: Competitive intelligence (competitor_relationships, competitive_signal_records) - 017: Competitive intelligence (competitor_relationships, competitive_signal_records)
- 024: Trend history time-series table
- 026: AI agents management (ai_agents, agent_performance_log)
- 027: Agent variants (agent_variants table for A/B testing)
## Key Conventions ## Key Conventions
- All services use `services/shared/config.py` for configuration via env vars - All services use `services/shared/config.py` for configuration via env vars
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@@ -77,6 +77,9 @@ Seed data: `python -m services.symbol_registry.seed`
### Autonomous Trading Engine ### Autonomous Trading Engine
Continuous decision loop that polls for actionable recommendations and executes paper trades without manual intervention. Includes confidence-based position sizing (with sample-size-dampened agreement scoring to prevent thin-evidence inflation), dynamic stop-loss/take-profit (ATR-based), circuit breakers (daily loss cap, single-position loss, volatility detection), reserve pool management (auto-siphon from profits), risk tier auto-adjustment (conservative/moderate/aggressive based on trailing performance), portfolio rebalancing (sector and concentration limits), gradual entry (multi-tranche orders), correlation-aware diversification, earnings calendar awareness, portfolio heat management, tax-lot tracking with wash sale detection, performance tracking (Sharpe, drawdown, win rate, profit factor), and backtesting against historical data. Continuous decision loop that polls for actionable recommendations and executes paper trades without manual intervention. Includes confidence-based position sizing (with sample-size-dampened agreement scoring to prevent thin-evidence inflation), dynamic stop-loss/take-profit (ATR-based), circuit breakers (daily loss cap, single-position loss, volatility detection), reserve pool management (auto-siphon from profits), risk tier auto-adjustment (conservative/moderate/aggressive based on trailing performance), portfolio rebalancing (sector and concentration limits), gradual entry (multi-tranche orders), correlation-aware diversification, earnings calendar awareness, portfolio heat management, tax-lot tracking with wash sale detection, performance tracking (Sharpe, drawdown, win rate, profit factor), and backtesting against historical data.
### AI Agent Management
Configurable AI agents (document extractor, event classifier, thesis rewriter) with database-driven model/prompt resolution. 60-second TTL cache for hot-swapping models without restarts. Agent performance logging with variant attribution for future A/B testing support.
### Global News Interpolation ### Global News Interpolation
Macro/geopolitical event ingestion from dedicated sources. Ollama-based classification by impact type, severity, affected regions, and sectors. Company exposure profiles (geographic revenue mix, supply chain regions, commodity dependencies, market position tier) map events to per-company macro impact scores with resilience modifiers. Forward-looking trend projections combine company momentum with macro trajectories. Macro/geopolitical event ingestion from dedicated sources. Ollama-based classification by impact type, severity, affected regions, and sectors. Company exposure profiles (geographic revenue mix, supply chain regions, commodity dependencies, market position tier) map events to per-company macro impact scores with resilience modifiers. Forward-looking trend projections combine company momentum with macro trajectories.
@@ -105,7 +108,8 @@ Historical pattern mining on the platform's own data — how similar catalyst ty
### Paper Trading ### Paper Trading
- Alpaca paper trading integration (3 accounts max per Alpaca owner) - Alpaca paper trading integration (3 accounts max per Alpaca owner)
- Full reset: liquidates broker positions, cancels orders, syncs capital from broker balance - Full reset: liquidates broker positions, cancels orders, clears local DB, syncs capital from broker's actual account balance
- No manual capital controls — engine capital always derived from broker state on reset
- Moderate risk tier default, auto-adjustable - Moderate risk tier default, auto-adjustable
- Full execution audit trail from signal to broker response - Full execution audit trail from signal to broker response
- Operator approval workflow available for live mode - Operator approval workflow available for live mode