Feature 1 - Configurable max_auto_tickers:
- Add max_auto_tickers config key (default 10) with TRADINGAGENTS_MAX_AUTO_TICKERS env override
- Macro synthesis agent accepts max_scan_tickers param, injects exact count into LLM prompt
- ScannerGraph passes config value to create_macro_synthesis()
- Backend engine applies safety cap on scan candidates (portfolio holdings always included)
- Frontend adds Max Tickers number input in params panel, sends max_tickers in auto run body
Feature 2 - Run persistence + phase-level node re-run:
- 2A: ReportStore + MongoReportStore gain save/load_run_meta, save/load_run_events,
list_run_metas methods; runs.py persists to disk in finally block; startup hydration
restores historical runs; lazy event loading on GET /{run_id}
- 2B: Analysts + trader checkpoint save/load methods in both stores; engine saves
checkpoints after pipeline completion alongside complete_report.json
- 2C: GraphSetup gains build_debate_subgraph() and build_risk_subgraph() for partial
re-runs; TradingAgentsGraph exposes debate_graph/risk_graph as lazy properties;
NODE_TO_PHASE mapping + run_pipeline_from_phase() engine method;
POST /api/run/rerun-node endpoint with _append_and_store helper
- 2D: Frontend history popover (loads GET /api/run/, sorts by created_at, click to load);
triggerNodeRerun() calls rerun-node endpoint; handleNodeRerun uses phase-level
re-run when active run is loaded
All 890 existing tests pass (10 skipped).
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
## Summary
- Adds `smart_money_scanner` as a new Phase 1b node that runs sequentially after `sector_scanner`, surfacing institutional footprints via Finviz screeners
- Introduces the **Golden Overlap** strategy in `macro_synthesis`: stocks confirmed by both top-down macro themes and bottom-up Finviz signals are labelled high-conviction
- Fixes model-name badge overflow in AgentGraph (long model IDs like OpenRouter paths were visually spilling into adjacent nodes)
- Completes all documentation: ADR-014, dataflow, architecture, components, glossary, current-state
## Key Decisions (see ADR-014)
- 3 zero-parameter tools (`get_insider_buying_stocks`, `get_unusual_volume_stocks`, `get_breakout_accumulation_stocks`) instead of 1 parameterised tool — prevents LLM hallucinations on string args
- Sequential after `sector_scanner` (not parallel fan-out) — gives access to `sector_performance_report` context and avoids `MAX_TOOL_ROUNDS=5` truncation in market_movers_scanner
- Graceful fallback: `_run_finviz_screen()` catches all exceptions and returns an error string — pipeline never hard-fails on web-scraper failure
- `breakout_accumulation` (52-wk high + 2x vol = O'Neil CAN SLIM institutional signal) replaces `oversold_bounces` (RSI<30 = retail contrarian, not smart money)
## Test Plan
- [x] 6 new mocked tests in `tests/unit/test_scanner_mocked.py` (happy path, empty DF, exception, sort order)
- [x] Fixed `tests/unit/test_scanner_graph.py` — added `smart_money_scanner` mock to compilation test
- [x] 2 pre-existing test failures excluded (verified baseline before changes)
- [x] AgentGraph badge: visually verified truncation with long OpenRouter model identifiers
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Replace supabase-py stubs with working psycopg2 implementation using
Supabase pooler connection string. Implement full business logic in
repository (avg cost basis, cash accounting, trade recording, snapshots).
Add 12 unit tests + 4 integration tests (51 total portfolio tests pass).
Fix cash_pct bug in models.py, update docs for psycopg2 + pooler pattern.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: daily digest consolidation and NotebookLM sync
- Add tradingagents/daily_digest.py: appends timestamped entries from
analyze and scan runs into a single reports/daily/{date}/daily_digest.md
- Add tradingagents/notebook_sync.py: uploads digest to Google NotebookLM
via nlm CLI, deleting the previous version before uploading (opt-in,
skips silently if NOTEBOOK_ID is not set)
- Add get_digest_path() helper to report_paths.py
- Hook both analyze and scan CLI commands to append + sync after each run
- Add NOTEBOOK_ID to .env.example
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* docs: update agent memory for daily digest + NotebookLM sync
Update CURRENT_STATE, ARCHITECTURE, and COMPONENTS context files to
reflect the feat/daily-digest-notebooklm implementation.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix: correct nlm CLI commands and env var name for NotebookLM sync
- Use nlm note list/create/update instead of source list/add/delete
- Parse notes from {"notes": [...]} response structure
- Rename NOTEBOOK_ID -> NOTEBOOKLM_ID in both code and .env.example
- Auto-discover nlm at ~/.local/bin/nlm when not in PATH
- Tested: create on first run, update on subsequent runs
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
* gitignore
* feat: unify report paths under reports/daily/{date}/ hierarchy
All generated artifacts now land under a single reports/ tree:
- reports/daily/{date}/market/ for scan results (was results/macro_scan/)
- reports/daily/{date}/{TICKER}/ for per-ticker analysis (was reports/{TICKER}_{timestamp}/)
- reports/daily/{date}/{TICKER}/eval/ for eval logs (was eval_results/{TICKER}/...)
Adds tradingagents/report_paths.py with centralized path helpers used by
CLI commands, trading graph, and pipeline.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: structured observability logging for LLM, tool, and vendor calls
Add RunLogger (tradingagents/observability.py) that emits JSON-lines events
for every LLM call (model, agent, tokens in/out, latency), tool invocation
(tool name, args, success, latency), data vendor call (method, vendor,
success/failure, latency), and report save.
Integration points:
- route_to_vendor: log_vendor_call() on every try/catch
- run_tool_loop: log_tool_call() on every tool invoke
- ScannerGraph: new callbacks param, passes RunLogger.callback to all LLM tiers
- pipeline/macro_bridge: picks up RunLogger from thread-local, passes to TradingAgentsGraph
- cli/main.py: one RunLogger per command (analyze/scan/pipeline), write_log()
at end, summary line printed to console
Log files co-located with reports:
reports/daily/{date}/{TICKER}/run_log.jsonl (analyze)
reports/daily/{date}/market/run_log.jsonl (scan)
reports/daily/{date}/run_log.jsonl (pipeline)
Also fix test_long_response_no_nudge: update "A"*600 → "A"*2100 to match
MIN_REPORT_LENGTH=2000 threshold set in an earlier commit.
Update memory system context files (ARCHITECTURE, COMPONENTS, CONVENTIONS,
GLOSSARY, CURRENT_STATE) to document observability and report path systems.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
Root causes fixed:
- test_config_wiring.py: `callable()` returns False on LangChain @tool
objects — replaced with `hasattr(x, "invoke")` check
- test_env_override.py: `load_dotenv()` in default_config.py re-reads
.env on importlib.reload(), leaking user's TRADINGAGENTS_* env vars
into isolation tests — mock env vars before reload
- test_scanner_comprehensive.py: LLM-calling test was not marked
@pytest.mark.integration — added marker so offline runs skip it
- test_scanner_fallback.py: assertions used stale `_output_files` list
from a previous run when output dir already existed — clear dir in
setUp; also fixed tool-availability check using hasattr(x, "invoke")
- test_scanner_graph.py: output-file path assertions used hardcoded
date string instead of fixture date; graph node assertions checked
for removed node names
Full offline suite: 388 passed, 70 deselected, 0 failures.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Migrate DECISIONS.md, MISTAKES.md, PROGRESS.md, agents/, plans/, and
tradingagents/llm_clients/TODO.md into a structured docs/agent/ scaffold
with ADR-style decisions, plans, templates, and a live state tracker.
This gives agent workflows a standard memory structure for decisions,
plans, logs, and session continuity via CURRENT_STATE.md.
Agent-Ref: docs/agent/plans/global-macro-scanner.md
State-Updated: Yes
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
ahmet guzererler
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