# Backtest Strategy ICM Workspace

This workspace orchestrates rules-based strategy backtesting for the operator's core
styles (SPY 0DTE credit spreads, single-leg equity/options day trades) using TTG data
servers as the only market-data source and a local pure-Python engine.

The agent follows the numbered stages to freeze strategy rules, verify data depth,
build the data cache, run the backtest, and produce an honest report.

Folder structure:
- CLAUDE.md (Layer 0): workspace identity
- CONTEXT.md (Layer 1): workspace-level routing
- stages/: numbered stage folders
  - 00_clarify_strategy/: freeze rules into a spec (with operator)
  - 01_verify_data/: enumerate contracts + verify historical depth
  - 02_fetch_cache/: pull bars/quotes into the shared cache
  - 03_run_backtest/: run the engine over cached data
  - 04_report/: render findings with small-sample honesty
- _config/: Layer 3 reference material (stable across runs)
- shared/: data cache (SQLite) + engine scripts
- Each stage's output/ holds Layer 4 working artifacts for handoff to next stage.

## Hard rules (apply to every stage)
- Market data comes ONLY from TTG data servers. Never scrape or substitute public sites.
- Python is stdlib-only. NO package installs. The operator manages packaging with uv
  (pyproject.toml in the workspace root has zero dependencies by design).
- No look-ahead: a signal on bar N may only use bars <= N.
- Every stage ends at a review gate. output/ is read (and optionally edited by the
  operator) before the next stage runs.
- Clear a stage's output/ before re-running it.
- Backtest results are research, not trade plans. Any live trade still goes through
  the normal cockpit path.