Drawdown Circuit Breaker

Drawdown Circuit Breaker

Overview

Evaluate whether the trader should take new trade risk today based on account-level realized P&L and recent terminal trade outcomes. This skill reads trader-memory-core thesis YAML files only. It produces a circuit_breaker_decision artifact that complements the market-side exposure_decision from exposure-coach.

The circuit breaker is a recommendation and recordkeeping tool. It does not replace human judgment, and it does not enforce broker-side blocks or automated order rejection.

When to Use

• Before screening or sizing any new swing trade candidate
• After a losing trade or partial trim to check whether a cooldown is active
• During daily planning when trader-memory-core contains recent closed or partially closed positions
• As a workflow gate before swing-opportunity-daily proceeds to candidate generation
• When reviewing whether daily, weekly, or monthly loss limits have been breached

Prerequisites

• Python 3.9+
• Local trader-memory-core thesis YAML files, usually under state/theses/
• Account size in dollars
• No API keys or network access required

Workflow

Step 1: Read Trader Memory State

Point the script at the thesis state directory:

python3 skills/drawdown-circuit-breaker/scripts/check_circuit_breaker.py \
  --state-dir state/theses \
  --account-size 100000 \
  --output-dir reports/

The script scans every th_*.yaml file and reads realized P&L from each thesis status_history[] ledger entry. It does not use _index.json for P&L, because the index is a lightweight lookup file and does not contain the required realized-P&L ledger.

After validating each file, the script groups valid theses by the case-sensitive, whitespace-trimmed thesis_id. If two or more valid files share an ID, it excludes the entire duplicate group from P&L and losing-streak calculations, reports every actual source path, and returns PARTIAL + HALTED until the duplicate state is repaired and the decision is rerun. metrics.theses_scanned counts only accepted theses with unique IDs.

If the state directory is missing or is an empty directory, the skill returns TRADING_ALLOWED with data_quality: EMPTY_STATE so a new user is not blocked by the absence of history. If the configured state path exists but is not a directory, the skill fails closed as incomplete state data.

If state exists but a thesis, ledger event, or terminal result must be skipped or conflicts with another recorded value, the skill fails closed with data_quality: PARTIAL, recommendation: HALTED, and an incomplete_state_data rule. Repair the warnings and rerun before taking new risk. The one recoverable exception is a finite terminal outcome.pnl_dollars fallback for a legacy thesis with no realized-P&L ledger entry; it remains visible as PARTIAL but does not by itself override the calculated recommendation. For ACTIVE, PARTIALLY_CLOSED, CLOSED, and INVALIDATED theses, each history event must be an object with a recognized status and parseable at, and the last history status must match the thesis status. ACTIVE and PARTIALLY_CLOSED theses must also carry entry actuals; PARTIALLY_CLOSED must carry a position. Malformed, stale, or skeletal lifecycle history disqualifies terminal fallback and halts. Ledger-shaped events whose realized_pnl is missing, untyped, or non-finite also halt instead of being coerced.

Step 2: Evaluate Circuit Breaker Rules

The default rules are:

Day, week, and month boundaries use America/New_York. Date-only producer timestamps from trader-memory-core are counted on the named ET date. Set --as-of for deterministic evaluation; date-only --as-of values cover the full ET day, while timestamp values exclude future events after that time:

python3 skills/drawdown-circuit-breaker/scripts/check_circuit_breaker.py \
  --state-dir state/theses \
  --account-size 100000 \
  --as-of 2026-07-02T12:00:00-04:00 \
  --output-dir reports/