Evaluate a local pre-trade checklist before manual order entry, blocking planless, oversized, revenge-risk, market-regime-blocked, or circuit-breaker-blocked entries while journaling the decision for trader-memory-core review.
Scanned 9/2/2026
Install to Claude Code
npx -y skills add Serennity007/awesome-stock-quant-skills --skill pre-trade-discipline-gate --agent claude-codeInstalls into .claude/skills of the current project.
Are you the author of Pre Trade Discipline Gate?
Add the live security badge to your README — it updates automatically with every re-scan.
[](https://www.skillsdirectory.com/skills/serennity007-pre-trade-discipline-gate)More formats (shields.io, HTML) on the badges page.
---
name: pre-trade-discipline-gate
description: Evaluate a local pre-trade checklist before manual order entry, blocking planless, oversized, revenge-risk, market-regime-blocked, or circuit-breaker-blocked entries while journaling the decision for trader-memory-core review.
---
# Pre-Trade Discipline Gate
## Overview
Evaluate whether a planned manual order should proceed before it is placed at the broker. This skill reads a local checklist plus optional market-regime, circuit-breaker, and trader-memory-core artifacts. It produces a `pre_trade_discipline_decision` artifact and can link that artifact back to the related thesis without changing the thesis review schedule.
The gate is intentionally offline. It does not place orders, cancel orders, call a broker API, or fetch market data.
## When to Use
- Immediately before placing any manual entry order
- When a candidate has passed chart validation and position sizing
- After a recent loss, to avoid revenge trades during the cooldown window
- When the workflow has an upstream `exposure_decision` and `circuit_breaker_decision`
- When you want checklist adherence to be visible in later trader-memory-core reviews
## Prerequisites
- Python 3.9+
- A local JSON or YAML answers file with candidate-level checklist answers
- Optional trader-memory-core thesis state under `state/theses/`
- Optional `exposure_decision` JSON from market-regime-daily / exposure-coach
- Optional `circuit_breaker_decision` JSON from drawdown-circuit-breaker
## Workflow
### Step 1: Prepare the Checklist
Create a JSON or YAML file with candidate answers. Only actionable manual-order intents are gated. Watchlist and ignore intents are journaled as `NO_ACTIONABLE_ORDERS`.
```json
{
"candidates": [
{
"symbol": "AAPL",
"thesis_id": "th_aapl_gm_20260703_0001",
"order_intent": "ENTRY_READY",
"entry_in_written_plan": true,
"stop_predefined": true,
"size_within_plan": true,
"planned_risk_dollars": 500,
"actual_risk_dollars": 500,
"notes": "Entry matches the journaled breakout plan."
}
]
}
```
Actionable intents are `ENTRY_READY`, `ACTIONABLE`, `ACTIONABLE_DAY1`, and `MANUAL_ORDER`. Non-actionable intents such as `WATCHLIST`, `DELAYED_EP_WATCH`, `PEAD_HANDOFF`, `IGNORE`, and `REJECTED` are recorded but do not create an order permission.
Provide both `planned_risk_dollars` and `actual_risk_dollars` for every actionable candidate. Use a finite, non-negative number or numeric string; zero is valid. Treat missing values, booleans, non-numeric strings, `NaN`, infinities, and negative values as `REVIEW_REQUIRED` inputs and review them before placing an order.
### Step 2: Run the Gate
```bash
python3 skills/pre-trade-discipline-gate/scripts/check_pre_trade_discipline.py \
--answers-file state/manual-entry-checklist.json \
--state-dir state/theses \
--market-regime-decision reports/exposure_decision_latest.json \
--circuit-breaker-decision reports/circuit_breaker_decision_latest.json \
--output-dir reports/pre-trade-discipline \
--journal-dir state/journal/pre-trade-discipline
```
Set `--as-of` for deterministic testing or backfills:
```bash
python3 skills/pre-trade-discipline-gate/scripts/check_pre_trade_discipline.py \
--answers-file state/manual-entry-checklist.json \
--as-of 2026-07-03T12:00:00-04:00
```
### Step 3: Interpret the Decision
| Decision | Meaning |
|---|---|
| `GO` | All actionable manual-order candidates passed the checklist and upstream gates |
| `REVIEW_REQUIRED` | Inputs are missing, unknown, or journaling failed; do not place orders until reviewed |
| `NO_GO` | At least one actionable candidate violated a discipline rule |
| `NO_ACTIONABLE_ORDERS` | The file contains no actionable manual orders; nothing should be placed |
By default the CLI exits `0` for every valid decision and exits `1` only for input or runtime errors. Use `--fail-on-non-go` when a shell pipeline should return `2` for any non-`GO` decision.
## Rules
The gate blocks an actionable candidate when:
- The entry is not confirmed in the written plan
- The stop is not predefined
- The size is not confirmed within plan
- Either risk-dollar field is missing or is not a finite, non-negative number (`REVIEW_REQUIRED`)
- `actual_risk_dollars` exceeds `planned_risk_dollars`
- trader-memory-core has a losing exit or partial loss inside the revenge window
- exposure-coach recommendation is `REDUCE_ONLY` or `CASH_PRIORITY`
- drawdown-circuit-breaker recommendation is `COOLDOWN`, `HALTED`, or `TRADING_HALTED`
Missing or unreadable market-regime or circuit-breaker artifacts produce `REVIEW_REQUIRED` for actionable orders. If no actionable order exists, the result remains `NO_ACTIONABLE_ORDERS`.
## Outputs
The script writes:
- `pre_trade_discipline_decision_YYYY-MM-DD_HHMMSS.json`
- A matching markdown report unless `--json-only` is set
- A JSONL journal row under `state/journal/pre-trade-discipline/` when `--journal-dir` is provided
Each candidate result includes a `checklist_answers` object with the written-plan, stop, size, risk-dollar, and notes answers used for the decision, so later reviews can audit what was answered at order time. Invalid risk-dollar values are stored as JSON `null`, while valid values retain their original representation.
If a candidate includes `thesis_id` and `--state-dir` is provided, the JSON report is linked into the thesis `linked_reports` list using trader-memory-core `link_report`. The skill does not call `mark_reviewed` and does not change monitoring review dates.
## Resources
- `scripts/check_pre_trade_discipline.py` - Main CLI and rule engine
- `references/discipline_gate_framework.md` - Rule definitions and integration notes
- `skills/trader-memory-core/schemas/thesis.schema.json` - Thesis state schema
## Key Principles
1. **Manual execution only** - The output is a pre-broker checklist gate, not an order router.
2. **Written plan first** - No written entry plan, stop, or size confirmation means no manual entry.
3. **Producer-compatible state reading** - Revenge-risk detection follows trader-memory-core timestamp and outcome behavior.
4. **Journal without review side effects** - The gate links reports to theses without advancing review schedules.
Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
No comments yet. Be the first to comment!