MCPInstall

pre-trade-discipline-gate

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.

Installs
2.7K
Last 24h
+23
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#5187
Security
Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/tradermonty/claude-trading-skills --skill pre-trade-discipline-gate
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads pre-trade-discipline-gate automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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.

{
  "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

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:

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

DecisionMeaning
GOAll actionable manual-order candidates passed the checklist and upstream gates
REVIEW_REQUIREDInputs are missing, unknown, or journaling failed; do not place orders until reviewed
NO_GOAt least one actionable candidate violated a discipline rule
NO_ACTIONABLE_ORDERSThe 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. Valid JSON decimals that cannot round-trip through a binary float are retained as numeric strings so underflow or precision loss cannot change the gate decision.

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.

FAQ

What does the pre-trade-discipline-gate skill do?

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.

How do I install pre-trade-discipline-gate?

Run npx skills add https://github.com/tradermonty/claude-trading-skills --skill pre-trade-discipline-gate in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/pre-trade-discipline-gate/ (personal) or .claude/skills/pre-trade-discipline-gate/ (project).

Which AI agents can use pre-trade-discipline-gate?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is pre-trade-discipline-gate safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains pre-trade-discipline-gate?

It is published by tradermonty in tradermonty/claude-trading-skills. It has 2,726 recorded installs.

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