Trade Performance Coach

Review closed trades, partial exits, and monthly trade aggregates for process adherence, risk discipline, execution quality, and evidence-based trading behavior patterns. Use after trader-memory-core and signal-postmortem have produced records, or when the user asks for a post-trade coach, risk-manager style review, rule-adherence review, next-session operating rules, or psychology-aware trading behavior feedback. This skill does not provide buy/sell advice, therapy, or broker execution.

No API

Download Skill Package (.skill) View Source on GitHub

Table of Contents

1. Overview

Trade Performance Coach reviews recorded trade outcomes and journal evidence to help a human trader improve their decision process. It converts closed-trade records, postmortem findings, risk rules, and optional market-regime context into an evidence-based coaching report covering:

  • process adherence
  • risk discipline
  • execution quality
  • possible trading-behavior patterns
  • next-session operating rules
  • coach questions for reflection

This skill is intended to fill the support role that a risk manager, desk lead, or trading coach might provide in a professional trading environment. It is strictly a process-review skill: it never recommends entering, exiting, buying, selling, shorting, holding, or sizing a specific security.

2. When to Use

Use this skill when any of the following are true:

  • A trade has been closed and the user wants a post-trade coaching review.
  • A partial close occurred and the user wants to inspect sizing, stop, or exit behavior.
  • The user has trader-memory-core thesis records and signal-postmortem findings and wants next-session operating rules.
  • The user wants a monthly review of recurring process, risk, execution, or behavior patterns.
  • The user asks for a risk-manager style review of their own recorded trades.
  • The user asks whether a loss was a process error, execution error, market environment issue, or acceptable variance.
  • The user wants possible FOMO, revenge-trade, overconfidence, hesitation, stop-moving, or size-creep patterns flagged with evidence.

3. Prerequisites

Recommended upstream records:

  • trader-memory-core closed thesis record or journal entry
  • signal-postmortem postmortem findings
  • original trade plan or trade ticket
  • actual entry / exit / partial-close actions
  • user-defined risk plan, if available
  • optional market-regime-daily / exposure-coach context

No paid API key is required. The deterministic script works from local JSON/YAML-like records.

4. Quick Start 

python3 skills/trade-performance-coach/scripts/review_trade_performance.py \
  --input reports/trade_memory/closed_thesis_EXMPL.json \
  --output-dir reports/trade-performance-coach

5. Workflow

Step 1 — Collect source records

Collect the most recent closed trade record, postmortem, risk plan, and journal notes.

python3 skills/trade-performance-coach/scripts/review_trade_performance.py \
  --input reports/trade_memory/closed_thesis_EXMPL.json \
  --output-dir reports/trade-performance-coach

Step 2 — Evaluate process adherence

Compare actual actions against the user’s documented plan and rules. Check for:

  • missing pre-entry thesis
  • setup confirmation skipped
  • trade taken against market-regime gate
  • stop moved without a pre-defined rule
  • exit / partial close inconsistent with plan
  • incomplete record quality

Step 3 — Evaluate risk discipline

Compare actual risk and heat against the risk plan. Check for:

  • per-trade risk above max
  • portfolio heat above max
  • weekly loss or consecutive-loss escalation
  • oversized trade after a winner or loser
  • correlated exposure if provided

Step 4 — Evaluate execution quality

Classify entry, stop, exit, add, trim, and review behavior. Separate clean-process losses from execution mistakes.

Step 5 — Detect possible behavior patterns

Use evidence from journal notes and action flags to tag possible trading behavior patterns. Always tie a tag to evidence and use non-diagnostic language.

Supported MVP tags:

  • fomo_entry
  • revenge_trade
  • premature_exit
  • overconfidence_after_winner
  • stop_moved
  • size_creep
  • hesitation
  • rule_drift
  • no_pattern_detected

Step 6 — Produce next-session operating rules

Convert findings into temporary, concrete guardrails. Examples:

  • require thesis record and screenshot before the next entry
  • cap risk at 0.5R for the next two trades after a rule violation
  • switch to review-only mode after repeated revenge-trade evidence
  • do not chase a missed entry; add to watchlist for the next valid setup

Step 7 — Human decision gate

End every report with a human decision gate. The default action is journal_only.

Allowed actions:

accept_rules / modify_rules / defer / journal_only

6. Resources

References:

  • skills/trade-performance-coach/references/behavior-tags.md
  • skills/trade-performance-coach/references/hermes-integration.md
  • skills/trade-performance-coach/references/output-contract.md
  • skills/trade-performance-coach/references/review-framework.md
  • skills/trade-performance-coach/references/risk-review-checklist.md

Scripts:

  • skills/trade-performance-coach/scripts/review_trade_performance.py