trade-performance-coach

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🇺🇸

Original

English

🇨🇳

Translation

Chinese

Trade Performance Coach

交易表现教练

Overview

概述

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.

交易表现教练会复盘已记录的交易结果和交易日志证据，帮助交易者优化决策流程。它将平仓交易记录、事后复盘结论、风险规则以及可选的市场环境背景转化为一份基于证据的教练报告，涵盖以下内容：

流程合规性
风险纪律
执行质量
潜在交易行为模式
下一交易时段操作规则
引导反思的教练式问题

本技能旨在替代专业交易环境中风险经理、交易主管或交易教练提供的支持角色。它是一款严格的流程复盘工具：绝不会建议对特定证券进行建仓、平仓、买入、卖出、做空、持有或调整仓位操作。

When to Use

使用场景

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.

当出现以下任一情况时，可使用本技能：

交易已平仓，用户需要交易后教练式复盘。
发生部分平仓，用户需要检查仓位调整、止损或平仓行为。
用户拥有
```
trader-memory-core
```
交易逻辑记录和
```
signal-postmortem
```
复盘结论，需要制定下一交易时段的操作规则。
用户需要对流程、风险、执行或行为的重复模式进行月度复盘。
用户要求以风险经理的风格复盘自己的已记录交易。
用户想了解某次亏损是流程错误、执行错误、市场环境问题还是可接受的波动。
用户希望系统标记出可能存在FOMO、报复性交易、过度自信、犹豫、移动止损或仓位逐步扩大等模式，并提供相关证据。

When Not to Use

禁用场景

Do not use this skill to:

Pick stocks or rank trade candidates.
Approve or reject a live trade as financial advice.
Place orders or draft broker instructions.
Provide therapy, mental-health diagnosis, or personality assessment.
Infer private psychological traits beyond the trade evidence supplied.
Shame the user for losses or rule violations.
Replace
```
trader-memory-core
```
; this skill consumes journal/thesis records and produces coaching findings.

If the input is incomplete, default to

REVIEW_REQUIRED

journal_only

mode and ask for missing records rather than inventing evidence.

请勿使用本技能进行以下操作：

选股或对交易候选标的进行排名。
对实时交易提供批准或拒绝的财务建议。
下达订单或起草经纪商指令。
提供心理治疗、心理健康诊断或人格评估。
超出所提供交易证据的范围推断用户的私人心理特征。
因用户亏损或违反规则而羞辱用户。
替代
```
trader-memory-core
```
；本技能会调用交易日志/逻辑记录并生成教练结论。

如果输入信息不完整，默认切换为

REVIEW_REQUIRED

或

journal_only

模式，请求补充缺失记录，而非编造证据。

Prerequisites

前置条件

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.

推荐的上游记录：

```
trader-memory-core
```
平仓交易逻辑记录或日志条目
```
signal-postmortem
```
复盘结论
原始交易计划或交易单
实际建仓/平仓/部分平仓操作记录
用户自定义的风险计划（如有）
可选的
```
market-regime-daily
```
/
```
exposure-coach
```
市场环境信息

无需付费API密钥。该确定性脚本基于本地类JSON/YAML格式的记录运行。

Inputs

输入信息

Minimum useful input is one recorded trade or one monthly aggregate.

Preferred fields:

yaml

review_type: single_trade | partial_close | monthly_aggregate
trade_id: string
ticker: string
outcome: win | loss | breakeven | mixed
planned:
  thesis: string
  entry: number
  stop: number
  target: number
  risk_r: number
  thesis_recorded_before_entry: boolean
  setup_confirmed: boolean
  market_regime: allowed | restrictive | cash_priority | unknown
actual:
  entry: number
  exit: number
  risk_r: number
  portfolio_heat_r: number
  stop_moved: boolean
  stop_move_planned: boolean
  entry_before_confirmation: boolean
  traded_against_regime: boolean
risk_plan:
  max_risk_per_trade_r: number
  max_portfolio_heat_r: number
  max_weekly_loss_r: number
postmortem:
  root_cause: thesis_quality | execution | risk_sizing | market_environment | rule_violation | randomness | unknown
  notes: [string]
journal:
  reflection: string
  emotions: [string]
monthly:
  trades: [object]
  consecutive_losses: number
  rule_violations: number

The script tolerates partial records. Missing evidence is marked as

unclear

最低有效输入为一条已记录的交易或一份月度汇总数据。

推荐字段：

yaml

review_type: single_trade | partial_close | monthly_aggregate
trade_id: string
ticker: string
outcome: win | loss | breakeven | mixed
planned:
  thesis: string
  entry: number
  stop: number
  target: number
  risk_r: number
  thesis_recorded_before_entry: boolean
  setup_confirmed: boolean
  market_regime: allowed | restrictive | cash_priority | unknown
actual:
  entry: number
  exit: number
  risk_r: number
  portfolio_heat_r: number
  stop_moved: boolean
  stop_move_planned: boolean
  entry_before_confirmation: boolean
  traded_against_regime: boolean
risk_plan:
  max_risk_per_trade_r: number
  max_portfolio_heat_r: number
  max_weekly_loss_r: number
postmortem:
  root_cause: thesis_quality | execution | risk_sizing | market_environment | rule_violation | randomness | unknown
  notes: [string]
journal:
  reflection: string
  emotions: [string]
monthly:
  trades: [object]
  consecutive_losses: number
  rule_violations: number

脚本支持部分记录输入。缺失的证据会标记为

unclear

。

Workflow

工作流程

Step 1 — Collect source records

步骤1 — 收集源记录

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

bash

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

收集最新的平仓交易记录、复盘结论、风险计划和日志笔记。

bash

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

步骤2 — 评估流程合规性

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

将实际操作与用户记录的计划和规则进行对比，检查以下内容：

缺少建仓前的交易逻辑记录
跳过信号确认环节
违反市场环境限制进行交易
未按预设规则移动止损
平仓/部分平仓操作与计划不一致
记录质量不完整

Step 3 — Evaluate risk discipline

步骤3 — 评估风险纪律

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

将实际风险和仓位热度与风险计划进行对比，检查以下内容：

单笔交易风险超过上限
组合仓位热度超过上限
周度亏损或连续亏损扩大
盈利或亏损后仓位过度放大
若提供相关数据，检查相关性风险暴露

Step 4 — Evaluate execution quality

步骤4 — 评估执行质量

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

对建仓、止损、平仓、加仓、减仓及复盘行为进行分类，区分流程合规的亏损与执行失误导致的亏损。

Step 5 — Detect possible behavior patterns

步骤5 — 检测潜在行为模式

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
```

利用日志笔记和操作标记的证据，标记潜在的交易行为模式。所有标记必须关联证据，并使用非诊断性语言。

支持的MVP标签：

```
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

步骤6 — 生成下一交易时段操作规则

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

将分析结论转化为临时、具体的操作准则。示例：

下一次建仓前必须记录交易逻辑并提供截图
违反规则后，接下来两笔交易的风险上限设为0.5R
若出现多次报复性交易证据，切换为仅复盘模式
不追高错过的建仓机会，加入观察列表等待下一次有效信号

Step 7 — Human decision gate

步骤7 — 人工决策环节

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

journal_only

Allowed actions:

text

accept_rules / modify_rules / defer / journal_only

每份报告末尾需设置人工决策环节，默认操作为

journal_only

。

允许的操作：

text

accept_rules / modify_rules / defer / journal_only

Output

输出结果

The skill produces a JSON report and optionally a Markdown report.

Required top-level JSON fields:

```
schema_version
```
```
review_type
```
```
review_id
```
```
overall_verdict
```
```
summary
```
```
scores
```
```
process_adherence_findings
```
```
risk_manager_notes
```
```
execution_quality_assessment
```
```
behavioral_pattern_tags
```
```
next_session_operating_rules
```
```
coach_questions
```
```
human_decision_gate
```
```
disclaimer
```

Verdicts:

Verdict	Meaning
`OK`	No material process violation found. Outcome appears compatible with the plan.
`WARN`	Minor process or record-quality concern.
`REVIEW_REQUIRED`	Meaningful process, risk, or behavior finding before next similar trade.
`RULE_VIOLATION`	Explicit user rule appears to have been broken.
`COOL_DOWN`	Repeated violations, drawdown/revenge pattern, or escalation suggests review-only mode.

本技能会生成一份JSON报告，可选生成Markdown报告。

必填的顶层JSON字段：

```
schema_version
```
```
review_type
```
```
review_id
```
```
overall_verdict
```
```
summary
```
```
scores
```
```
process_adherence_findings
```
```
risk_manager_notes
```
```
execution_quality_assessment
```
```
behavioral_pattern_tags
```
```
next_session_operating_rules
```
```
coach_questions
```
```
human_decision_gate
```
```
disclaimer
```

结论说明：

结论	含义
`OK`	未发现重大流程违规，交易结果与计划相符。
`WARN`	存在轻微流程或记录质量问题。
`REVIEW_REQUIRED`	在下一次同类交易前，需关注重要的流程、风险或行为问题。
`RULE_VIOLATION`	明显违反了用户设定的规则。
`COOL_DOWN`	多次违规、回撤/报复性交易模式或风险升级，建议进入仅复盘模式。

Example Command

示例命令

bash

python3 skills/trade-performance-coach/scripts/review_trade_performance.py \
  --input skills/trade-performance-coach/scripts/tests/fixtures/single_trade_rule_violation_loss.json \
  --output-dir reports/trade-performance-coach \
  --markdown

bash

python3 skills/trade-performance-coach/scripts/review_trade_performance.py \
  --input skills/trade-performance-coach/scripts/tests/fixtures/single_trade_rule_violation_loss.json \
  --output-dir reports/trade-performance-coach \
  --markdown

Resources

参考资源

Read these selectively when invoked:

```
references/review-framework.md
```
— five-axis review model, scoring, verdicts
```
references/behavior-tags.md
```
— behavior tag definitions and evidence rules
```
references/risk-review-checklist.md
```
— risk manager checklist and severity rules
```
references/output-contract.md
```
— JSON output contract and schema notes
```
references/hermes-integration.md
```
— suggested Hermes
```
/post-trade-coach
```
and monthly coaching integration

assets/performance_coach_report.schema.json

— machine-readable output schema

```
scripts/review_trade_performance.py
```
— deterministic local reviewer

调用时可选择性查阅以下资源：

```
references/review-framework.md
```
— 五维度复盘模型、评分标准、结论定义
```
references/behavior-tags.md
```
— 行为标签定义及证据规则
```
references/risk-review-checklist.md
```
— 风险经理检查清单及严重程度规则
```
references/output-contract.md
```
— JSON输出规范及架构说明

references/hermes-integration.md

— 建议的Hermes

/post-trade-coach

及月度教练集成方案

assets/performance_coach_report.schema.json

— 机器可读的输出架构

```
scripts/review_trade_performance.py
```
— 确定性本地复盘脚本

Guardrails

约束规则

This is process-review support, not financial advice.
Do not recommend buying, selling, shorting, holding, or sizing a specific security.
Do not provide therapy or mental-health diagnosis.
Do not infer personality traits.
Do not shame or moralize the user.
Tie every behavior tag to evidence.
Use "possible pattern" language for behavior tags.
Always include a human decision gate.
Default to journal/review mode when data is incomplete.

本工具仅提供流程复盘支持，不构成财务建议。
不得建议对特定证券进行买入、卖出、做空、持有或调整仓位操作。
不得提供心理治疗或心理健康诊断。
不得推断用户的人格特征。
不得羞辱用户或进行道德评判。
所有行为标签必须关联证据。
对行为标签使用“潜在模式”类表述。
必须包含人工决策环节。
数据不完整时默认切换为日志/复盘模式。