Trading Coach

🏆 AI交易复盘教练 — 把你的券商CSV变成可执行的改进洞察！ 自动FIFO配对持仓，8维度质量评分(入场/出场/趋势/风险...)，10维度AI洞察。 支持富途(中/英)、老虎、中信、华泰等主流券商。 触发条件: 用户提供交易CSV、要求分析交易表现、评估交易质量、生成复盘报告、 计算盈亏统计、识别交易模式问题、"帮我复盘"、"分析我的交易"。

Security Scan

The skill's purpose and instructions for analyzing broker CSVs are coherent, but the SKILL.md tells users/agents to clone and run an external GitHub repository (unvetted code) and to create a config file — this poses a code-execution / exfiltration risk that you should review before running.

Purpose & Capability

Name, description and reference docs consistently describe a CSV-based trading-replay/analysis tool (FIFO matching, scoring, insights). No declared env vars or unrelated binaries are requested — the requested capabilities align with processing CSVs and generating reports.

Instruction Scope

SKILL.md instructs the agent/user to git clone a third‑party GitHub repo and run Python scripts (import_trades.py, run_matching.py, score_positions.py, analyze_scores.py). That is within the functional scope (you need code to parse and score CSVs), but it delegates execution to external, unreviewed code and copies a config_template.py to config.py (which may lead to local secrets or configuration changes). The skill itself does not request credentials, but the instructions are sufficiently open-ended that the external repo could ask for or handle secrets or make network calls.

Install Mechanism

There is no declared install spec in the registry package, but the runtime instructions explicitly direct cloning an external GitHub repository and installing requirements via pip. That effectively instructs fetching and executing arbitrary third‑party code from an external source (user repo 'BENZEMA216/tradingcoach'), which is higher risk than an instruction-only skill that runs only built-in logic. The repo is hosted on GitHub (a known host) but is an unverified user repo — extract/run of arbitrary Python code is possible.

Credentials

The skill declares no required environment variables, no credentials, and no config paths. For its stated purpose (CSV-based analysis) this is proportionate. Note: because SKILL.md instructs creating a config.py, the external repo might request API keys or other secrets — the package itself does not declare or require them.

Persistence & Privilege

The skill does not request 'always: true' or any persistent system-level privileges. It is user-invocable and allows model invocation (defaults). Nothing in the bundle indicates it modifies other skills or global agent settings.

What to consider before installing

This skill appears to do what it says (turn broker CSVs into matched positions, scores and AI insights) and does not itself request credentials. The main risk is that the SKILL.md tells you (or an agent) to git clone and pip install a third‑party GitHub repo and then run its Python scripts — that could execute arbitrary code or attempt network calls or read files/configs. Before installing or running: 1) manually inspect the GitHub repo code (especially scripts, config_template.py) for network calls, hardcoded endpoints, or code that reads unexpected files; 2) run the code in an isolated environment (VM/container) and review requirements.txt for risky packages; 3) do not upload CSVs containing sensitive personal data to unknown remote services; 4) check whether the repo asks for API keys or broker credentials in config.py — provide only what's necessary and avoid sharing account secrets; 5) prefer running a local vetted implementation or ask the author for a signed release or reproducible build. If you want, I can list the concrete checks to perform in the repo (files/lines to search for) or, if you provide the cloned repo contents, scan them for suspicious behaviors.

🏆 Trading Coach — AI交易复盘教练

别再凭感觉交易了。让数据告诉你哪里做对了，哪里需要改进。

将券商导出的CSV交易记录，转化为专业级复盘报告和可执行的改进建议。

✨ 核心能力

• 🔄 智能导入 — 自动识别5种券商格式，一键导入
• 📊 FIFO配对 — 自动把买卖配对成完整持仓周期
• 🎯 8维度评分 — 入场、出场、趋势、风险、行为...全面诊断
• 💡 AI洞察 — 10维度分析，找出你的交易盲点

🚀 快速开始

# 首次安装
git clone https://github.com/BENZEMA216/tradingcoach.git ~/tradingcoach
cd ~/tradingcoach
python3 -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt && cp config_template.py config.py

# 一键复盘
python scripts/import_trades.py /path/to/trades.csv  # 导入
python scripts/run_matching.py                        # 配对
python scripts/score_positions.py --all               # 评分
python scripts/analyze_scores.py                      # 报告

📈 支持券商

券商	编码	自动检测
富途(中文)	UTF-8-BOM	✅ 方向、代码、成交时间
富途(英文)	UTF-8	✅ Side、Symbol、Fill Time
老虎证券	UTF-8	✅ 交易方向、股票代码
中信证券	GBK	✅ 买卖标志、证券代码
华泰证券	GBK	✅ 操作、证券代码

详见 references/csv_formats.md

🎯 评分体系

8个维度，每个都有权重：

维度	权重	评估内容
入场质量	18%	RSI/MACD/布林带配合度
出场质量	17%	止盈止损执行
趋势把握	14%	顺势/逆势、ADX强度
风险管理	12%	R:R比率、MAE/MFE
市场环境	11%	市场状态适配
交易行为	11%	纪律性、冲动检测
新闻契合	7%	新闻背景一致性
执行质量	5%	滑点、成交效率

等级: A(90+) / B(80-89) / C(70-79) / D(60-69) / F(<60)

详见 references/scoring_system.md

💡 AI洞察

10个维度深度分析你的交易模式：入场质量、出场时机、风险控制、持仓周期、费用侵蚀、历史对比、模式识别、根因分析、事件关联、改进建议

详见 references/insight_dimensions.md

📊 输出示例

总持仓: 150笔 | 胜率: 62.5% | 总盈亏: $12,500 | 平均评分: 72.3 (C)

⚠️ 在超买区域做多 — 入场时RSI=75.2，建议避免RSI>70时追涨
✅ 止损执行良好 — 平均亏损控制在2.3%，纪律性强
💡 持仓时间偏短 — 平均持仓2.3天，考虑延长持有优质标的

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☕ 支持作者

如果这个工具帮到了你，请考虑请我喝杯咖啡！

• GitHub Sponsors: @BENZEMA216
• Buy Me a Coffee: buymeacoffee.com/benzema216
• USDC (Base): 0x... (联系获取地址)

你的支持是我持续改进的动力 🚀