Trade Journal Coach

交易复盘与心理诊断教练。专注于交易后复盘分析，通过拆解历史交易数据、对比计划与执行，找出导致亏损的坏习惯（频繁止损、盈利拿不住、逆势抗单、仓位失控、FOMO 等）。提供心理疏导和纪律约束建议，帮助用户实现"知行合一"。使用场景：用户交易后复盘、连续亏损求安慰、连续盈利求分析、定期review 交易记录时触发。

This skill’s functionality (analyzing trading records and giving psychological coaching) is plausible and the included journal_analyzer.py appears to implement metrics and reporting. However: 1) The SKILL.md mentions multiple helper scripts and reference files that are not present in the bundle — ask the author why those files are missing or obtain a complete package before trusting it. 2) The provided file content in the review appears truncated; request the full journal_analyzer.py and inspect it yourself for any network calls (requests, urllib, sockets), subprocess/spawn calls, or writes to arbitrary paths before running. 3) Because the skill requires full trade records (sensitive), never supply brokerage credentials or API keys; prefer providing a synthetic or redacted sample first. 4) If you decide to run it, do so in a sandboxed environment (local VM or container) and monitor outbound network activity. 5) If you want higher assurance, ask the maintainer for a minimal reproducible example and the missing referenced files, or request a code-signing / source repository (e.g., GitHub) so you can verify provenance.

Type: OpenClaw Skill Name: trade-journal-coach Version: 1.0.0 The 'trade-journal-coach' skill bundle is a legitimate tool designed for analyzing trading performance and providing psychological coaching. The core logic in 'scripts/journal_analyzer.py' performs standard financial calculations (win rate, profit/loss ratios, drawdowns) and identifies behavioral patterns like FOMO or lack of discipline without any malicious side effects. There is no evidence of data exfiltration, unauthorized network access, or prompt injection attacks; the instructions in 'SKILL.md' are strictly aligned with the stated purpose of trading review.