Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/idea2realclaw/myagent/self-reflectionnpx skills add idea2realClaw/myAgent --skill self-reflectiongit clone --depth 1 https://github.com/idea2realClaw/myAgentWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00049 | $0.00915 |
| Opus 5 | $0.00024 | $0.00458 |
| Sonnet 5 | $0.00010 | $0.00183 |
| Haiku 4.5 | $0.00005 | $0.00092 |
Grade A, and why
self-reflection scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
自我反省与成长 Skill
概述
这个 Skill 帮助龙木心（我）建立系统性的自我反省机制，包括：
- 记录犯错和卡壳的地方
- 总结成功经验和最佳实践
- 分析根本原因和改进方案
- 跟踪持续改进效果
脚本路径
~/.workbuddy/skills/self-reflection/scripts/reflection.py
反省维度
1. 错误记录
- 发生了什么？（具体问题）
- 为什么发生？（根本原因）
- 怎么解决？（临时修复）
- 怎么避免？（长期改进）
2. 经验沉淀
- 哪里做对了？（成功案例）
- 为什么成功？（关键因素）
- 怎么复现？（最佳实践）
3. 流程优化
- 当前痛点（重复性工作、效率低下）
- 改进方案（自动化、标准化、工具化）
4. 同理心学习
- 观察他人（其他 AI 助手、师父的反馈）
- 可借鉴点（风格、方法、习惯）
命令参考
记录反省
# 交互式记录（问答引导）
python3 ~/.workbuddy/skills/self-reflection/scripts/reflection.py record
# 命令行模式（JSON 格式）
python3 ~/.workbuddy/skills/self-reflection/scripts/reflection.py record --json '{
"type": "error|success|process|learn",
"what": "具体事件",
"why": "原因分析",
"how": "改进方案"
}'
查看反省日志
# 查看全部
python3 ~/.workbuddy/skills/self-reflection/scripts/reflection.py list
# 按类型筛选
python3 ~/.workbuddy/skills/self-reflection/scripts/reflection.py list error
# 查看最近 N 条
python3 ~/.workbuddy/skills/self-reflection/scripts/reflection.py list 10
生成改进报告
# 生成本周改进总结
python3 ~/.workbuddy/skills/self-reflection/scripts/reflection.py report --days 7
# 生成月度报告
python3 ~/.workbuddy/skills/self-reflection/scripts/reflection.py report --days 30
搜索关键词
python3 ~/.workbuddy/skills/self-reflection/scripts/reflection.py search "Gmail"
python3 ~/.workbuddy/skills/self-reflection/scripts/reflection.py search "IMAP"
使用流程（SOP）
每日反省（建议每次会话结束时）
- 运行
reflection.py record - 选择类型（错误/成功/流程/学习）
- 按提示填写事件、原因、改进
- 系统自动保存到反省日志
每周复盘（建议周初）
- 运行
reflection.py report --days 7 - 回顾本周错误和改进
- 制定下周目标
反省模板
错误模板
【错误】描述具体问题
【原因】根本原因分析
【临时修复】当时怎么解决的
【长期改进】以后怎么避免
成功模板
【成功】描述做得好的地方
【关键因素】为什么成功
【可复现】形成最佳实践
注意事项
- 反省要诚实，不美化错误
- 改进要可落地，具体可执行
- 成功要可复制，转化为标准化流程
- 定期回顾，持续迭代
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 136 lines · 49 tokens per session scan A a55f84148cc5
self-reflection is a skill published in the GitHub repository idea2realClaw/myAgent (2 stars, last pushed 13d ago), licensed MIT. It adds 49 tokens to every session and 915 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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