Overview
- Skill Key
- brennerspear/agent-self-reflection
- Author
- brennerspear
- Source Repo
- openclaw/skills
- Version
- 1.0.0
- Source Path
- skills/brennerspear/agent-self-reflection
- Latest Commit SHA
- a4c89656797cd75d3edbcc3e84b6856429be018d
Periodic self-reflection on recent sessions. Analyzes what went well, what went wrong, and writes concise, actionable insights to the appropriate workspace files. Designed to run as a cron job.
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Status
ACTIVE
Visibility
PUBLIC
直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 self-reflection 技能。 若已安装,则直接安装 self-reflection 技能。
# Self-Reflection Skill Reflect on recent sessions and extract actionable insights. Runs hourly via cron. ## Step 1: Gather Recent Sessions ```bash # List sessions active in the last 2 hours openclaw sessions --active 120 --json ``` Parse the output to get session keys and IDs. Skip subagent sessions (they're task workers, not interesting for reflection). Focus on: - Telegram group/topic sessions (real user interactions) - Direct sessions (1:1 with Brenner) - Cron-triggered sessions (how did automated tasks go?) ## Step 2: Read Session History For each interesting session from Step 1, read the JSONL transcript: ```bash # Read the last ~50 lines of each session file (keep it bounded!) tail -50 ~/.openclaw/agents/main/sessions/<sessionId>.jsonl ``` **⚠️ CRITICAL: Never load full session files. Use `tail -50` or `Read` with offset/limit. Sessions can be 100k+ tokens.** Parse the JSONL to understand what happened. Look for: - `type: "user"` or `type: "human"` — what was asked - `type: "assistant"` — what you responded - `type: "tool_use"` / `type: "tool_result"` — what tools were called and results - Error patterns, retries, confusion ## Step 3: Analyze & Extract Insights For each session, ask yourself: ### What went well? - Tasks completed smoothly on first try - Good tool usage patterns worth reinforcing - Efficient approaches to remember ### What went wrong? - Errors, retries, wrong approaches - Misunderstandings of user intent - Tools that didn't work as expected - Context that was missing ### Lessons learned? - "Next time, do X instead of Y" - "Remember that Z works this way" - "Tool A needs parameter B or it fails" - "When user says X, they usually mean Y" **Quality bar:** Each insight must be: - **Specific** — not "be more careful" but "check if file exists before editing" - **Actionable** — something future-you can directly apply - **Non-obvious** — skip things any competent agent would know - **New** — don't repeat insights already captured ## S...
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