OpenClaw

self-reflection

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.

brennerspear0 来源安装数☆ 0 仓库 Starsv1.0.0

查看来源 ↗安装与使用 SKILL.md ↗

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

SkillHub CLI

skillhub install brennerspear/agent-self-reflection

打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

Self-Reflection Skill

Reflect on recent sessions and extract actionable insights. Runs hourly via cron.

Step 1: Gather Recent Sessions

# 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:

# 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...

来源信息

Source: github
Repository: openclaw/skills
Path: skills/brennerspear/agent-self-reflection
Version: 1.0.0
Commit: a4c89656797cd75d3edbcc3e84b6856429be018d
分类来源: rules
状态: active
可见性: public

这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。

来源内容

SKILL.md

# 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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