self-reflection

Continuous self-improvement through structured reflection and memory

1,864 stars

Best use case

self-reflection is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Continuous self-improvement through structured reflection and memory

Teams using self-reflection should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/self-reflection/SKILL.md --create-dirs "https://raw.githubusercontent.com/LeoYeAI/openclaw-master-skills/main/skills/self-reflection/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/self-reflection/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How self-reflection Compares

Feature / Agentself-reflectionStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Continuous self-improvement through structured reflection and memory

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 🪞 Self-Reflection

A skill for continuous self-improvement. The agent tracks mistakes, lessons learned, and improvements over time through regular heartbeat-triggered reflections.

## Quick Start

```bash
# Check if reflection is needed
self-reflection check

# Log a new reflection
self-reflection log "error-handling" "Forgot timeout on API call" "Always add timeout=30"

# Read recent lessons
self-reflection read

# View statistics
self-reflection stats
```

## How It Works

```
Heartbeat (60m) → Agent reads HEARTBEAT.md → Runs self-reflection check
                                                      │
                                            ┌─────────┴─────────┐
                                            ▼                   ▼
                                           OK              ALERT
                                            │                   │
                                       Continue            Reflect
                                                               │
                                                     ┌─────────┴─────────┐
                                                     ▼                   ▼
                                                   read               log
                                              (past lessons)     (new insights)
```

## Commands

| Command | Description |
|---------|-------------|
| `check [--quiet]` | Check if reflection is due (OK or ALERT) |
| `log <tag> <miss> <fix>` | Log a new reflection |
| `read [n]` | Read last n reflections (default: 5) |
| `stats` | Show reflection statistics |
| `reset` | Reset the timer |

## OpenClaw Integration

Enable heartbeat in `~/.openclaw/openclaw.json`:

```json
{
  "agents": {
    "defaults": {
      "heartbeat": {
        "every": "60m",
        "activeHours": { "start": "08:00", "end": "22:00" }
      }
    }
  }
}
```

Add to your workspace `HEARTBEAT.md`:

```markdown
## Self-Reflection Check (required)
Run `self-reflection check` at each heartbeat.
If ALERT: read past lessons, reflect, then log insights.
```

## Configuration

Create `~/.openclaw/self-reflection.json`:

```json
{
  "threshold_minutes": 60,
  "memory_file": "~/workspace/memory/self-review.md",
  "state_file": "~/.openclaw/self-review-state.json",
  "max_entries_context": 5
}
```

## Author

Created by [hopyky](https://github.com/hopyky)

## License

MIT

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