self-improving-agent
Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Clau...
Rank
62
Safety
84
Downloads
78k
Updated
Apr 15, 2026
Version
1.0.11
Source
CLAWHUB
About
What it does, and when to use it.
Capability contract not published. No trust telemetry is available yet. 77.6K downloads reported by the source. Last updated 4/15/2026.
Avoid when
- Contract metadata is missing or unavailable for deterministic execution.
Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing
Public facts
Every fact links back to the source it came from.
- Vendor
- Clawhubvendor · observed Apr 15, 2026
- Adoption signal
- 77.6K downloadsadoption · observed Apr 15, 2026
- Latest release
- 1.0.11release · observed Feb 22, 2026
- Handshake status
- UNKNOWNsecurity
Install and run
Setup complexity: low.
clawhub skill install kn70cjr952qdec1nx70zs6wefn7ynq2t:self-improving-agent- Install using `clawhub skill install kn70cjr952qdec1nx70zs6wefn7ynq2t:self-improving-agent` in an isolated environment before connecting it to live workloads.
- No published capability contract is available yet, so validate auth and request/response behavior manually.
- Review the upstream CLAWHUB listing at https://clawhub.ai/pskoett/self-improving-agent before using production credentials.
Contract: missing
curl -s "https://www.xpersona.co/api/v1/agents/clawhub-pskoett-self-improving-agent/snapshot"
Documentation
CLAWHUB
94,615 characters of source documentation, loaded on request.
Extracted files
5 files captured from the source.
SKILL.md
---
name: self-improvement
description: "Captures learnings, errors, and corrections to enable continuous improvement. Use when: (1) A command or operation fails unexpectedly, (2) User corrects Claude ('No, that's wrong...', 'Actually...'), (3) User requests a capability that doesn't exist, (4) An external API or tool fails, (5) Claude realizes its knowledge is outdated or incorrect, (6) A better approach is discovered for a recurring task. Also review learnings before major tasks."
metadata:
---
# Self-Improvement Skill
Log learnings and errors to markdown files for continuous improvement. Coding agents can later process these into fixes, and important learnings get promoted to project memory.
## Quick Reference
| Situation | Action |
|-----------|--------|
| Command/operation fails | Log to `.learnings/ERRORS.md` |
| User corrects you | Log to `.learnings/LEARNINGS.md` with category `correction` |
| User wants missing feature | Log to `.learnings/FEATURE_REQUESTS.md` |
| API/external tool fails | Log to `.learnings/ERRORS.md` with integration details |
| Knowledge was outdated | Log to `.learnings/LEARNINGS.md` with category `knowledge_gap` |
| Found better approach | Log to `.learnings/LEARNINGS.md` with category `best_practice` |
| Simplify/Harden recurring patterns | Log/update `.learnings/LEARNINGS.md` with `Source: simplify-and-harden` and a stable `Pattern-Key` |
| Similar to existing entry | Link with `**See Also**`, consider priority bump |
| Broadly applicable learning | Promote to `CLAUDE.md`, `AGENTS.md`, and/or `.github/copilot-instructions.md` |
| Workflow improvements | Promote to `AGENTS.md` (OpenClaw workspace) |
| Tool gotchas | Promote to `TOOLS.md` (OpenClaw workspace) |
| Behavioral patterns | Promote to `SOUL.md` (OpenClaw workspace) |
## OpenClaw Setup (Recommended)
OpenClaw is the primary platform for this skill. It uses workspace-based prompt injection with automatic skill loading.
### Installation
**Via ClawdHub (recommended):**
```bash
clawdhub install self-improving-agent
```
**Manual:**
```bash
git clone https://github.com/peterskoett/self-improving-agent.git ~/.openclaw/skills/self-improving-agent
```
Remade for openclaw from original repo : https://github.com/pskoett/pskoett-ai-skills - https://github.com/pskoett/pskoett-ai-skills/tree/main/skills/self-improvement
### Workspace Structure
OpenClaw injects these files into every session:
```
~/.openclaw/workspace/
├── AGENTS.md # Multi-agent workflows, delegation patterns
├── SOUL.md # Behavioral guidelines, personality, principles
├── TOOLS.md # Tool capabilities, integration gotchas
├── MEMORY.md # Long-term memory (main session only)
├── memory/ # Daily memory files
│ └── YYYY-MM-DD.md
└── .learnings/ # This skill's log files
├── LEARNINGS.md
├── ERRORS.md
└── FEATURE_REQUESTS.md
```
### Create Learning Files
```bash
mkdir -p ~/.openclaw/workspace/.learnings
```
Then create the _meta.json
{
"ownerId": "kn70cjr952qdec1nx70zs6wefn7ynq2t",
"slug": "self-improving-agent",
"version": "1.0.11",
"publishedAt": 1771777713337
}references/examples.md
# Entry Examples Concrete examples of well-formatted entries with all fields. ## Learning: Correction ```markdown ## [LRN-20250115-001] correction **Logged**: 2025-01-15T10:30:00Z **Priority**: high **Status**: pending **Area**: tests ### Summary Incorrectly assumed pytest fixtures are scoped to function by default ### Details When writing test fixtures, I assumed all fixtures were function-scoped. User corrected that while function scope is the default, the codebase convention uses module-scoped fixtures for database connections to improve test performance. ### Suggested Action When creating fixtures that involve expensive setup (DB, network), check existing fixtures for scope patterns before defaulting to function scope. ### Metadata - Source: user_feedback - Related Files: tests/conftest.py - Tags: pytest, testing, fixtures --- ``` ## Learning: Knowledge Gap (Resolved) ```markdown ## [LRN-20250115-002] knowledge_gap **Logged**: 2025-01-15T14:22:00Z **Priority**: medium **Status**: resolved **Area**: config ### Summary Project uses pnpm not npm for package management ### Details Attempted to run `npm install` but project uses pnpm workspaces. Lock file is `pnpm-lock.yaml`, not `package-lock.json`. ### Suggested Action Check for `pnpm-lock.yaml` or `pnpm-workspace.yaml` before assuming npm. Use `pnpm install` for this project. ### Metadata - Source: error - Related Files: pnpm-lock.yaml, pnpm-workspace.yaml - Tags: package-manager, pnpm, setup ### Resolution - **Resolved**: 2025-01-15T14:30:00Z - **Commit/PR**: N/A - knowledge update - **Notes**: Added to CLAUDE.md for future reference --- ``` ## Learning: Promoted to CLAUDE.md ```markdown ## [LRN-20250115-003] best_practice **Logged**: 2025-01-15T16:00:00Z **Priority**: high **Status**: promoted **Promoted**: CLAUDE.md **Area**: backend ### Summary API responses must include correlation ID from request headers ### Details All API responses should echo back the X-Correlation-ID header from the request. This is required for distributed tracing. Responses without this header break the observability pipeline. ### Suggested Action Always include correlation ID passthrough in API handlers. ### Metadata - Source: user_feedback - Related Files: src/middleware/correlation.ts - Tags: api, observability, tracing --- ``` ## Learning: Promoted to AGENTS.md ```markdown ## [LRN-20250116-001] best_practice **Logged**: 2025-01-16T09:00:00Z **Priority**: high **Status**: promoted **Promoted**: AGENTS.md **Area**: backend ### Summary Must regenerate API client after OpenAPI spec changes ### Details When modifying API endpoints, the TypeScript client must be regenerated. Forgetting this causes type mismatches that only appear at runtime. The generate script also runs validation. ### Suggested Action Add to agent workflow: after any API changes, run `pnpm run generate:api`. ### Metadata - Source: error - Related Files: openapi.yaml, src/client/api.ts - Tags: api, codegen, type
references/hooks-setup.md
# Hook Setup Guide
Configure automatic self-improvement triggers for AI coding agents.
## Overview
Hooks enable proactive learning capture by injecting reminders at key moments:
- **UserPromptSubmit**: Reminder after each prompt to evaluate learnings
- **PostToolUse (Bash)**: Error detection when commands fail
## Claude Code Setup
### Option 1: Project-Level Configuration
Create `.claude/settings.json` in your project root:
```json
{
"hooks": {
"UserPromptSubmit": [
{
"matcher": "",
"hooks": [
{
"type": "command",
"command": "./skills/self-improvement/scripts/activator.sh"
}
]
}
],
"PostToolUse": [
{
"matcher": "Bash",
"hooks": [
{
"type": "command",
"command": "./skills/self-improvement/scripts/error-detector.sh"
}
]
}
]
}
}
```
### Option 2: User-Level Configuration
Add to `~/.claude/settings.json` for global activation:
```json
{
"hooks": {
"UserPromptSubmit": [
{
"matcher": "",
"hooks": [
{
"type": "command",
"command": "~/.claude/skills/self-improvement/scripts/activator.sh"
}
]
}
]
}
}
```
### Minimal Setup (Activator Only)
For lower overhead, use only the UserPromptSubmit hook:
```json
{
"hooks": {
"UserPromptSubmit": [
{
"matcher": "",
"hooks": [
{
"type": "command",
"command": "./skills/self-improvement/scripts/activator.sh"
}
]
}
]
}
}
```
## Codex CLI Setup
Codex uses the same hook system as Claude Code. Create `.codex/settings.json`:
```json
{
"hooks": {
"UserPromptSubmit": [
{
"matcher": "",
"hooks": [
{
"type": "command",
"command": "./skills/self-improvement/scripts/activator.sh"
}
]
}
]
}
}
```
## GitHub Copilot Setup
Copilot doesn't support hooks directly. Instead, add guidance to `.github/copilot-instructions.md`:
```markdown
## Self-Improvement
After completing tasks that involved:
- Debugging non-obvious issues
- Discovering workarounds
- Learning project-specific patterns
- Resolving unexpected errors
Consider logging the learning to `.learnings/` using the format from the self-improvement skill.
For high-value learnings that would benefit other sessions, consider skill extraction.
```
## Verification
### Test Activator Hook
1. Enable the hook configuration
2. Start a new Claude Code session
3. Send any prompt
4. Verify you see `<self-improvement-reminder>` in the context
### Test Error Detector Hook
1. Enable PostToolUse hook for Bash
2. Run a command that fails: `ls /nonexistent/path`
3. Verify you see `<error-detected>` reminder
### Dry Run Extract Script
```bash
./skills/self-improvement/scripts/extract-skill.sh test-skill --dry-run
```
Expectedreferences/openclaw-integration.md
# OpenClaw Integration
Complete setup and usage guide for integrating the self-improvement skill with OpenClaw.
## Overview
OpenClaw uses workspace-based prompt injection combined with event-driven hooks. Context is injected from workspace files at session start, and hooks can trigger on lifecycle events.
## Workspace Structure
```
~/.openclaw/
├── workspace/ # Working directory
│ ├── AGENTS.md # Multi-agent coordination patterns
│ ├── SOUL.md # Behavioral guidelines and personality
│ ├── TOOLS.md # Tool capabilities and gotchas
│ ├── MEMORY.md # Long-term memory (main session only)
│ └── memory/ # Daily memory files
│ └── YYYY-MM-DD.md
├── skills/ # Installed skills
│ └── <skill-name>/
│ └── SKILL.md
└── hooks/ # Custom hooks
└── <hook-name>/
├── HOOK.md
└── handler.ts
```
## Quick Setup
### 1. Install the Skill
```bash
clawdhub install self-improving-agent
```
Or copy manually:
```bash
cp -r self-improving-agent ~/.openclaw/skills/
```
### 2. Install the Hook (Optional)
Copy the hook to OpenClaw's hooks directory:
```bash
cp -r hooks/openclaw ~/.openclaw/hooks/self-improvement
```
Enable the hook:
```bash
openclaw hooks enable self-improvement
```
### 3. Create Learning Files
Create the `.learnings/` directory in your workspace:
```bash
mkdir -p ~/.openclaw/workspace/.learnings
```
Or in the skill directory:
```bash
mkdir -p ~/.openclaw/skills/self-improving-agent/.learnings
```
## Injected Prompt Files
### AGENTS.md
Purpose: Multi-agent workflows and delegation patterns.
```markdown
# Agent Coordination
## Delegation Rules
- Use explore agent for open-ended codebase questions
- Spawn sub-agents for long-running tasks
- Use sessions_send for cross-session communication
## Session Handoff
When delegating to another session:
1. Provide full context in the handoff message
2. Include relevant file paths
3. Specify expected output format
```
### SOUL.md
Purpose: Behavioral guidelines and communication style.
```markdown
# Behavioral Guidelines
## Communication Style
- Be direct and concise
- Avoid unnecessary caveats and disclaimers
- Use technical language appropriate to context
## Error Handling
- Admit mistakes promptly
- Provide corrected information immediately
- Log significant errors to learnings
```
### TOOLS.md
Purpose: Tool capabilities, integration gotchas, local configuration.
```markdown
# Tool Knowledge
## Self-Improvement Skill
Log learnings to `.learnings/` for continuous improvement.
## Local Tools
- Document tool-specific gotchas here
- Note authentication requirements
- Track integration quirks
```
## Learning Workflow
### Capturing Learnings
1. **In-session**: Log to `.learnings/` as usual
2. **Cross-session**: Promote to workspace files
### Promotion Decision Tree
```
Is the learning projecMachine-readable data
The same record, as JSON, for agents and crawlers.
{
"facts": [
{
"factKey": "vendor",
"category": "vendor",
"label": "Vendor",
"value": "Clawhub",
"href": "https://clawhub.ai/pskoett/self-improving-agent",
"sourceUrl": "https://clawhub.ai/pskoett/self-improving-agent",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-04-15T00:45:39.800Z",
"isPublic": true
},
{
"factKey": "traction",
"category": "adoption",
"label": "Adoption signal",
"value": "77.6K downloads",
"href": "https://clawhub.ai/pskoett/self-improving-agent",
"sourceUrl": "https://clawhub.ai/pskoett/self-improving-agent",
"sourceType": "profile",
"confidence": "medium",
"observedAt": "2026-04-15T00:45:39.800Z",
"isPublic": true
},
{
"factKey": "latest_release",
"category": "release",
"label": "Latest release",
"value": "1.0.11",
"href": "https://clawhub.ai/pskoett/self-improving-agent",
"sourceUrl": "https://clawhub.ai/pskoett/self-improving-agent",
"sourceType": "release",
"confidence": "medium",
"observedAt": "2026-02-22T16:28:33.337Z",
"isPublic": true
},
{
"factKey": "handshake_status",
"category": "security",
"label": "Handshake status",
"value": "UNKNOWN",
"href": "https://www.xpersona.co/api/v1/agents/clawhub-pskoett-self-improving-agent/trust",
"sourceUrl": "https://www.xpersona.co/api/v1/agents/clawhub-pskoett-self-improving-agent/trust",
"sourceType": "trust",
"confidence": "medium",
"observedAt": null,
"isPublic": true
}
],
"events": [
{
"eventType": "release",
"title": "Release 1.0.11",
"description": "No functional or content changes; OpenClaw-specific environment metadata was removed. - Removed the OpenClaw `requires.env` metadata block from the skill definition. - All usage guidance, logging formats, and workflow instructions remain unchanged. - No new features or bug fixes included in this version. - This update does not require any action from users. - Ensures cleaner skill metadata and wider compatibility.",
"href": "https://clawhub.ai/pskoett/self-improving-agent",
"sourceUrl": "https://clawhub.ai/pskoett/self-improving-agent",
"sourceType": "release",
"confidence": "medium",
"observedAt": "2026-02-22T16:28:33.337Z",
"isPublic": true
}
]
}Record generated Oct 10, 2026.
