A structured logging and memory system that enables AI agents to capture errors, corrections, and best practices for continuous autonomous improvement.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install self-improving-agent-1-0-2
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install self-improving-agent-1-0-2 using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Self-Improvement Skill?
The Self-Improvement Skill provides a systematic framework for AI agents to document their operational lifecycle. By capturing learnings, errors, and feature requests in local markdown files, agents can avoid repeating mistakes and evolve their capabilities over time. Integrating this with Openclaw Skills allows developers to maintain a high-quality project memory that persists across sessions, ensuring the agent remains aligned with project-specific conventions and evolving technical requirements.
This skill acts as an autonomous feedback loop. When an agent encounters an error or receives a user correction, it doesn't just fix it in the moment; it records the event to prevent future occurrences. By promoting high-value entries to permanent project memory files like CLAUDE.md or AGENTS.md, the skill ensures that every interaction contributes to a more intelligent and efficient development environment within the ecosystem of Openclaw Skills.
Self-Improvement Skill Use Cases
- Logging unexpected command or operation failures to prevent recurring bugs.
- Capturing user corrections to update the agent's internal knowledge and style.
- Tracking requested capabilities that do not yet exist for future roadmap planning.
- Promoting broadly applicable best practices to project-wide instruction files.
- Identifying recurring patterns in development to trigger systemic architectural improvements.
How Self-Improvement Skill Works
- The agent detects a trigger such as a failed command, a direct user correction, or a newly discovered best practice.
- A structured entry is generated and appended to the relevant file in the
.learnings/directory using standardized Openclaw Skills templates. - Each entry is assigned a unique ID (e.g., LRN-YYYYMMDD-XXX), priority level, and functional area tag for easy filtering.
- The agent conducts periodic reviews of pending entries to resolve issues or link related patterns.
- High-value insights are promoted to project memory files or extracted into entirely new, reusable Openclaw Skills.
Self-Improvement Skill Setup
To begin using this skill, create the necessary directory structure in your project root:
mkdir -p .learnings
For automated integration with Claude Code or Codex, configure your .claude/settings.json to include the skill activator hooks:
{
"hooks": {
"UserPromptSubmit": [{
"matcher": "",
"hooks": [{
"type": "command",
"command": "./skills/self-improvement/scripts/activator.sh"
}]
}]
}
}
Self-Improvement Skill Data Schema & Taxonomy
The skill organizes its data within a .learnings/ folder using three primary markdown files:
| File | Purpose | Metadata Captured |
|---|---|---|
LEARNINGS.md |
Knowledge gaps, corrections, and best practices | Priority, Status, Area, Source |
ERRORS.md |
Command failures and tool exceptions | Reproducibility, Context, Suggested Fix |
FEATURE_REQUESTS.md |
Missing capabilities and user needs | Complexity, Frequency, Suggested Implementation |
Entries are identified by a unique ID format: TYPE-YYYYMMDD-XXX (e.g., ERR-20250115-A3F).
Self-Improvement Skill Advanced Features
- Automated error detection using PostToolUse hooks to capture stack traces in real-time.
- Skill extraction scripts that automatically convert resolved learnings into standalone Openclaw Skills.
- Multi-agent synchronization supporting Clawdbot, Claude Code, and GitHub Copilot workflows.
- Integration with specialized workspace files like SOUL.md for behavioral traits and TOOLS.md for capability documentation.
- Pattern detection via CLI utilities to identify and escalate high-priority recurring issues.
SKILL.md
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