A sophisticated Python CLI tool designed to monitor, analyze, and optimize the lifecycle and performance of OpenClaw agent skills.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install self-skill-evolver
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-skill-evolver 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 Skill Evolver?
Self Skill Evolver is a specialized utility for developers looking to maintain high-quality AI capabilities. By focusing on the continuous improvement of Openclaw Skills, this tool provides a structured framework for evaluating skill reliability, performance, and maintainability. It serves as a quality assurance layer that ensures every agent skill is operating at peak efficiency before and after deployment.
The tool bridges the gap between raw code and actionable insights by scanning SKILL.md files and associated source code. It empowers developers to move beyond manual testing by providing automated improvement suggestions and detailed reporting, making it an essential component for any professional Openclaw Skills development workflow.
Self Skill Evolver Use Cases
- Evaluating skill reliability and performance metrics before a production release.
- Monitoring real-time usage and success rates of Openclaw Skills in active environments.
- Identifying technical debt or documentation gaps within SKILL.md and source code files.
- Generating comprehensive health reports for a library of agent skills.
- Managing long-term skill logs and user feedback to guide version updates.
How Self Skill Evolver Works
- The user initializes the environment using the init command to set up the local tracking database.
- The tool monitors Openclaw Skills performance by logging specific actions, execution statuses, and durations.
- A health score is calculated based on code quality scans, documentation completeness, and historical success rates.
- Developers run analysis commands to identify specific areas for improvement within the skill structure.
- The system generates actionable suggestions and exports them into JSON, Markdown, or HTML reports for review.
Self Skill Evolver Setup
Install the tool directly via the clawhub registry to begin optimizing your Openclaw Skills:
clawhub install self-skill-evolver
Ensure you have Python 3.8+ and SQLite3 available on your system. Once installed, initialize the tracker:
self-skill-evolver init
Self Skill Evolver Data Schema & Taxonomy
Self Skill Evolver organizes its data using a local SQLite backend to ensure fast, persistent tracking of Openclaw Skills metadata:
| Component | Format | Description |
|---|---|---|
| Performance Logs | SQLite | Records action status, execution time, and timestamps. |
| Health Scores | Numeric/JSON | Aggregated metrics based on code scans and documentation parity. |
| Reports | MD/HTML/JSON | Exportable files detailing improvement suggestions and analysis results. |
| Feedback | String/Int | Stores user-provided ratings and qualitative comments for each skill. |
Self Skill Evolver Advanced Features
- Bulk analysis capabilities using the --all flag to audit entire skill directories simultaneously.
- Granular log management including filtering by age and status for automated cleanup.
- Automated SKILL.md validation to ensure documentation matches technical implementation.
- Multi-format reporting engine support for integration into CI/CD pipelines.
- Optional GitPython integration for tracking skill evolution across different version commits.
SKILL.md
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