A framework for capturing execution feedback and promoting it into durable workspace memory to ensure agents learn from every interaction.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install self-improving-agent-ollieb89
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-ollieb89 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-Improving Agent?
The Self-Improving Agent skill provides a systematic approach to technical evolution within an AI workspace. By capturing errors, user corrections, and capability gaps into structured logs, it allows an agent to build a persistent memory of what works and what does not. This process is essential for developers using Openclaw Skills who want their agents to become increasingly autonomous and context-aware over time, rather than repeating the same mistakes across different sessions.
This skill functions as a bridge between immediate execution and long-term architectural improvement. It utilizes a dedicated directory structure and a set of helper scripts to ensure that every meaningful signal—whether it is a failed bash command or a nuanced stylistic correction—is preserved and eventually integrated into the core workspace configuration files.
Self-Improving Agent Use Cases
- Tracking recurring command failures or runtime errors to prevent future occurrences.
- Documenting specific user preferences and corrections to refine the agent persona.
- Identifying missing tools or capabilities that need to be developed as new Openclaw Skills.
- Capturing complex workflow workarounds that should be codified into durable documentation.
How Self-Improving Agent Works
- The agent detects a signal such as an error, a manual correction, or a repeated pattern of behavior.
- The relevant event is logged into the
.learnings/directory using specialized templates for errors, features, or general learnings. - High-value patterns are reviewed and promoted from temporary logs into durable workspace files like SOUL.md or TOOLS.md.
- Original log entries are updated with status transitions such as resolved or promoted to maintain a clear audit trail.
- Automated scripts help extract and scaffold new Openclaw Skills based on the accumulated data.
Self-Improving Agent Setup
To get started, place the skill in your workspace and verify the environment setup using the provided check script:
bash workspace/skills/self-improving-agent/scripts/check_env.sh
You can also test the skill extraction workflow with a dry run:
bash workspace/skills/self-improving-agent/scripts/extract-skill.sh my-new-pattern --dry-run
Self-Improving Agent Data Schema & Taxonomy
The skill organizes metadata and feedback using a structured directory and markdown-based taxonomy:
| File | Purpose | Key Metadata |
|---|---|---|
.learnings/LEARNINGS.md |
Captures best practices and knowledge gaps | Type, Status, Reference |
.learnings/ERRORS.md |
Logs command and tool failures | Error Code, Context, Fix |
.learnings/FEATURE_REQUESTS.md |
Tracks requested but missing capabilities | Priority, Description |
Status values include: pending, resolved, promoted, and wont_fix.
Self-Improving Agent Advanced Features
- Integrated error detection scripts for automated feedback capture during CLI operations.
- Skill extraction scaffolding to quickly turn recurring patterns into standalone Openclaw Skills.
- Promotion rules that map specific learnings to core workspace files like AGENTS.md and TOOLS.md.
- Environment verification hooks to ensure the logging directory remains consistent across sessions.
SKILL.md
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