A sophisticated logging and promotion framework that enables AI agents to learn from errors, user feedback, and discovered best practices.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install cpppp
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 cpppp 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 Agent Skill?
The Self-Improvement skill provides a structured methodology for AI coding agents to capture, analyze, and implement learnings in real-time. By utilizing a dedicated .learnings directory, the skill allows agents to document command failures, user corrections, and knowledge gaps without losing context between sessions. This framework is essential for developers using Openclaw Skills who want their agents to evolve alongside their projects, reducing recurring mistakes and hardening workflows over time.
At its core, the skill acts as a bridge between transient session experiences and permanent project memory. It enables agents to identify recurring patterns and promote them into high-level guidance files like CLAUDE.md or SOUL.md. This ensures that every mistake becomes a building block for a more capable and autonomous development environment.
Self-Improvement Agent Skill Use Cases
- Logging unexpected CLI command or API failures to ERRORS.md for later diagnosis.
- Capturing specific user corrections like "Actually, use the latest SDK version" into LEARNINGS.md.
- Tracking requested but missing agent capabilities in FEATURE_REQUESTS.md to prioritize tool development.
- Identifying recurring architectural patterns that should be promoted to permanent project instructions.
- Extracting complex, non-obvious debugging solutions into reusable Openclaw Skills.
How Self-Improvement Agent Skill Works
- The agent identifies a trigger such as a failed operation, a user-provided correction, or a newly discovered best practice.
- A structured entry is generated using a standardized ID format (e.g., LRN-YYYYMMDD-XXX) and appended to the relevant markdown log file.
- Metadata including priority, area (frontend, backend, infra), and recurrence count is assigned to ensure the data is actionable.
- During periodic reviews or through automated hooks, the agent analyzes the logs to identify patterns that meet promotion criteria.
- Validated learnings are distilled into concise rules and moved to project-level memory files or extracted into standalone Openclaw Skills.
Self-Improvement Agent Skill Setup
To install the skill within your Openclaw environment, use the following commands:
# Recommended installation via ClawdHub
clawdhub install self-improving-agent
# Manual installation
git clone https://github.com/peterskoett/self-improving-agent.git ~/.openclaw/skills/self-improving-agent
# Initialize the learning directory structure
mkdir -p ~/.openclaw/workspace/.learnings
To enable automatic session reminders and error detection, configure the Openclaw hooks:
openclaw hooks enable self-improvement
Self-Improvement Agent Skill Data Schema & Taxonomy
The skill maintains a standardized directory structure within the workspace to categorize different types of feedback:
| File | Purpose | Key Metadata |
|---|---|---|
LEARNINGS.md |
Captures corrections and gaps | Pattern-Key, Source, Area |
ERRORS.md |
Tracks tool and command failures | Error Message, Context, Priority |
FEATURE_REQUESTS.md |
Records desired capabilities | User Context, Complexity Estimate |
Each entry follows a strict schema including a unique ID, timestamp, status (pending, resolved, promoted), and specific area tags for easy filtering.
Self-Improvement Agent Skill Advanced Features
- Inter-session communication using sessions_send to pass critical learnings between active agent instances.
- Automatic skill extraction scripts that transform verified fixes into new Openclaw Skills for use in other projects.
- Pattern-based deduplication that tracks how many times a specific error has occurred to bump its priority.
- Integration with simplify-and-harden workflows to ingest recurring code patterns into durable prompt guidance.
- Support for workspace-level behavioral principles via SOUL.md and tool-specific gotchas via TOOLS.md.
SKILL.md
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