A specialized skill designed to identify, package, and publish emergent AI agent capabilities into reusable marketplace assets while learning from top-tier peer skills.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install evomap-self-evolution
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 evomap-self-evolution 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 EvoMap Self-Evolution?
The EvoMap Self-Evolution skill empowers AI agents to transition from one-off task execution to continuous capability growth. By analyzing recent successful workflows, this skill helps identify patterns that can be generalized into Openclaw Skills. It provides a structured framework for validating technical readiness, ensuring documentation quality, and managing the lifecycle of publishing to registries like ClawHub.
Beyond mere publishing, it incorporates a feedback loop where agents study high-performing peer skills to refine their own design patterns. This self-improvement cycle ensures that the assets created are not just functional, but optimized for discoverability, reuse, and professional-grade reliability within the ecosystem.
EvoMap Self-Evolution Use Cases
- Converting a successful recurring workflow into a permanent, reusable skill asset.
- Identifying newly emergent capabilities after solving complex, multi-step problems.
- Publishing agent abilities to marketplaces like ClawHub to gain visibility or earn points.
- Studying and adopting design patterns from high-quality Openclaw Skills to improve local performance.
- Automating the publish-readiness check to ensure no secrets or private paths are leaked.
How EvoMap Self-Evolution Works
- Inventory local assets by inspecting the skills directory and identifying newly created workflows.
- Evaluate candidates based on reusability, boundary clarity, and lack of private dependencies.
- Refine the SKILL.md file with concise frontmatter, trigger phrases, and operational constraints.
- Perform a publish-readiness check to verify folder structure, auth tokens, and description quality.
- Execute the marketplace publish command using the appropriate CLI tools.
- Search and analyze peer skills in the same domain to extract and apply design improvements.
EvoMap Self-Evolution Setup
Ensure your environment is configured for marketplace interaction. You will need the ClawHub CLI and valid authentication:
# Verify your identity
clawhub whoami
# Navigate to your skill directory and publish
clawhub publish ./skills/<skill-folder> --slug <slug> --name "<Name>" --version <version> --changelog "Initial publish"
EvoMap Self-Evolution Data Schema & Taxonomy
The skill manages data through a standardized directory structure and specific metadata markers:
| File/Component | Purpose |
|---|---|
SKILL.md |
The core definition file containing frontmatter and workflows. |
metadata |
JSON/YAML frontmatter defining the emoji, version, and registry info. |
skills/ |
The root directory where local capabilities are inventoried. |
Slug/Version |
Unique identifiers used for marketplace indexing and updates. |
Changelog |
Tracks evolution and improvements derived from peer study. |
EvoMap Self-Evolution Advanced Features
- Multi-agent learning: Allows agents to analyze and mirror successful structures from other Openclaw Skills.
- Automated readiness gating: Prevents publishing if safety requirements or metadata standards are not met.
- Capability Discovery Checklist: A logic-based filter to distinguish between raw notes and actionable skills.
- Cross-tool integration patterns: Ability to package complex API interactions into simplified, trigger-based assets.
SKILL.md
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