Capability Awareness System

Enables OpenClaw agents to discover, recognize, and access documentation for custom skills on demand with zero overhead when inactive.

Makes OpenClaw agents aware of custom skills and capabilities. Skills-first approach with on-demand documentation loading. Zero overhead when not in use. Foundation for skill marketplace discovery.

When to use: Skill discovery, capability documentation, agent self-awareness of available tools

What to know:

Repository: https://github.com/pfaria32/openclaw-capability-awareness

Problem

Default OpenClaw agents don't know about custom skills you've installed. They need to:

1. Discover what capabilities exist
2. Know when to use each skill
3. Access skill documentation on demand

Solution

Skills-First Approach:

• Agent sees skill descriptions in prompt
• Reads full SKILL.md when topic is relevant
• Zero overhead when skills not in use
• Simple, proven, low-risk

Implementation Options

Option 1: Skills-First (Recommended for v1)

Add capability cards to agent prompt:

Available Skills:
- token-economy: Model routing and cost optimization
- health-tracking: Apple Health and Strava integration
- memory-system: RAG-based semantic search

Agent reads full SKILL.md when needed.

Option 2: Full Injection (Advanced)

• Router-gated skill loading
• Dynamic prompt injection
• Context-aware capability exposure
• Zero baseline cost (only loads when relevant)

Installation

cd /home/node/.openclaw/workspace
git clone https://github.com/pfaria32/openclaw-capability-awareness.git projects/capability-awareness-system

Usage

Current Implementation (Skills-First)

Skills are documented in workspace/skills/*/SKILL.md. The agent loads these automatically through the AGENTS.md workflow:

## Skills (mandatory)
Before replying: scan <available_skills> <description> entries.
- If exactly one skill clearly applies: read its SKILL.md at <location> with `read`, then follow it.

This is already working! Just add new skills to the workspace/skills directory.

Future Implementation (Full Injection)

See repository for:

• Router design and schema
• Embedding-based skill matching
• Dynamic prompt injection strategy
• Cost/token analysis

Status

✅ Skills-First approach — Deployed and working 📋 Full Injection design — Documented, not yet implemented

Attribution

Built to support the emerging OpenClaw skill ecosystem. Simple beats clever.

Documentation

Implementation options, design decisions, and upgrade path documented in repository.