Capability Awareness System

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.