AMAP-ML/SkillClaw

Health v2 · maintenance only

Flags: no_releases young

Adoption not part of the score

2514 stars · 248 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

SkillClaw is a Python-based framework that lets AI agent skills evolve collectively from real interactions across sessions, agents, devices, and users. It integrates with agent platforms like Hermes, OpenClaw, and Codex, running a background daemon that improves skills automatically as users chat.

Use cases

• make my ai agent learn skills from conversations automatically
• share learned skills across multiple agents and devices
• continually improve agent capabilities without retraining
• set up a self-evolving skill system for hermes or openclaw agents
• run a background daemon that evolves agent skills from usage
• build agents with collective intelligence across users

When to choose

• you want agent skills to improve from real interactions without manual curation
• you use a supported agent platform like Hermes, OpenClaw, or Codex
• you need skill sharing across sessions, agents, devices, or users
• you prefer a lightweight install-and-chat workflow with background evolution

When to avoid

• you need a fully deterministic, auditable agent behavior with no runtime skill changes
• your agent stack is incompatible with the supported integrations
• you require formal guarantees or evaluation of learned skills before deployment
• you only need static prompt templates rather than evolving skills

Facets

library · maturity active

agent-framework llm-training machine-learning sdk large-language-models machine-learning developer-tools python windows cli skill-learning continual-learning self-evolving-agents collective-intelligence agentic-evolver openclaw hermes ai-agents macos linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="AMAP-ML/SkillClaw")