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Automated security scan — not a certification.
by AMAP-ML
Let Skills Evolve Collectively with Agentic Evolver
# Add to your Claude Code skills
git clone https://github.com/AMAP-ML/SkillClawLast scanned: 5/1/2026
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"status": "PASSED",
"scannedAt": "2026-05-01T06:38:32.302Z",
"semgrepRan": false,
"npmAuditRan": true,
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}See how SkillClaw compares with popular alternatives.
SkillClaw is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by AMAP-ML. Let Skills Evolve Collectively with Agentic Evolver. It has 2,691 GitHub stars.
Yes. SkillClaw passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/AMAP-ML/SkillClaw" and add it to your Claude Code skills directory (see the Installation section above).
SkillClaw is primarily written in Python. It is open-source under AMAP-ML on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh SkillClaw against similar tools.
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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
Automated security scan — not a certification.
| 🚀 Quick Install | 💬 Just Chat | 🔌 Broad Compatibility | 🧬 Collective Skill Evolution |
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Been using Hermes for a while — is your skill library still a mess? Duplicates, outdated ones, half-baked ones all piled together like an unsorted loot box. The problem isn't that Hermes doesn't learn enough — it's that nobody helps it digest.
SkillClaw is built for this. Auto-evolve, auto-deduplicate, auto-improve quality. It won't change how you work or interrupt your flow — it just quietly rewrites your agent's growth curve.
SkillClaw doesn't make Hermes learn more — it makes everything Hermes has learned actually count.
That's just one user's story. One user can also run multiple agents or use multiple devices — SkillClaw unifies them all:
Running multiple Hermes agents for different tasks? Without SkillClaw, each builds its own isolated skill silo. With SkillClaw, skills are merged, deduplicated, and cross-pollinated into a unified library, then distributed back to all agents. Your Frontend agent's React patterns make the Backend agent's API design better — and vice versa.
Same user, different machines. Your Home Hermes learns React; your School Hermes learns ML; your Work Hermes learns K8s. Without SkillClaw, each starts from scratch. With it, skills unify across all environments — every Hermes instance benefits from every other's experience, regardless of where you are.
Everything above is what one user gets. Now scale it up: when you join a shared group, every team member's real-world experience feeds into the same evolution loop. User A debugs a database issue — the skill evolves. User B, C, D benefit instantly without ever hitting the same problem. N users, one Skill, continuous evolution.
skillclaw dashboard sync and skillclaw dashboard serve for inspecting local/shared skills, validation progress, version history, and session traces.doctor / restore commands.doctor hermes, skillclaw skills * management commands, and a major docs overhaul.SkillClaw makes LLM agents progressively better by evolving reusable skills from real session data. A single user already benefits — skills are automatically deduplicated, improved, and verified across sessions. Scale up when you're ready: multiple agents, multiple devices, or multiple users can all feed the same evolution loop.
The system has two components:
Client Proxy — A local API proxy (/v1/chat/completions, /v1/messages) that intercepts agent requests, records session artifacts, and manages your local skill library. This is all you need to get started.
Evolve Server (evolve_server) — An optional service that reads session data from shared storage, evolves or creates skills, and writes them back. Add it when you want automatic evolution or team-wide sharing. It supports two engines:
workflow: fixed 3-stage LLM pipeline (Summarize → Aggregate → Execute)agent: OpenClaw-driven agent workspace with direct skill editingBoth components share the same storage layer (Alibaba OSS / S3 / local filesystem) and skill format (SKILL.md).
Start with just the client. Add the server when you need it.
skillclaw-evolve-server for the group. Everyone's experience feeds the same evolution loop.The client and server only meet through shared storage (`l