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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| 🚀 Quick Install | 💬 Just Chat | 🔌 Broad Compatibility | 🧬 Collective Skill Evolution | |:-:|:-:|:-:|:-:|
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 Duplicates, outdated ones, half-baked ones all piled together like an unsorted loot box.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 (local, oss, or s3). This means: