✨ SkillClaw: Let Skills Evolve Collectively with Agentic Evolver ✨

What SkillClaw Brings to One Hermes User

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 Duplicates, outdated ones, half-baked ones all piled together like an unsorted loot box.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:

Multiple agents? One unified skill library.

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.

Multiple devices? Skills follow you, not your machine.

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.

Collective Skill Evolution

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.

News

• 2026/04/22 — Added a bilingual dashboard with skillclaw dashboard sync and skillclaw dashboard serve for inspecting local/shared skills, validation progress, version history, and session traces.
• 2026/04/20 — Added Codex and Claude Code integration with proxy auto-configuration, native skills-directory defaults, and doctor / restore commands.
• 2026/04/17 — Added QwenPaw integration and updated the docs for broader multi-agent compatibility.
• 2026/04/17 — Added full Hermes integration, per-turn skill tracking, doctor hermes, skillclaw skills * management commands, and a major docs overhaul.
• 2026/04/14 — WeChat discussion group is live! Join the group to chat with us.
• 2026/04/14 — Initial Hermes support landed together with the first README refresh.
• 2026/04/12 — Active discussion with Deer-Flow on cross-framework skill sharing.
• 2026/04/11 — SkillClaw ranked #2 Paper of the Day on Hugging Face Daily Papers!
• 2026/04/10 — SkillClaw is now open source! Code released on GitHub.

Overview

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:

1. 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.

2. 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 editing

Both components share the same storage layer (Alibaba OSS / S3 / local filesystem) and skill format (SKILL.md).

Deployment Model

Start with just the client. Add the server when you need it.

1. Single user + auto-evolution: Install the client proxy, then add an evolve server on the same machine (or anywhere that can reach your storage) to automatically refine skills in the background.
2. Team / shared group: Point multiple clients at the same shared storage and run one 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:

• If you only want to use SkillClaw yourself, install the client first. You can add an evolve server later.
• If you want to join an existing team, you still install only the client. You do not run the evolve server unless you are operating the shared group.
• The evolve server can run on the same laptop, a remote VM,