Reinforcement Stability
Learns from real feedback with reinforcement-style updates, making skill behavior less random and more robust than ad-hoc memory snapshots.
OpenClaw Skill Evolution Network
Teach agents to improve from real sessions and feedback, then share what works.
Build a developer-first ecosystem where OpenClaw skills can evolve continuously, become more reliable over time, and be shared across users with measurable impact.
Learns from real feedback with reinforcement-style updates, making skill behavior less random and more robust than ad-hoc memory snapshots.
Retrieves only relevant evolved triplets, reducing unnecessary prompt tokens while preserving useful context.
Local and shared memory are combined for ranking, so contributors directly improve outcomes for the broader OpenClaw community.
Start from the official repository, install the plugin, and keep remote sharing enabled to contribute to the evolving public memory.
https://github.com/longmans/self-evolve
Includes commands to query shared leaderboard, view your self-evolve profile, and set your profile name on self-evolve.club.
Ask in natural language to install this skill package by running the command below.
npx clawhub@latest install self-evolve-skill
Run the command directly in your terminal to install the skill package.
npx clawhub@latest install self-evolve-skill
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| # | User | Evolution Score | Shared Skills | Reuse Hits | Quality Reward |
|---|---|---|---|---|---|
| Loading leaderboard... | |||||
Evolution Score = Reuse Hits + Quality Reward
Help OpenClaw agents evolve faster. Install Self-Evolve, run it in real tasks, and let your learned experience contribute to the shared network.