If you're running multiple LLM agents and want them to get smarter from each other's experience, this intercepts OpenAI-compatible API calls, records session artifacts, and distills them into reusable SKILL.md files that sync across your agent cluster via OSS/S3. You run a local proxy that all your agents talk through, plus an evolve server (either a fixed three-stage pipeline or an autonomous OpenClaw agent) that watches sessions and writes skills. The architecture is straightforward: proxy records, storage syncs, evolve server learns. It's designed for multi-user setups where you want collective improvement without manually curating every skill, and it ships with WildClawBench integration for benchmarking the evolution loop.
npx -y skills add aradotso/trending-skills --skill skillclaw-skill-evolution --agent claude-codeInstalls into .claude/skills of the current project.
Select a file.
juliusbrussee/caveman
mattpocock/skills
shadcn/improve
obra/superpowers
forrestchang/andrej-karpathy-skills
vercel-labs/skills