Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
Fix upload/search compatibility with current Raysurfer SDK fields
What This Skill Does
Code Cache stores code generated by AI agents and retrieves it when a similar task comes up later. It uses semantic search to match task descriptions, so agents reuse validated solutions instead of regenerating them from scratch.
Retrieving proven code from a semantic cache is faster and cheaper than asking an LLM to regenerate the same solution on every run.
When to use it
- Reusing a data pipeline script across multiple agent runs
- Retrieving a chart-building snippet for recurring reports
- Skipping LLM generation when fetching GitHub trending repos again
- Searching cached solutions before starting a new automation task
- Rating cached code to improve future retrieval accuracy
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Fetch GitHub trending repos
- 1Runs /code-cache search 'Fetch GitHub trending repos' --show-code to check for a match
- 2Finds a cached snippet with a verdict score above the threshold
- 3Retrieves execution-ready files via /code-cache files 'Fetch GitHub trending repos'
- 4Executes the cached code without LLM generation
- 5Votes on the result with /code-cache vote <id> --up if the output is correct
GitHub trending repos fetched using a cached script, no token generation required
Requirements
Accounts, API keys, or tools you or your AI assistant may need to set up while using this skill.