Code Cache - Semantic Code Caching for AI Agents

This skill enables semantic code caching via the Raysurfer API.

What It Does

When your agent generates and executes code, Code Cache stores it. When a similar task comes up later, the agent can retrieve and run the cached code instead of regenerating it—saving time and tokens.

Setup

Get your API key from the Raysurfer dashboard and configure it:

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Available Commands

Search for cached code

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Search for cached code snippets that match a natural language task description.

Options:

• - --top-k N — Maximum number of results (default: 5)
• INLINECODE1 — Minimum verdict score filter (default: 0.3)
• INLINECODE2 — Display the source code of the top match

Example:
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Get code files for a task

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Retrieve code files ready for execution, with a pre-formatted prompt addition for your LLM.

Options:

• - --top-k N — Maximum number of files (default: 5)
• INLINECODE4 — Output directory (default: .code_cache)

Example:
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Upload code to cache

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Upload code from an execution to the cache for future reuse.

Options:

• - --files, -f — Files to upload (required, can specify multiple)
• INLINECODE7 — Mark the execution as failed (default: succeeded)
• INLINECODE8 — Disable automatic voting on stored code blocks

Example:
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Vote on cached code

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Vote on whether cached code was useful. This improves retrieval quality over time.

Options:

• - --up — Upvote / thumbs up (default)
• INLINECODE10 — Downvote / thumbs down
• INLINECODE11 — Original task description (optional)
• INLINECODE12 — Code block name (optional)
• INLINECODE13 — Code block description (optional)

Example:
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How It Works

1. 1. Cache Hit: When you ask for code similar to something previously executed, Code Cache returns the cached version instantly
2. Cache Miss: When no match exists, your agent generates code normally, then Code Cache stores it for future use
3. Verdict Scoring: Code that works gets 👍, code that fails gets 👎—retrieval improves over time

API Reference

The skill wraps these Raysurfer API methods:

Why Code Caching?

LLM agents repeat the same patterns constantly. Instead of regenerating code every time:

• - 30x faster: Retrieve proven code instead of waiting for generation
• Lower costs: Reduce token usage by reusing cached solutions
• Higher quality: Cached code has been validated and voted on
• Consistent output: Same task = same proven solution

Learn more at raysurfer.com or read the documentation.