raysurfer

What This Skill Does

The Raysurfer skill integrates a powerful code caching and retrieval system into the OpenClaw AI agent framework. Its primary purpose is to eliminate redundant coding efforts by surfacing verified, community-vetted, and previously executed code snippets. By searching the Raysurfer API before initiating new tasks, the agent can reuse high-quality solutions, accelerate development cycles, and ensure that proven logic is prioritized over fresh generation. When a cache hit occurs, the agent evaluates the code against the current project requirements, adapts it, and verifies its execution, ensuring both speed and accuracy. If the agent generates new code, the skill facilitates uploading that solution to the global cache, contributing to a collective intelligence database that benefits all users of the platform.

Installation

To enable the Raysurfer skill in your OpenClaw environment, execute the following command in your terminal:

clawhub install openclaw/skills/skills/ryx2/raysurfer

Ensure that you have set the RAYSURFER_API_KEY environment variable in your system configuration. This key is mandatory for authorizing API requests to the Raysurfer backend and is required for both searching the cache and contributing new code blocks.

Use Cases

• Boilerplate Reduction: Automatically retrieve boilerplate setups for common web scrapers, data processing pipelines, or API integrations.
• Complex Algorithm Reuse: Quickly access optimized implementations of common algorithms (e.g., sorting, graph traversal, or mathematical conversions) that have been previously battle-tested.
• Standardization: Ensure team-wide adherence to specific coding patterns by surfacing preferred implementation styles from the cache.
• Error Mitigation: Leverage snippets that have a high 'thumbs up' ratio to reduce the likelihood of encountering bugs in routine implementation tasks.

Example Prompts

1. "Raysurfer, look for a Python script that calculates the moving average of a time-series CSV file and apply it to the data.csv in my current folder."
2. "I need to authenticate with the GitHub API. Check the cache for a reliable OAuth2 implementation before writing the code from scratch."
3. "Search for a high-rated script to perform batch resizing on images in the /assets directory. If you find a good one, use it; otherwise, write a robust Pillow-based solution and upload it to Raysurfer."

Tips & Limitations

• Always Verify: Even with high combined scores, cached code should always be verified within the context of your specific directory structure and local dependencies.
• Refine Searches: Use descriptive task names in your search queries to improve the relevance of the retrieved code_block results. Adding specific context (like libraries used) can significantly improve your combined_score.
• Contribute Back: When you fix a bug in cached code or create a novel, high-performing solution, ensure you follow the upload workflow. This keeps the cache healthy and increases the likelihood of finding successful matches in future tasks.
• Security: Be mindful that cached code is shared. Always review downloaded code for unexpected system calls or malicious imports before execution, even if the code has a high success rating.