Rag Architect

RAG Architect - POWERFUL

This skill is coherent with its stated purpose and appears benign, but take these precautions before use: - Review and control which directory you give the scripts: the included code reads files recursively and will process any text/markdown files in the target path. Do not point it at sensitive directories unless you intend that. - The documentation recommends external services (OpenAI, Pinecone, etc.). Only provide API keys/credentials if you trust the integration and run the code in an environment you control. The skill itself does not request keys, so any credential sharing would be your action. - Run the scripts in an isolated or sandboxed environment (container or VM) if you want to avoid accidental access to other local data. - Inspect the full source (provided) before executing; although the visible code uses standard library file I/O and analysis, always verify there are no unexpected network calls or obfuscated code in omitted/truncated parts. - If you want stricter safety, disable autonomous invocation for this skill in your agent and call it manually after reviewing outputs and configuring credentials.

Type: OpenClaw Skill Name: rag-architect Version: 2.1.1 The 'rag-architect' skill bundle is a comprehensive and professional toolkit for designing and optimizing Retrieval-Augmented Generation (RAG) pipelines. It contains three Python scripts (chunking_optimizer.py, rag_pipeline_designer.py, and retrieval_evaluator.py) that perform document analysis and architectural recommendations using only standard Python libraries, with no network access, shell execution, or obfuscation. The extensive documentation, including SKILL.md and various reference guides, is purely educational and lacks any evidence of prompt injection or malicious instructions.