Meta Knowledge Base

AI-powered knowledge base builder that automatically captures, organizes, and retrieves information. Learns from conversations, documents, and interactions t...

This appears to be a local KB prototype rather than a production-ready ingestion agent. Before installing or enabling auto-capture: 1) Review and test the Python file in a sandbox — the code writes everything passed to add()/add_from_file() into ~/.meta_knowledge/<name>/*.json. 2) Do not enable automatic hooks (after_message, file-watch, email parsing) without auditing what data will be sent; they can cause sensitive messages/files to be stored. 3) You do not need to blindly run the pip install line: the code as shipped uses a local dummy embedding generator; installing faiss-cpu and sentence-transformers is optional and heavy — only install them if you plan to replace the stubbed embedding function with a real model and understand platform implications. 4) If you intend to use remote fetching (add_from_url) or real embeddings, inspect and modify those methods to ensure safe network behavior and to add rate-limiting, timeouts, and explicit consent. 5) If you want a production deployment, request or implement explicit filters, redaction, and access controls so the KB does not capture secrets automatically.

Type: OpenClaw Skill Name: meta-knowledge-base Version: 1.0.0 The skill bundle implements a basic local knowledge base with semantic search and RAG capabilities. The code in meta_knowledge.py manages data storage in a local directory (~/.meta_knowledge) and provides standard functionality for indexing and retrieving text content without any evidence of data exfiltration, malicious execution, or unauthorized access.