gno
Search local documents, files, notes, and knowledge bases. Index directories, search with BM25/vector/hybrid, get AI answers with citations. Use when user wants to search files, find documents, query notes, look up information in local folders, index a directory, set up document search, build a knowledge base, needs RAG/semantic search, or wants to start a local web UI for their docs.
Why use this skill?
Transform your local files into a searchable, AI-powered knowledge base with GNO. Private, offline, and semantic search for documents, notes, and code.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/nicoataiza/gno-bak-2026-01-28t18-01-20-10-30What This Skill Does
GNO is a comprehensive Local Knowledge Engine designed for OpenClaw. It functions as a powerful RAG (Retrieval-Augmented Generation) system that runs entirely on your local machine, ensuring complete data privacy by eliminating the need for cloud uploads or external API calls for indexing. It allows you to transform local folders—containing PDFs, markdown notes, source code, or documents—into a searchable, semantic knowledge base. With hybrid search capabilities (combining BM25 for keyword accuracy and vector embeddings for semantic context), GNO enables you to retrieve information based on meaning rather than just keywords. Furthermore, it provides sophisticated tools for managing document relationships, including backlink analysis and knowledge graph visualization, alongside a built-in web interface for seamless document exploration.
Installation
To integrate GNO into your OpenClaw environment, use the provided installation command via your terminal:
clawhub install openclaw/skills/skills/nicoataiza/gno-bak-2026-01-28t18-01-20-10-30
Once installed, initialize your local directory using gno init, then add your desired document folders using gno collection add <path> --name <collection_name>. Finally, trigger the indexing process with gno index to begin building your semantic search database.
Use Cases
GNO is ideal for users who manage large quantities of personal or professional documentation and want to query their data using AI. Common scenarios include: searching through extensive technical documentation or codebases, maintaining a 'second brain' via Obsidian or Notion markdown exports, performing research tasks where you need to synthesize information from multiple local PDFs, and managing project-specific knowledge bases that require strict offline privacy. It is also perfect for users needing a visual overview of how their notes and files connect to one another.
Example Prompts
- "GNO, search my project notes for any mention of the authentication flow and provide a summary of how the token refresh logic works."
- "Can you index my downloads folder and tell me what the latest whitepaper says about the new database architecture?"
- "Open the web interface for my current knowledge base and show me the network graph of how these documents are linked."
Tips & Limitations
For optimal performance, ensure your document directory is clean and free of unnecessary build artifacts. Use 'context' tags to help the AI understand the relevance of specific directories if search results feel too broad. Note that while GNO is highly efficient, the initial indexing process for large repositories can be resource-intensive depending on your CPU/GPU hardware. Always run 'gno doctor' if you encounter issues with search accuracy or index corruption to verify system health.
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-nicoataiza-gno-bak-2026-01-28t18-01-20-10-30": {
"enabled": true,
"auto_update": true
}
}
}Tags(AI)
Flags: file-read, file-write
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