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PythonReactSEOPDF
OpenClaw

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.

gmickel0 installations selon la source☆ 0 Étoiles du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install gmickel/gno

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

GNO - Local Knowledge Engine

Fast local semantic search. Index once, search instantly. No cloud, no API keys.

When to Use This Skill

  • User asks to search files, documents, or notes
  • User wants to find information in local folders
  • User needs to index a directory for searching
  • User mentions PDFs, markdown, Word docs, code to search
  • User asks about knowledge base or RAG setup
  • User wants semantic/vector search over their files
  • User needs to set up MCP for document access
  • User wants a web UI to browse/search documents
  • User asks to get AI answers from their documents
  • User wants to tag, categorize, or filter documents
  • User asks about backlinks, wiki links, or related notes
  • User wants to visualize document connections or see a knowledge graph

Quick Start

gno init                              # Initialize in current directory
gno collection add ~/docs --name docs # Add folder to index
gno index                             # Build index (ingest + embed)
gno search "your query"               # BM25 keyword search

Command Overview

Category Commands Description
Search search, vsearch, query, ask Find documents by keywords, meaning, or get AI answers
Links links, backlinks, similar, graph Navigate document relationships and visualize connections
Retrieve get, multi-get, ls Fetch document content by URI or ID
Index init, collection add/list/remove, index, update, embed Set up and maintain document index...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/gmickel/gno
Version
—
Commit
4da9c988717091b9dec50b145ca1e3cde835c704
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

Contenu extrait

SKILL.md
# GNO - Local Knowledge Engine

Fast local semantic search. Index once, search instantly. No cloud, no API keys.

## When to Use This Skill

- User asks to **search files, documents, or notes**
- User wants to **find information** in local folders
- User needs to **index a directory** for searching
- User mentions **PDFs, markdown, Word docs, code** to search
- User asks about **knowledge base** or **RAG** setup
- User wants **semantic/vector search** over their files
- User needs to **set up MCP** for document access
- User wants a **web UI** to browse/search documents
- User asks to **get AI answers** from their documents
- User wants to **tag, categorize, or filter** documents
- User asks about **backlinks, wiki links, or related notes**
- User wants to **visualize document connections** or see a **knowledge graph**

## Quick Start

```bash
gno init                              # Initialize in current directory
gno collection add ~/docs --name docs # Add folder to index
gno index                             # Build index (ingest + embed)
gno search "your query"               # BM25 keyword search
```

## Command Overview

| Category     | Commands                                                         | Description                                               |
| ------------ | ---------------------------------------------------------------- | --------------------------------------------------------- |
| **Search**   | `search`, `vsearch`, `query`, `ask`                              | Find documents by keywords, meaning, or get AI answers    |
| **Links**    | `links`, `backlinks`, `similar`, `graph`                         | Navigate document relationships and visualize connections |
| **Retrieve** | `get`, `multi-get`, `ls`                                         | Fetch document content by URI or ID                       |
| **Index**    | `init`, `collection add/list/remove`, `index`, `update`, `embed` | Set up and maintain document index...

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