Notre avis
GNO est un moteur de recherche local qui indexe des documents et permet des recherches sémantiques ou par mots-clés, avec réponses IA et citations.
Points forts
- Recherche instantanée après indexation, sans dépendance cloud.
- Multiples modes de recherche (BM25, vectoriel, hybride, IA) adaptés à différents besoins.
- Interface web intégrée pour naviguer et interroger les documents.
- Intégration MCP pour les assistants IA locaux.
Limites
- Nécessite une indexation initiale qui peut être longue pour de gros volumes.
- Les réponses IA nécessitent des modèles locaux à télécharger et configurer.
- Ne fonctionne que sur les fichiers présents sur la machine locale.
Utilisez GNO lorsque vous devez rechercher rapidement des informations dans des documents locaux sans les envoyer vers le cloud.
Évitez GNO si vos fichiers changent fréquemment et nécessitent une recherche en temps réel sans réindexation.
Analyse de sécurité
SûrThe skill only uses the 'gno' command, a local document indexing and search tool, with no dangerous operations, network calls, or data exfiltration.
Aucun point d'attention détecté
Exemples
Search my notes for the meeting notes from last weekIndex my research papers in ~/papers and then search for machine learning methodsSet up a local document search system for my project foldername: gno description: 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. allowed-tools: Bash(gno:*) Read
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
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 |
| 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 |
| Tags | tags, tags add, tags rm | Organize and filter documents |
| Context | context add/list/rm/check | Add hints to improve search relevance |
| Models | models list/use/pull/clear/path | Manage local AI models |
| Serve | serve | Web UI for browsing and searching |
| MCP | mcp, mcp install/uninstall/status | AI assistant integration |
| Skill | skill install/uninstall/show/paths | Install skill for AI agents |
| Admin | status, doctor, cleanup, reset, completion | Maintenance and diagnostics |
Search Modes
| Command | Speed | Best For |
| ---------------------- | ------- | ---------------------------------- |
| gno search | instant | Exact keyword matching |
| gno vsearch | ~0.5s | Finding similar concepts |
| gno query --fast | ~0.7s | Quick lookups |
| gno query | ~2-3s | Balanced (default) |
| gno query --thorough | ~5-8s | Best recall, complex queries |
| gno ask --answer | ~3-5s | AI-generated answer with citations |
Retry strategy: Use default first. If no results: rephrase query, then try --thorough.
Common Flags
-n <num> Max results (default: 5)
-c, --collection Filter to collection
--tags-any <t1,t2> Has ANY of these tags
--tags-all <t1,t2> Has ALL of these tags
--json JSON output
--files URI list output
--line-numbers Include line numbers
Global Flags
--index <name> Alternate index (default: "default")
--config <path> Override config file
--verbose Verbose logging
--json JSON output
--yes Non-interactive mode
--offline Use cached models only
--no-color Disable colors
--no-pager Disable paging
Reference Documentation
| Topic | File | | ----------------------------------------------------- | ------------------------------------ | | Complete CLI reference (all commands, options, flags) | cli-reference.md | | MCP server setup and tools | mcp-reference.md | | Usage examples and patterns | examples.md |
Ingénierie de Prompts
Data & IA
Bonnes pratiques et templates de prompt engineering pour maximiser les résultats IA.
Visualisation de Données
Data & IA
Génère des visualisations de données et graphiques adaptés à vos données.
Architecture RAG
Data & IA
Guide de configuration d'architectures RAG (Retrieval-Augmented Generation).