GNO - Local Knowledge Engine

VerifiedSafe

GNO is a local knowledge engine for searching documents, notes, and files using keyword, semantic, or hybrid search. It indexes directories and provides AI-generated answers with citations. Use it when you need to find information in local folders, build a knowledge base, or set up document search without cloud dependencies.

Sby Skills Guide Bot
Data & AIIntermediate
6/2/2026
Claude Code
#local-search#semantic-search#rag#document-indexing#knowledge-base

Recommended for

Automated summary

GNO is a local semantic search engine that indexes documents (PDFs, Markdown, code, etc.) and supports keyword, vector, and hybrid search, including AI-generated answers with citations—all without cloud or API keys.

Strengths

  • Fully local operation ensuring data privacy and offline capability
  • Multiple search modes (BM25, vector, hybrid) with speed/accuracy trade-offs
  • Built-in web UI for browsing and searching documents
  • Supports collections, tags, and context hints to refine search results

Limitations

  • Requires initial indexing which can be time-consuming for large document sets
  • Local AI models may be less accurate than cloud-based alternatives
  • AI answer quality depends on the model and context provided
When to use it

Use GNO when you need to quickly search through a large local document collection, perform semantic searches, or get AI answers grounded in your own files.

When not to use it

Avoid GNO if your documents are primarily cloud-hosted, you don't need advanced search capabilities, or the initial indexing overhead isn't justified for infrequent queries.

Security analysis

Safe
Quality score92/100

The skill only describes usage of a local search tool (gno) using allowed Bash(gno:*) commands, which are restricted to gno-specific operations. There is no execution of arbitrary code, no data exfiltration, no destruction, and no safety bypasses. The tool operates locally and doesn't involve cloud services or external network calls.

No concerns found

How this analysis is made

Examples

Search documents semantically
Search my notes folder for documents about machine learning, using semantic search to find related concepts.
Index and ask questions
Index the ~/docs directory with GNO, then ask it to summarize the key findings from the project reports and provide citations.
Set up a knowledge base
Set up GNO to index all markdown files in my knowledge base, add relevant tags, and start the web UI so I can browse and search.

name: 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 |

From the file to a first result

The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.

View the source and supporting files

This download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.

1. Download the file

Download SKILL.md

From the root of a test project, save the file as .skill-downloads/gno-local-knowledge-engine-mm5t8ate/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.

Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.

mkdir -p '.skill-downloads/gno-local-knowledge-engine-mm5t8ate' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/gno-local-knowledge-engine-mm5t8ate/download' --output '.skill-downloads/gno-local-knowledge-engine-mm5t8ate/SKILL.md.part' && mv '.skill-downloads/gno-local-knowledge-engine-mm5t8ate/SKILL.md.part' '.skill-downloads/gno-local-knowledge-engine-mm5t8ate/SKILL.md'

2. Check prerequisites

Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.

Tools declared by the author (check availability in your agent): Bash(gno:*) Read

No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.

The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.

3. Load the skill

After inspection, copy the complete folder into your project using one of the commands below, then open a new tool session. The command stops if a folder with the same name already exists: compare the files before replacing it.

Claude Code
test -f '.skill-downloads/gno-local-knowledge-engine-mm5t8ate/SKILL.md' && test -s '.skill-downloads/gno-local-knowledge-engine-mm5t8ate/SKILL.md' && mkdir -p '.claude/skills' && test ! -e '.claude/skills/gno' && cp -R '.skill-downloads/gno-local-knowledge-engine-mm5t8ate' '.claude/skills/gno'

OpenSkills

OpenSkills must already be installed. The local install/read procedure is checked with OpenSkills 1.5.0, which requires Node.js ≥ 20.6.0. Catalog slugs are not resolved automatically.

Official OpenSkills installation
openskills install './.skill-downloads/gno-local-knowledge-engine-mm5t8ate'

openskills read 'gno-local-knowledge-engine-mm5t8ate'

Reading should display the installed file content and its base directory. It does not run the skill or install its dependencies.

For an agent that reads AGENTS.md, then sync the index. This command changes AGENTS.md: review the diff before using it.

openskills sync

Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.

4. Try a first task

Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:

Read .skill-downloads/gno-local-knowledge-engine-mm5t8ate/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.

Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.

Related skills