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Gno.Bak 2026 01 28T18:01:20+10:30

GNO 是本地知识引擎技能:用 gno CLI 初始化并索引本地目录(PDF、Markdown、Word、代码等),通过关键词、向量或混合查询检索,获取带引用的 AI 答案,并可管理标签、集合、反向链接与知识图谱,支持 Web UI 浏览和 MCP 接入 AI 助手。数据与模型均在本地,无需云端或 API key。

nicoataiza
nicoataiza
热度 74.03
最近更新 2026-05-17 11:07:55
分类:搜索依赖:代码执行 / 读写文件 / MCP 服务 / 内部调用大模型应用场景:研究 / 笔记整理 / 工作流 / API 集成

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add gno-bak-2026-01-28t18-01-20-10-30
Metadata
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
  • 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
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, vec, 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

Important: Embedding After Changes

If you edit/create files that should be searchable via vector search:

gno index              # Full re-index (sync + embed)
# or
gno embed              # Embed only (if already synced)

MCP gno.sync and gno.capture do NOT auto-embed. Use CLI for embedding.

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