gmickel/gno

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
• User wants to export a note or collection for gno.sh publishing

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 | | Publish | publish export | Export gno.sh publish artifacts | | 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 (search/vsearch/query/ask)

-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
--since <date>        Modified after date (ISO: 2026-03-01)
--until <date>        Modified before date (ISO: 2026-03-31)
--exclude <terms>     Exclude docs containing any term (comma-separated)
--intent <text>       Disambiguate ambiguous queries (e.g. "python" = language not snake)
--json                JSON output
--files               URI list output
--line-numbers        Include line numbers

Advanced: Structured Query Modes (query/ask only)

Use --query-mode to combine multiple retrieval strategies in one query (repeatable):

# Combine keyword + hypothetical document
gno query "API rate limiting" \
  --query-mode "term:rate limit" \
  --query-mode "hyde:how to implement request throttling"

# Add intent steering
gno query "python" \
  --query-mode "term:python" \
  --query-mode "intent:programming language"

Modes: term:<text> (keyword), intent:<text> (disambiguation), hyde:<text> (hypothetical doc for semantic matching). Max one hyde per query.

Document Retrieval

# Full document by URI
gno get gno://work/readme.md

# By document ID
gno get "#a1b2c3d4"

# Specific line range: --from <start> -l <count>
gno get gno://work/report.md --from 100 -l 20

# With line numbers
gno get gno://work/report.md --line-numbers

# JSON output with capabilities metadata
gno get gno://work/report.md --json

# Multiple documents
gno multi-get gno://work/doc1.md gno://work/doc2.md

Editable vs read-only: gno get --json returns a capabilities field showing whether a document is editable at its source. Markdown and plain text files are editable in place. Converted documents (PDF, DOCX, XLSX) are read-only -- to edit their content, create a new markdown note instead of overwriting the binary source.

Search Then Get (common pipeline)

# Search, get full content of top result
gno query "auth" --json | jq -r '.results[0].uri' | xargs gno get

# Get all results
gno search "error handling" --json | jq -r '.results[].uri' | xargs gno multi-get

MCP Retrieval Strategy

When using GNO through MCP, prefer this retrieval order:

1. Check gno_status first when freshness, missing vectors, or stale results are plausible.
2. Use gno_query first for normal content questions. It returns snippets plus uri, docid, and often line; pass graph: true only when linked context is worth the extra latency.
3. Use graph/link expansion for relationship context: gno_graph_neighbors for nearby documents, gno_graph_path for "how are X and Y connected?", gno_links/gno_backlinks for one-document link expansion, and gno_similar for semantic neighbors. Prefer explicit graph edges over inferred, ambiguous, or similarity edges when confidence matters.
4. Use gno_get with fromLine/lineCount for targeted reads, or gno_multi_get to batch top refs.

Use narrower tools when the request tells you to:

• gno_search: exact phrase, filename, identifier, stack trace, error text
• gno_vsearch: conceptual similarity when exact wording differs
• gno_status: stale results, missing embeddings, vector unavailable
• gno_graph: graph report/stats, hubs, isolates, unresolved links, edge confidence/audit, communities, unfamiliar corpus overview
• gno_graph_neighbors: relationship/corpus-navigation questions around a known document
• gno_graph_path: "how are X and Y connected?" questions

For ambiguous terms, pass intent instead of bloating the query text. For typed retrieval, use queryModes: term for lexical anchors, intent for disambiguation, one hyde for a hypothetical answer/document.

Document Links & Similarity

# Outgoing links from a document
gno links gno://notes/readme.md

# Find documents linking TO a document (backlinks)
gno backlinks gno://notes/api-design.md

# Find semantically similar documents
gno similar gno://notes/auth.md

# Similar across all collections (not just same collection)
gno similar gno://notes/auth.md --cross-collection

# Stricter threshold (default: 0.7)
gno similar gno://notes/auth.md --threshold 0.85

# Knowledge graph
gno graph --json
gno graph -c notes --similar   # Include similarity edges
gno graph --neighbors gno://notes/auth.md
gno graph --from gno://notes/a.md --to gno://notes/b.md

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

Non-default index search results may include ?index=<name> on gno:// URIs. Keep that query string when passing the URI to gno get.

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)
gno embed travel       # Embed one collection only
# or
gno embed --collection travel

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

Collection-specific embedding models

Collections can override the global embedding model with models.embed.

CLI path:

gno collection add ~/work/gno/src \
  --name gno-code \
  --embed-model "hf:Qwen/Qwen3-Embedding-0.6B-GGUF/Qwen3-Embedding-0.6B-Q8_0.gguf"

Good default guidance:

• keep the global preset for mixed notes/docs collections
• use a collection-specific embed override for code-heavy collections when benchmark guidance says so
• after changing an embed model on an existing populated collection, run:

gno embed --collection gno-code

If you want to remove old vectors after switching:

gno collection clear-embeddings gno-code        # stale models only
gno collection clear-embeddings gno-code --all  # remove everything, then re-embed

MCP-equivalent write tool:

• gno_clear_collection_embeddings

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 |