Find knowledge base entries similar to a given entry by comparing tags and content. Returns related contexts ranked by similarity score. Useful for discovering related patterns, examples, or documentation after finding one relevant entry.

Search saved contexts by keyword or natural language query. Returns matching context summaries ranked by relevance using hybrid keyword + semantic search. Searches across titles, reasoning, code snippets, file paths, and commit SHAs. Results include local contexts and (if authenticated) cloud workspace contexts including team-shared contexts. Use for finding past decisions, understanding why code was written, or discovering relevant prior work. Use gitwhy_get <context_id> to read the full context. CLI alternative: `git why search "<query>"`.

Get a Star Wars film by its numeric ID. Returns title, episode number, director, producer, release date, and opening crawl.

Submit a URL for NHS to crawl and score. Use when you discover an agent-first tool, API, or service that isn't in the index yet. NHS will fetch the site, check its 7 agentic signals (llms.txt, ai-plugin.json, OpenAPI, structured API, MCP server, robots.txt AI rules, Schema.org), compute a score, and add it to the index. The site becomes searchable within a few seconds if the crawl succeeds.

Upload local contexts to the GitWhy cloud as private (not shared with team). Use after saving contexts locally to back them up to the cloud. Synced contexts remain private until explicitly published with gitwhy_publish. CLI alternative: `git why push <context-id>` (syncs specified contexts as private).

List available context checkpoints. Shows all saved contexts available for multi-agent workflows. Args: limit: Maximum number of contexts to return (default 20, max 100) offset: Number of contexts to skip for pagination (default 0) name_pattern: Filter contexts by name (case-insensitive substring match) include_descriptions: Include full descriptions in output (default False for compact listing) ctx: MCP context (automatically provided) Returns: Dict with list of available contexts and their details Examples: >>> await list_contexts() {'success': True, 'total': 3, 'contexts': [...]} >>> await list_contexts(limit=5, name_pattern='investigation') {'success': True, 'total': 2, 'contexts': [...]}