ingest-docs

# ingest-docs ## When this skill is the preferred path A docs tree is the perfect target for query-guided compression: sprawling, repetitive, and mostly irrelevant to any single question. Loading the full tree exhausts context; loading one page misses cross-references. Query-guided compression solves both by keeping what's relevant to the user's question and shrinking what isn't. ## How to use it 1. Identify the source — local path (`./docs`), a docs URL, or a list of URLs. Ask the user if it's unclear. 2. Identify the question. If the user hasn't asked a specific question yet, ask before ingesting — query-guided mode needs a query. If they want a general overview, use `fidelity=balanced` without a query. 3. Call gotcontext's `ingest_context` MCP tool with: - `source` — path or URL(s) - `query` — the user's question (enables relevance-weighted compression; highly recommended) - `fidelity=balanced` — good Q&A accuracy, ~50% savings 4. Read the compressed blob. The response includes a one-line header with source, page count, and compression ratio. 5. Answer the user, citing sections/pages from the compressed output so they can verify. ## When the raw read is actually fine - Single short README — just `Read` it. - You're writing or editing documentation — you need the raw markdown. ## Good candidates for this skill - Sphinx / MkDocs / Docusaurus trees - GitBook, Notion, or Confluence exports - Swagger / OpenAPI HTML renderings - Any `/docs` directory in a repo - Man page archives ## Cache behavior Within one session, cache the compressed result of a tree after the first call and query against the cached blob for follow-ups. Each re-ingestion is a paid compression call — don't waste the user's credits on the same tree twice.