Query a document

Ranked search over an already-extracted text or Markdown file. You give it a natural-language query; it returns the most relevant line windows (with line numbers), not the whole document. This is the "parse once, then query the file" pattern: convert a PDF a single time, then ask as many questions as you like against the cheap, local text.

This is built for agent economy. A converted document can be tens of thousands of lines and will blow out your context window if you read it back. Querying returns only the handful of passages that matter, with line numbers you can use for a precise follow-up read.

When to use this

• Use query when you have a converted file and a question — "what's the termination clause", "where are the FY24 revenue figures", "does this mention indemnification". It ranks every line and hands back the best windows.
• Use pdf-to-markdown / pdf-to-text first to produce the file. query does not parse PDFs; it searches their extracted text.
• Don't read the whole converted file into context to find one thing, and don't run grep after grep — that's what this replaces. One ranked query beats many exact-match passes when you don't know the document's exact wording.

Related Nutrient skills

query searches a file a converter already produced, so you'll usually want one of these too — add it the way your agent installs skills (they install separately but share the same underlying binary):

• pdf-to-markdown — PDF → structured Markdown (headings, lists, tables); best for most RAG / LLM-context work.
• pdf-to-text — PDF → layout-preserving plain text; best when column/tabular alignment must survive.