extract

Extract

Turn already-collected HTML, markdown or plain text into the JSON your next operation actually needs. You choose the schema and extraction objective. The skill binds the result to the exact source bytes, validates it with Runx's native JSON Schema engine and keeps quotations for each populated field.

Use it for documents, captured pages, application forms or research material that needs a typed handoff. This is a semantic extraction task: the agent reads the supplied document and proposes a value. Validation and provenance checks are deterministic; the model's interpretation is not claimed to be deterministic.

Choose an input lane

The default extract runner accepts content, source_ref, schema and objective. Use it when web-fetch, an artifact reader or an upstream operation has already collected the text. source_ref identifies that document or capture; it does not trigger a network request or prove the URL is current.

from-file accepts the same fields except content, plus a workspace-relative path and optional repo_root, path_scope and max_bytes. The default root is the caller workspace; path_scope: skill selects the owning package root. It uses native artifact.admit and artifact.read under fs.read authority. It requires the complete document in one bounded UTF-8 page; a larger or partial page fails before extraction. Convert PDFs, images or audio through the selected document/OCR/transcription capability first. This skill does not add a file reader, scraper or provider client.

Text is bounded to one million characters for inline input and one million bytes for a file read. The schema is a self-contained JSON Schema 2020-12, at most 256 KiB. External schema retrieval is disabled. Standard JSON Schema format keywords are annotations; a format-specific business rule needs its own check.

Procedure and proof

1. Compile the caller's schema before asking an agent to extract anything.
2. Digest the exact text as UTF-8.
3. Extract one JSON value to the supplied schema and objective. Record missing fields and source quotations using JSON Pointers into the proposed value.
4. Validate the value through native data.validate, including nested arrays, string lengths, numeric bounds and local schema references.
5. Check that every populated scalar has a quotation present in the exact input, and that each cited pointer names an actual populated field. JSON Pointer escapes use ~0 for ~ and ~1 for /.
6. Return ready only when schema and quotation checks pass. Otherwise return held with value: null and the failed checks. The sealed receipt retains what was proposed; do not treat a held result as usable extracted data.