document-extract

name	document-extract
description	Extract structured fields from a document using a caller-supplied JSON schema.
inputs	[{"name":"document_id","type":"string","required":true,"description":"UUID of the Document to extract from."},{"name":"schema","type":"object","required":true,"description":"JSON Schema object describing the fields to extract (e.g. contract parties, dates, amounts)."},{"name":"page_range","type":"array","required":false,"description":"Optional [start, end] page numbers to limit extraction scope."}]
outputs	[{"name":"extracted","type":"object","description":"Key-value map of extracted fields matching the caller-supplied schema."},{"name":"confidence","type":"object","description":"Per-field confidence scores (0.0–1.0)."}]
tools	["llm-extract","db-query"]

document-extract

When to use

Use this skill when the user needs structured data pulled from a specific document — such as contract terms, invoice line items, or form fields. Prefer it over document-search when the output must conform to a known schema rather than returning ranked snippets.

How it works

• Load Page rows (optionally scoped by page_range) and join with Section context via db-query.
• Serialize page text and pass it alongside the caller's JSON Schema to llm-extract.
• The model returns a JSON object; validate it against the schema before returning.
• Persist a snapshot of the extracted payload to the Document.metadata field via db-query for audit trail.

Audit

Emits one ExecutionHistory row with event_type=DOCUMENT_EDITED and actor_type=agent.