Batch Document Intake with Claude Code: Result JSON Schema

A production playbook for batch document intake in cross-industry operations using Claude Code: result json schema, run-scoped inputs, logs, typed results, and artifacts.

Audience: Back-office automation teams

The problem

Back-office automation teams need batch document intake to run repeatedly against folders of documents, classification rules, and target systems. In cross-industry operations, the pain is not one good answer; it is repeatability, auditability, exception handling, and evidence that survives handoff.

Implementation path

Define the outer result contract once, let the batch document intake skill own body.data, and reject terminal output that does not match the expected schema.

Tradeoffs and failure modes

Schema enforcement adds upfront design work, but removes prompt parsing from the product surface. For batch document intake, the practical test is whether a second run can be debugged, retried, and consumed by a product without reading the raw agent transcript.

Result shape

{
  "schema_version": "argo.result.v1",
  "summary": "batch document intake completed",
  "body": { "type": "batch_document_intake", "data": {}, "exceptions": [] },
  "artifacts": []
}

Run this on Argo