Data Room Indexing with Claude Code: Result JSON Schema

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

Audience: Deal teams and diligence operators

The problem

Deal teams and diligence operators need data room indexing to run repeatedly against folders of PDFs, spreadsheets, and evidence files. 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 data room indexing 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 data room indexing, 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": "data room indexing completed",
  "body": { "type": "data_room_indexing", "data": {}, "exceptions": [] },
  "artifacts": []
}

Run this on Argo