Research Brief Generation with Claude Code: Result JSON Schema
A production playbook for research brief generation in cross-industry operations using Claude Code: result json schema, run-scoped inputs, logs, typed results, and artifacts.
Audience: Analyst and strategy teams
The problem
Analyst and strategy teams need research brief generation to run repeatedly against source PDFs, web captures, notes, and citation rules. 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 research brief generation 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 research brief generation, 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": "research brief generation completed",
"body": { "type": "research_brief_generation", "data": {}, "exceptions": [] },
"artifacts": []
}
Run this on Argo