Test Generation with Claude Code: Result JSON Schema

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

Audience: QA and developer productivity teams

The problem

QA and developer productivity teams need test generation to run repeatedly against source files, fixtures, failing traces, and acceptance criteria. 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 test 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 test 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": "test generation completed",
  "body": { "type": "test_generation", "data": {}, "exceptions": [] },
  "artifacts": []
}

Run this on Argo