Agent Result Schema Design with Claude Code: Result JSON Schema
A production playbook for agent result schema design in cross-industry operations using Claude Code: result json schema, run-scoped inputs, logs, typed results, and artifacts.
Audience: Backend engineers productizing agents
The problem
Backend engineers productizing agents need agent result schema design to run repeatedly against expected product events, downstream schemas, and examples. 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 agent result schema design 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 agent result schema design, 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": "agent result schema design completed",
"body": { "type": "agent_result_schema", "data": {}, "exceptions": [] },
"artifacts": []
}
Run this on Argo