Agent Evaluation Suite with Claude Code: Result JSON Schema
A production playbook for agent evaluation suite in cross-industry operations using Claude Code: result json schema, run-scoped inputs, logs, typed results, and artifacts.
Audience: AI quality teams
The problem
AI quality teams need agent evaluation suite to run repeatedly against eval cases, expected outputs, logs, and scoring rubrics. 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 evaluation suite 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 evaluation suite, 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 evaluation suite completed",
"body": { "type": "agent_evaluation_suite", "data": {}, "exceptions": [] },
"artifacts": []
}
Run this on Argo