Agent Result Schema Design with Claude Code: API Runtime Pattern
A production playbook for agent result schema design in cross-industry operations using Claude Code: api runtime pattern, 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
Package the agent result schema design instructions as a skill, send expected product events, downstream schemas, and examples as run-scoped inputs, execute with Claude Code, poll terminal status, and consume argo.result.v1 instead of parsing a transcript.
Tradeoffs and failure modes
The API boundary forces the workflow to define inputs, terminal states, and result shape before customers depend on it. 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.
Run request
POST /api/skills/<skill_id>/run
provider=claude-code
workflow=agent-result-schema
inputs[]=@./input-pack.zip
result_schema=argo.result.v1
Run this on Argo