Run Output Validation with Codex: API Runtime Pattern
A production playbook for run output validation in cross-industry operations using Codex: api runtime pattern, run-scoped inputs, logs, typed results, and artifacts.
Audience: AI platform teams
The problem
AI platform teams need run output validation to run repeatedly against result JSON, artifacts, logs, and acceptance checks. 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 run output validation instructions as a skill, send result JSON, artifacts, logs, and acceptance checks as run-scoped inputs, execute with Codex, 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 run output validation, 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=codex
workflow=run-output-validation
inputs[]=@./input-pack.zip
result_schema=argo.result.v1
Run this on Argo