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Trace grading | OpenAI API

Teaches how to implement automated evaluation of LLM outputs by using model-based grading on traces to assess quality, accuracy, or specific criteria.

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Derived skill

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Viewing SKILL.md

Trace grading | OpenAI API

Teaches how to implement automated evaluation of LLM outputs by using model-based grading on traces to assess quality, accuracy, or specific criteria.

When To Use

Use when you need to automate the evaluation of LLM trace data to programmatically score model responses against specific quality metrics.

Reference Files

File	Contains	Use For
`SKILL.md`	Entry point: scope, routing table, and workflow.	Start here.
`docs/trace-grading-openai-api-workflow-guide.md`	A guide explaining how to assign structured scores and labels to agent traces to evaluate correctness and quality.	Questions about a guide explaining how to assign structured scores and labels to agent traces to evaluate correctness and quality.

What This Skill Covers

Trace grading is the process of assigning structured scores or labels to an agent’s trace—the end-to-end log of decisions, tool calls, and reasoning steps—to...
Main sections: Get started with traces, Evaluate traces with runs.

Workflow

Open the most relevant file under docs/ for the exact documented workflow and wording.
Open schemas/ files for exact structured contracts.
Open examples/ files for concrete requests, commands, snippets, and manifests.
Do not add behavior or configuration that is not present in the attached source files.

Canonical source: https://developers.openai.com/api/docs/guides/trace-grading