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Design representative eval cases
Create normal, edge, negative, ambiguous, and adversarial prompts with required inputs, environments, and expected evidence.
Codex skill evaluation
CategoryAI & Codex Skills
Codex Evaluation Skills
Codex Evaluation Skills help you test whether a Codex skill triggers correctly, follows its workflow, produces useful artifacts, respects boundaries, and improves results across realistic tasks. Download the skills for building repeatable eval sets, graders, regression checks, and evidence-based skill revisions.
Skill evalsTest casesGradersRegression checks
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task: complete codex skill evaluation task
inspect:
- requirements and context
- existing standards
- failure and edge cases
verify: outputs + checks + handoffWhy a specialist workflow matters
A skill can read well in SKILL.md and still fail when the prompt is vague, the repository is unfamiliar, or the expected result is not shown to the evaluator.
Useful evaluation measures routing, instruction following, tool behavior, artifact quality, safety boundaries, efficiency, and consistency across varied prompts.
These skills help Codex design evals that test the skill rather than reward memorized wording or leak the intended answer into the run.
What the downloadable skills can do
What Codex Evaluation Skills can help accomplish
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Capture runs and artifacts
Record prompts, skill activation, traces, tool calls, files, outputs, timing, failures, and environmental conditions.
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Build suitable graders
Combine deterministic checks, artifact inspection, rubric scoring, human review, and task-specific acceptance criteria.
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Compare revisions safely
Run baselines and candidates on the same cases, inspect regressions, analyze variance, and connect changes to observed behavior.
A repeatable working process
How the codex skill evaluation workflow moves from request to verified result
The steps keep context, implementation, and verification visible so the result can be reviewed and repeated.
workflow.statusREADY
Context → Plan → Work → Verify
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Define what the skill promises
Turn its trigger description, workflow, boundaries, outputs, and quality bar into observable claims.
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Create a balanced test set
Cover intended use, near misses, missing context, difficult inputs, failure recovery, and tasks where the skill should not trigger.
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Run without leaking the answer
Isolate cases, preserve raw outputs and traces, control environment differences, and avoid giving the evaluator the desired conclusion.
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Score, inspect, and revise
Use automated checks where reliable, review artifacts, explain failures, update one hypothesis at a time, and rerun regressions.
Useful across real projects
Where Codex Evaluation Skills fit
The workflow adjusts to the project, audience, tools, and risk while preserving the same quality standard.
Single-skill evaluation
Test routing, instructions, outputs, scripts, references, assets, and boundaries for one reusable workflow.
Repository tasks
Measure whether a skill helps Codex understand an unfamiliar codebase, make a focused change, and verify it correctly.
Artifact workflows
Inspect documents, sites, spreadsheets, images, reports, or other deliverables for task-specific quality.
Continuous regression
Run a stable eval set when SKILL.md, scripts, references, models, tools, or dependent environments change.
Common requests
Tasks these skills can handle
Start with one defined outcome and provide the source material, constraints, and checks that matter.
01Create a skill eval plan
02Write representative test prompts
03Define pass and fail criteria
04Build deterministic graders
05Score artifact quality
06Compare a baseline and revision
07Investigate a regression
08Prepare an eval report
Who benefits most
Who Is This For?
These skills are designed for people who need dependable codex skill evaluation work with a visible process.
Skill authors
Learn whether instructions work on realistic prompts before distributing a skill.
Engineering teams
Add repeatable quality gates for shared Codex workflows and project-specific skills.
Marketplace maintainers
Assess capability claims, installation integrity, boundaries, and version-to-version behavior.
Researchers and evaluators
Study routing, instruction following, tool use, artifacts, variance, and failure patterns.
Good to know:
An eval score describes performance on the tested cases and environment. It does not prove universal quality, safety, or future behavior, and it should not hide grader limitations or failed runs.
Set up the workflow
Installation Guide
Install the complete skill folder and add the project-specific context before beginning.
Download and extract the evaluation skills
Keep SKILL.md with case-design, execution, grading, comparison, and reporting guidance.
Choose an isolated eval project
Separate test fixtures, run outputs, graders, reports, and temporary work from the skill being evaluated.
Provide the skill contract
Add its files, claimed triggers, supported tasks, exclusions, expected artifacts, and verification requirements.
Define execution and scoring tools
State how Codex runs will be captured, which checks are deterministic, where human review is required, and how results will be compared.
Before you download
Frequently Asked Questions
Practical answers about capabilities, limits, setup, and review.
Can the skills evaluate another Codex skill?+
Yes. They can turn its stated behavior into test cases, run the cases in a controlled setup, and organize evidence.
How many eval prompts are needed?+
It depends on scope and risk. Start with a small balanced set that covers normal use, edge cases, non-trigger cases, and known failure modes.
Can an LLM grade the results?+
It can apply a clear rubric, but subjective grading should be calibrated against examples and supplemented with deterministic or human checks.
Do the skills measure skill triggering?+
Yes. They can test when a skill should activate, should stay inactive, or should ask for missing inputs.
Can evals prevent every regression?+
No. They detect regressions represented in the test set. New failures require new cases and periodic review.
Make the work repeatable
Give Codex an evaluation workflow that turns skill claims into cases, captured evidence, defensible scores, and safer revisions.
Clear context. Purposeful work. Relevant checks. A result others can understand.