Mode d’emploi
- Copiez la commande et examinez le paquet avant de l’installer dans votre environnement agent.
- Consultez le document original pour les outils, identifiants et environnements requis.
- Décrivez les entrées et le livrable souhaité ; comparez la sortie aux sources.
npx skills add https://github.com/ai-evals-course/evals-skills --skill write-code-evalAvant de commencer
- L’installation n’inclut ni abonnement au modèle, ni quota API, ni accès aux fichiers.
- Étoiles et installations reflètent l’activité, pas un test indépendant de qualité ou de sécurité.
Document Skill original
Rendu depuis le dépôt source en conservant titres, exemples, code, tableaux, liens et images.
Write a code evaluator
Start with a failure mode found through error analysis. Write one check for that failure mode, much like a unit test that asserts what should hold for each trace.
- State the rule and identify the trace fields or reference data the check needs. If the rule requires interpretation, use
write-judge-prompt. - Implement the check in the project's language and eval framework. Return a result and a reason in the format that framework expects.
- Test known passes and failures, including borderline cases. Run the check on available traces and inspect mistakes. If the rule uses a proxy for human judgment, compare its results with human labels.
Examples
| Failure mode | Possible check |
|---|---|
| Invalid output structure | Parse the output and check required fields |
| Missing or forbidden text | Match a string or pattern |
| Citation not in retrieved documents | Compare cited IDs with retrieved IDs |
| Bad tool call | Check arguments against the tool schema or run the call in a safe test environment |
| Wrong value | Compare the output with a reference value |
Choose the check from the failure rule. For a failure with both objective and interpretive parts, check the objective part with code and use a judge for the rest.
