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write-code-eval

/write-code-eval

Write code evaluators for known failure modes with objective rules. Use when code can check the rule from a trace, with or without a reference answer. Use `write-judge-prompt` when the rule requires interpretation.

Licence
Apache-2.0
Last repository change
24.09.2026

Assessment and security

100/ 100Class: good
Format25 / 25
Frontmatter with name and description, valid name, description up to 1,024 characters, name matching the folder.
Discoverability25 / 25
Description explains when to use the skill, has a reasonable length and uses third person.
Content35 / 35
At least 150 words and at most 500 lines, headings, step lists, examples or code.
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Deprecation

No signals detected. Repository changed on 24.09.2026, without references to retired models or APIs.

Licence

Apache-2.0, otwarta: można używać i zmieniać, z zachowaniem licencji i informacji o zmianach.

What it does and when to use it

Write code evaluators for known failure modes with objective rules. Use when code can check the rule from a trace, with or without a reference answer. Use `write-judge-prompt` when the rule requires interpretation.

Original author description

Write code evaluators for known failure modes with objective rules. Use when code can check the rule from a trace, with or without a reference answer. Use `write-judge-prompt` when the rule requires interpretation.

How it works

  1. Examples
Original SKILL.md headings · 21 lines, 223 words
SKILL.md preview
---
name: write-code-eval
description: >
  Write code evaluators for known failure modes with objective rules. Use when
  code can check the rule from a trace, with or without a reference answer.
  Use `write-judge-prompt` when the rule requires interpretation.
---

# 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.

1. State the rule and identify the trace fields or reference data the check needs. If the rule requires interpretation, use `write-judge-prompt`.
2. Implement the check in the project's language and eval framework. Return a result and a reason in the format that framework expects.
3. 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.
Files in this package (2)
  • SKILL.md 2 KB
  • agents/openai.yaml 1 KB

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Database snapshot: 13.11.2026 · package version 28a5ff050a8e (SHA-256 digest of the entire package)

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