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Validate that input meets prerequisites based on the user's saved standards for the project type. Use at the start of any quality pipeline to ensure the user has provided sufficient requirements.
Passed 15 of 22 test cases with the skill, and 4 of 22 without it.
and 23 more in the full report
13 fixed2 passed either way5 still failing2 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.
I'm drafting a task description for our upcoming REST API endpoint refactoring work: 'We need to speed up the GET /users endpoint because it's slow.' Please audit this requirement for our backend service project. Return a JSON report evaluating whether it's ready, containing an overall validity status, a list of specific issues found, granular validation details covering clarity, completeness, and context sufficiency, a recommended next step, and a short summary.
| Checked | Without skill | With skill |
|---|---|---|
| The top-level validity key is named 'status' set to 'invalid' | Missed | Passed |
| The issues array highlights the lack of target latency metrics | Passed | Passed |
| The recommendation indicates asking the user for baseline performance measurements | Passed | Passed |
The instructions your model reads when the skill loads.
Ensures the user's input (requirements, description, source material) meets the prerequisites defined in their standards for this project type. This is the first gate in the quality pipeline.
Based on the user's saved standards for the project type, verify:
Completeness - Is there enough information?
Clarity - Is the description clear and specific?
Format - Is it in a recognizable format?
Sufficiency - Is there enough context?
Standards Alignment - Does it match their defined validation rules?
test cases passed, vs 4 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.