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Evaluate one design or a user-approved maturity-mapped batch through a transparent evidence-based rubric. Classify each work, score design quality and presentation, identify Critical risks, report evidence confidence, and optionally shortlist works within separate maturity tracks.
Passed 20 of 22 test cases with the skill, and 7 of 22 without it.
and 18 more in the full report
14 fixed6 passed either way1 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 14 test cases the skill fixed. Same model, same prompt, with and without the skill.
Run a batch evaluation on 5 entries using our mapped classification rule 'all_academic_projects -> Student Concept'. What metadata flag must be recorded in the batch manifest?
| Checked | Without skill | With skill |
|---|---|---|
| Records maturity_source as user in the batch manifest. | Missed | Passed |
The instructions your model reads when the skill loads.
Evaluate design quality consistently without pretending that a score is an award outcome. Keep design quality, presentation quality, and evidence confidence separate. Require the user to choose the maturity track.
Do not:
Route winner retrieval to $design-award-search, award selection to $design-award-match, concrete redesign work to $design-optimization when available, and final package compliance to $design-submission-check.
Accept images, a PDF, project text, a portfolio page, video frames, prototype evidence, test records, or a structured brief.
Maturity is mandatory and must come from the user. Accept exactly:
Student Concept / 学生概念Mature Work / 成熟作品If maturity is absent, ask exactly one question and stop scoring:
test cases passed, vs 7 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.