Individual skill

model-card

Use when a trained medical-imaging model needs its documentation. Fills a Model Card and a Datasheet for its dataset from facts you supply, adds a METRIC-informed data-quality pass and gates that no required section is empty. Never invents numbers, provenance or licence.

skills/model-card/SKILL.md

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Last checked: Nov 11, 2026

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Repository stars (not skill ratings): 376
Repository last updated: Nov 10, 2026
License: MIT

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

biostatistics Repository topic
claude-code Repository topic
claude-skills Repository topic
clinical-research Repository topic
diagnostic-accuracy Repository topic
literature-review Repository topic
manuscript Repository topic
medical-ai Repository topic
medical-research Repository topic
meta-analysis Repository topic
data Derived category
docs Derived category

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Browse files

SKILL.mdcore · 6,170 bytes
SKILL.mdcore · 6,170 bytes
SKILL.mdcore · 6,170 bytes
references/datasheet_template.mddoc · 2,280 bytes
references/metric_dimensions.mddoc · 3,066 bytes
references/model_card_template.mddoc · 3,239 bytes
scripts/check_model_card_complete.pyruns · 12,315 bytes
scripts/check_model_card_complete_challenge/fixture/complete/DATASHEET.mddoc · 2,179 bytes
scripts/check_model_card_complete_challenge/fixture/complete/MODEL_CARD.mddoc · 2,785 bytes
scripts/check_model_card_complete_challenge/fixture/incomplete/MODEL_CARD.mddoc · 880 bytes
scripts/check_model_card_complete_challenge/problem.mddoc · 1,853 bytes
scripts/check_model_card_complete_challenge/verify.shruns · 1,857 bytes
skill.ymlasset · 2,877 bytes
tests/test_model_card_complete.shruns · 12,116 bytes

Read excerpt


# Model-Card Skill

## Purpose

This skill produces the **documentation an engineer-built medical-imaging model must carry**: a
**Model Card** (intended use, out-of-scope use, training data, per-subgroup performance, caveats), a
**Datasheet** for its dataset (provenance, composition, collection, labelling, consent), and a
**METRIC-informed data-quality pass**. It fills the templates **from facts the user supplies** — it
never invents a number, a provenance detail, a consent status, or a licence — and ships a deterministic
gate that no required section is missing or left as an unfilled `[NEEDS INPUT]` placeholder.

It is the **reporting** seam of the model-engineering lane: after `/model-assessment` audits the design
and produces the numbers, this skill records them in a portable, auditable card that
`/write-paper` and `/check-reporting` consume. It mirrors `/version-dataset` structurally (generate +