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Generates detailed text descriptions of medical images and charts for.

31

Quality

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

32%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The skill has real bundle files and a runnable script, but the SKILL.md body is dominated by templated boilerplate with broken cross-references and lacks skill-specific executable examples. It is functional but inefficient and not well-structured for navigation.

Suggestions

Remove generic boilerplate (Lifecycle Status, generic Evaluation Criteria, Risk/Security tables) unless they carry skill-specific content, to recover token efficiency.

Fix the broken 'See ## ... above' pointers and either populate references/guidelines.md with one-level-deep detail or remove the dangling references.

Replace abstract description-generation guidance with a concrete, copy-paste example invoking scripts/main.py.describe() on a real medical image input and showing the resulting JSON.

DimensionReasoningScore

Conciseness

The body is heavily padded with boilerplate that adds little skill-specific value (e.g. 'Repository baseline for current packaged skills', 'Add pinned versions if this skill needs stricter environment control', generic Risk/Security/Evaluation tables), which is exactly the verbosity the rubric penalizes.

1 / 3

Actionability

There are concrete commands (`python -m py_compile scripts/main.py`, `python scripts/main.py`) and a real script exists, but the actual description-generation guidance is abstract (no working example showing how to call describe() with real inputs and interpret the output), so it is incomplete rather than fully executable.

2 / 3

Workflow Clarity

A numbered workflow and an error-handling/fallback section provide a sequence, and a Quick Check validation step exists, but the steps are generic templates with no real validation checkpoint tied to the actual describe() output, so checkpoints are implicit rather than explicit.

2 / 3

Progressive Disclosure

Content is organized into sections and a references/ file exists, but several references are broken or circular ('See `## Features` above', 'See `## Prerequisites` above', 'See `## Workflow` above'), and a 151-byte references file duplicates inline features rather than providing one-level-deep detail, so navigation is not cleanly signaled.

2 / 3

Total

7

/

12

Passed

Description

17%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description names a domain and an action but is grammatically truncated, lacks any explicit 'when to use' trigger, and offers no natural user keywords. It is closer to the weak examples than the strong ones.

Suggestions

Complete the truncated sentence and finish the thought (e.g. '...for accessibility and academic documentation.').

Add an explicit trigger clause: 'Use when the user needs alt text or figure legends for medical images, scans, or charts.'

Include natural keyword variations users would say (alt text, figure legends, accessibility descriptions, microscopy, scan).

DimensionReasoningScore

Specificity

Names a domain ('medical images and charts') and concrete actions ('Generates detailed text descriptions'), but the sentence is truncated mid-phrase ('...charts for.') and does not list multiple distinct actions like the score-3 anchor requires.

2 / 3

Completeness

It states what the skill does but provides no 'Use when...' clause or equivalent explicit trigger guidance, which per the judging guidelines caps completeness at 2; combined with the truncated sentence the 'when' is entirely absent, landing at 1.

1 / 3

Trigger Term Quality

No natural user-facing keywords appear; 'medical images and charts' is domain jargon and there are no common variations or trigger words a user would actually say, matching the 'no natural keywords' anchor.

1 / 3

Distinctiveness Conflict Risk

The medical-visual niche is somewhat specific and unlikely to broadly conflict, but the broken, generic phrasing could still overlap with general image-description skills, matching 'somewhat specific but could still overlap'.

2 / 3

Total

6

/

12

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
aipoch/medical-research-skills
Reviewed

Table of Contents

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