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sci-paper-reviewer

Simulates a strict SCI peer-review workflow; trigger when a user uploads or pastes a manuscript (PDF/DOC/DOCX/TXT) and requests an innovation score (1–12) plus experimental-logic vulnerability checks and revision suggestions.

69

Quality

85%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

75%Weight 40%Scale 1-5

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

The body is a well-structured, actionable instruction-only skill with a clear review workflow, concrete parser command, and a detailed innovation/vulnerability rubric. Its weaknesses are mild redundancy between Key Features and Implementation Details and an unused references file that should be linked from the Dependencies section.

Suggestions

Replace the inlined "Dependencies" list with a one-line pointer to references/document_parser_requirements.md (e.g., "See references/document_parser_requirements.md for parser dependencies") to use the existing reference file and tighten the body.

Drop or fold the "Key Features" section into "Implementation Details" to remove the duplicated restatement of the innovation rubric and vulnerability categories.

Add an explicit checkpoint after section extraction (e.g., "If Abstract/Results are missing, warn the user before scoring") to give the review workflow a clear feedback loop.

DimensionReasoningScore

Conciseness

The body is mostly efficient and avoids explaining concepts Claude already knows, but the "Key Features" section duplicates material restated in "Implementation Details", and the "Dependencies" list with repeated "(version varies)" notes could be trimmed. It is above the 3-anchor (efficient with some slack) but the redundancy keeps it from 5.

4 / 5

Actionability

Provides a concrete executable command (python scripts/enhanced_document_parser.py ...), copy-paste example prompt templates, and specific score-band definitions for the innovation rubric and vulnerability categories with real examples (qPCR without protein-level confirmation). It is not a 5 because the bulk is guidance rather than fully executable code across all cases.

4 / 5

Workflow Clarity

The process is clearly sequenced (parse → extract sections → classify → score innovation → screen vulnerabilities → emit structured report) with numbered sections and a parser failure-handling checkpoint. It is not a 5 because there is no explicit feedback loop verifying that sections were extracted before scoring, and no verification step on the final report.

4 / 5

Progressive Disclosure

Good section structure and the referenced scripts/enhanced_document_parser.py is a real bundle file. However the "Dependencies" section is inlined in SKILL.md even though references/document_parser_requirements.md exists and is never linked, a minor organization gap. It is above the 3-anchor (structured with references) but the orphaned reference file keeps it from 5.

4 / 5

Total

16

/

20

Passed

Description

95%Weight 40%Scale 1-5

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 is strong: it states what the skill does, when to trigger it, includes file extensions and natural trigger terms, and occupies a distinctive niche. Minor gap is that not every body-level capability (research-type classification, section extraction) is surfaced in the description.

DimensionReasoningScore

Specificity

Names the domain ("strict SCI peer-review workflow") and several concrete actions — innovation score (1–12), experimental-logic vulnerability checks, revision suggestions — but omits other capabilities named in the body (research-type classification, section extraction). It is above the 3-anchor (1–2 actions) but not fully comprehensive enough for 5.

4 / 5

Completeness

Explicitly answers both what ("Simulates a strict SCI peer-review workflow; ... innovation score ... vulnerability checks ... revision suggestions") and when ("trigger when a user uploads or pastes a manuscript ... and requests an innovation score ...") with concrete trigger phrases, matching the 5-anchor exactly.

5 / 5

Trigger Term Quality

Covers natural user phrasing and synonyms ("manuscript", "peer review", "innovation score", "revision suggestions") plus explicit file extensions (PDF/DOC/DOCX/TXT), matching the comprehensive-coverage anchor. It is not a 4 because file extensions and common variations are all present.

5 / 5

Distinctiveness Conflict Risk

The combination of "strict SCI peer-review", "innovation score (1–12)" and "experimental-logic vulnerability checks" carves a clear niche with distinct triggers and minimal overlap risk. It is clearly above the 4-anchor because the triggers are highly specific rather than merely 'mostly distinct'.

5 / 5

Total

19

/

20

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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