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literature-review

Conducts systematic, scoping, and narrative literature reviews using PubMed, arXiv, bioRxiv, Semantic Scholar, and other appropriate sources. Use for research synthesis, reproducible literature searches, screening, citation checking, or preparing Markdown and PDF reviews. Tracks search coverage, records versus studies, and evidence limitations; supports meta-analysis planning but does not supply a meta-analysis engine.

Quality

90%

Does it follow best practices?

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Adds up to 20 points to the overall score

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

85%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.

A well-structured, domain-rich skill body: clear phased workflow with validation loops and clean progressive disclosure to real bundle files. Minor duplication of the frontmatter triggers and a few generic-knowledge items are the only trims needed.

DimensionReasoningScore

Conciseness

Overall efficient and dense with domain-specific procedural knowledge (records-vs-reports-vs-studies, PRISMA reconciliation, DOI verification caveats), but the 'When to Use This Skill' section duplicates the frontmatter description and a few items (e.g., 'Publication bias: Only positive results published', generic 'Be objective/Be clear' writing tips) explain concepts Claude already knows.

4 / 5

Actionability

Provides copy-paste-ready commands with pinned versions (uv tool install, verify_citations.py, generate_pdf.py --check-deps, generate_schematic.py) and points to real bundled scripts, but the core search/screening commands for the common workflow are only in references rather than exemplified in the body.

4 / 5

Workflow Clarity

Seven phases are clearly numbered and sequenced with explicit validation checkpoints and feedback loops: pilot-and-refine search testing, per-phase counts kept for PRISMA reconciliation, citation verification before finalization, and a dependency check before PDF generation.

5 / 5

Progressive Disclosure

The body is a well-organized overview with clearly signaled, one-level-deep markdown links to references (core_workflow.md, search_and_citation.md, example_workflow.md, database_strategies.md); all referenced bundle files exist and references contain no further nested links.

5 / 5

Total

18

/

20

Passed

Description

92%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.

Strong description: concrete, third-person capability statement with named sources, an explicit 'Use for…' trigger clause, and a clear scope boundary. Only minor keyword-synonym gaps keep trigger coverage from full marks.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — conducts systematic/scoping/narrative reviews, searches named databases (PubMed, arXiv, bioRxiv, Semantic Scholar), screening, citation checking, preparing Markdown and PDF reviews, tracking coverage and evidence limitations — which is comprehensive coverage across the review lifecycle.

5 / 5

Completeness

Explicitly answers both: what it does (first sentence enumerates review types, sources, and tracking behaviors) and when to use it ('Use for research synthesis, reproducible literature searches, screening, citation checking, or preparing Markdown and PDF reviews').

5 / 5

Trigger Term Quality

Good natural keyword coverage ('literature reviews', 'research synthesis', 'reproducible literature searches', 'citation checking', 'meta-analysis planning'), but a few common user phrasings are missing (e.g., 'lit review', 'evidence synthesis', 'related work', 'state of the art').

4 / 5

Distinctiveness Conflict Risk

Clear literature-review niche with distinct triggers (named bibliographic databases, PRISMA-style screening) and an explicit negative boundary ('does not supply a meta-analysis engine') that further separates it from adjacent skills.

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.

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_field

'metadata' should map string keys to string values

Warning

Total

15

/

16

Passed

Repository

K-Dense-AI/scientific-agent-skills

Path

skills/literature-review/SKILL.md

Reviewed

Table of Contents

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