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academic-highlight-generator

Generates submission-ready Elsevier/SCI Highlights from manuscript text or extracted PDF/DOCX/TXT content. Use when a user needs 3-5 concise, evidence-grounded highlight bullets for a research paper, review, meta-analysis, case report, or bioinformatics manuscript.

74

Quality

92%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

85%Weight 40%Scale 1-3

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

A well-structured, actionable skill body with a clear validated workflow and appropriate externalization of prompts and extraction logic. Its only weakness is mild redundancy where output constraints are restated across several sections.

Suggestions

Consolidate the repeated bullet constraints (3-5 count, 85-char limit, grounding, no fabrication) into a single authoritative section and have other sections reference it instead of restating the rules.

Consider moving the per-type coverage priorities list into references/prompts.md alongside the matching generation prompts, keeping the SKILL.md body as an overview.

DimensionReasoningScore

Conciseness

The body is mostly efficient and does not explain known concepts, but constraints (3-5 bullets, 85-char limit, grounding, no fabrication) are restated across Output Contract, Workflow step 5, Deterministic Rules, and the Quality Checklist, adding redundant tokens.

2 / 3

Actionability

Provides an executable command (python scripts/extract_text.py), a copy-paste-ready output contract with exact format and character limit, and a concrete refusal template, all directly actionable.

3 / 3

Workflow Clarity

A clearly numbered 5-step workflow with an explicit validation gate (stop + refusal template if source insufficient), extraction-failure handling, and a final self-critique checklist.

3 / 3

Progressive Disclosure

Body is an overview with well-signaled one-level-deep references to references/prompts.md (classification, generation, critique prompts) and scripts/extract_text.py, both confirmed as real bundle files; detail is correctly split out.

3 / 3

Total

11

/

12

Passed

Description

100%Weight 40%Scale 1-3

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

A strong, third-person description that explicitly states capabilities, output format, and a clear 'Use when' trigger. It is specific, distinctive, and free of vague fluff or over-claims.

DimensionReasoningScore

Specificity

Names concrete actions and output shape ('Generates submission-ready Elsevier/SCI Highlights', '3-5 concise, evidence-grounded highlight bullets') plus concrete input sources (PDF/DOCX/TXT), matching the multiple-specific-actions anchor.

3 / 3

Completeness

Explicitly answers both what (generates submission-ready Highlights from manuscript content) and when via an explicit 'Use when a user needs 3-5 ... highlight bullets' trigger clause.

3 / 3

Trigger Term Quality

Covers natural terms users would say ('research paper', 'review', 'meta-analysis', 'case report', 'bioinformatics manuscript', 'Highlights') with good breadth of variations.

3 / 3

Distinctiveness Conflict Risk

Narrow, well-defined niche (Elsevier/SCI journal-submission Highlights) with distinct triggers unlikely to fire for unrelated skills.

3 / 3

Total

12

/

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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