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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.

68

Quality

86%

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SKILL.md
Quality
Evals
Security

Quality

Content

81%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 instruction skill with a validated five-step workflow, concrete templates, and appropriately offloaded detail in prompts.md and extract_text.py. Main improvements are deduplicating the repeated article-type and command sections, moving coverage priorities into prompts.md, and adding a worked example of real output highlights.

Suggestions

Deduplicate the article-type list (When to Use vs. Workflow step 3) and the extract_text.py command (Path B vs. step 2) — state each once and cross-reference to cut roughly 15 lines.

Add one worked example (short abstract input → final Highlights output) so the generation step shows, not just describes, the target quality.

Move the per-type 'Coverage priorities by type' table into references/prompts.md alongside the matching generation prompts to remove rule duplication.

DimensionReasoningScore

Conciseness

The body is operational with no explanations of concepts Claude already knows, but contains trimmable redundancy: the article-type list appears twice ("When to Use" with 8 types and Workflow step 3 with 10 types) and the extraction command is repeated in both "Path B" and Workflow step 2. This matches anchor 4 (efficient, minor instances that could be trimmed) rather than 3, since no section is padding or over-explanation.

4 / 5

Actionability

Concrete, executable guidance throughout: an exact command ("python scripts/extract_text.py <file_path>"), a copy-paste output contract template, a refusal template, and hard limits ("Exactly 3-5 bullets", "Maximum 85 characters per English bullet"). It falls short of anchor 5 because there is no worked input-to-output example of actual highlights, which matters for a generation task.

4 / 5

Workflow Clarity

The five-step workflow (validate sufficiency, extract, detect type, generate, self-critique) has an explicit validation checkpoint up front with a refusal contract, explicit failure handling ("report the exact failure... do not invent content from the missing file"), and a step-5 self-critique checklist — matching anchor 5 (explicit validation steps, feedback loops for error recovery, checklists).

5 / 5

Progressive Disclosure

SKILL.md is an overview with well-signaled, one-level-deep references that both exist (references/prompts.md holds classification/generation prompts; scripts/extract_text.py holds extraction). Minor gap: the inline "Coverage priorities by type" list in step 4 partially duplicates per-type rules already in prompts.md, matching anchor 4 (minor organization gaps) rather than 5.

4 / 5

Total

17

/

20

Passed

Description

87%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.

A strong description: third-person voice, explicit what-and-when structure, concrete domain parameters, and specific manuscript-type triggers. The only improvement space is slightly broader synonym coverage of natural user phrasing.

DimensionReasoningScore

Specificity

"Generates submission-ready Elsevier/SCI Highlights from manuscript text or extracted PDF/DOCX/TXT content" names the domain and concrete actions (generation plus handling of PDF/DOCX/TXT sources) with specific parameters ("3-5 concise, evidence-grounded highlight bullets"). It lists several specific actions with minor coverage gaps, matching anchor 4; not 3 because it goes beyond 1-2 generic actions, and not 5 because it does not enumerate a comprehensive action set (e.g., no mention of validation or refinement steps).

4 / 5

Completeness

It explicitly answers what ("Generates submission-ready Elsevier/SCI Highlights from manuscript text or extracted PDF/DOCX/TXT content") and when ("Use when a user needs 3-5 concise, evidence-grounded highlight bullets for a research paper, review, meta-analysis, case report, or bioinformatics manuscript") with concrete trigger phrases, exactly matching anchor 5.

5 / 5

Trigger Term Quality

Natural user phrases are present: "Highlights", "research paper", "review, meta-analysis, case report", "bioinformatics manuscript", plus file extensions "PDF/DOCX/TXT" and "Elsevier/SCI". A few natural terms are missing ("manuscript submission", "highlight section", "bullet points"), which matches anchor 4 rather than 5's comprehensive synonym coverage.

4 / 5

Distinctiveness Conflict Risk

The description occupies a clear niche (journal submission Highlights for academic manuscripts) with distinct triggers (Elsevier/SCI, manuscript types, highlight bullets), so conflict with generic writing or document skills is minimal — anchor 5.

5 / 5

Total

18

/

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

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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