meta-analysis-methods-generator

Generates the Methods section for a meta-analysis paper, including search strategy, screening, quality assessment, data extraction, and statistical analysis.

Quality

65%

Does it follow best practices?

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Adds up to 20 points to the overall score

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Securityby

Passed

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tessl review fix ./scientific-skills/Academic Writing/meta-analysis-methods-generator/SKILL.md

Quality

Content

60%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 content delivers concrete, actionable prompt templates and a clear sequenced workflow, with a real bundle script and good section structure. Its main weakness is verbosity: heavy boilerplate and contradictory validation guidance inflate the token budget without adding value.

Suggestions

Remove the generic boilerplate sections (Key Features, Implementation Details, Recommended Workflow, Required Inputs) that restate obvious process guidance Claude already knows.

Resolve the contradiction between 'Quick Validation' ('No local script validation step is required') and 'Validation Shortcut' ('run python scripts/validate_skill.py --help'), keeping one consistent validation path.

Merge the duplicated 'Workflow' and 'Recommended Workflow' sections into a single authoritative workflow to reduce redundancy.

Dimension	Reasoning	Score
Conciseness	The body is noticeably verbose with many generic boilerplate sections (Key Features, Implementation Details, Recommended Workflow, Required Inputs, etc.) that restate what Claude already knows, plus two overlapping workflow sections and contradictory validation guidance ('No local script validation step is required' vs. 'run python scripts/validate_skill.py --help').	2 / 5
Actionability	Provides concrete, reusable prompt templates for all six subsections and a real script path (scripts/validate_skill.py), giving mostly executable guidance with only minor gaps.	4 / 5
Workflow Clarity	The Workflow section gives a clear 6-step sequence with per-step inputs, plus Quality Rules and a Completion Checklist as checkpoints; minor gaps come from the contradictory validation sections.	4 / 5
Progressive Disclosure	Content is well-sectioned with clear headers, the single referenced bundle file (scripts/validate_skill.py) exists and is correctly signaled, and there are no deeply nested references; minor gaps are the inlined prompt bulk and boilerplate sections that could be trimmed.	4 / 5
	Total	14 / 20 Passed

Description

71%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 specific and well-scoped to meta-analysis methods generation, clearly stating what it does. Its main weakness is the absence of an explicit 'when to use' trigger clause, which caps completeness.

Suggestions

Add an explicit 'Use when...' clause naming natural trigger phrases (e.g., 'Use when writing the Methods section of a meta-analysis or systematic review').

Include common synonyms and related terms like 'systematic review', 'PRISMA', or 'risk of bias' to broaden trigger coverage.

Dimension	Reasoning	Score
Specificity	Names the domain and lists multiple concrete actions — 'search strategy, screening, quality assessment, data extraction, and statistical analysis' — giving comprehensive coverage of what the Methods section contains.	5 / 5
Completeness	The 'what' is clearly stated, but there is no 'Use when...' clause or equivalent explicit trigger guidance, so completeness is capped at 3 per the judging guidelines.	3 / 5
Trigger Term Quality	Includes natural terms a researcher would say ('meta-analysis paper', 'methods section', 'screening', 'quality assessment', 'statistical analysis'), but misses common synonyms/extensions like 'systematic review' or 'PRISMA'.	4 / 5
Distinctiveness Conflict Risk	Targets a clear niche (meta-analysis Methods section generation) with distinct triggers, with only minor overlap risk against general academic-writing skills.	4 / 5
	Total	16 / 20 Passed

Validation

93%

Warnings & errors only

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

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: aipoch/medical-research-skills
Path: scientific-skills/Academic Writing/meta-analysis-methods-generator/SKILL.md
Commit: 63c61d3

Reviewed: 12 hours ago

Table of Contents

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