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meta-search-builder

Medical literature search strategy generator. Given a user's natural-language description (e.g., meta-analysis topic, PICOS elements, research question), automatically extract medical entities (disease, intervention, population, outcomes) and generate professional search queries for seven major databases (PubMed, Cochrane, Embase, Web of Science, CNKI, Wanfang, VIP). Useful for developing search strategies for systematic reviews and meta-analyses.

53

Quality

60%

Does it follow best practices?

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SecuritybySnyk

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tessl review fix ./scientific-skills/Other/meta-search-builder/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

46%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 has a genuine, actionable workflow core (entity extraction rules plus an output template pointing to a real reference), but it is buried under generic boilerplate sections that add little skill-specific value. Tightening the padding and adding concrete validation would improve it.

Suggestions

Remove or collapse boilerplate sections (Dependencies, Implementation Details, Required Inputs, Output Contract) that restate general norms Claude already knows; keep only skill-specific guidance.

Inline a short concrete example of an actual database query (e.g., a sample PubMed Boolean string built from PICOS) instead of deferring all query syntax to the reference file.

Replace generic validation boilerplate with a concrete, skill-specific check (e.g., verify each of the 7 databases has a populated query block and that PICOS fields are non-empty before emitting the result).

DimensionReasoningScore

Conciseness

Much of the body is generic boilerplate (Dependencies, Implementation Details that says 'See ## Workflow above', When to Use, Required Inputs, Output Contract) that restates norms Claude already knows rather than adding skill-specific knowledge.

2 / 5

Actionability

Step 1 gives concrete extraction rules (limit 5 keywords, simplification example, term mapping) and the output template is specific, but the core executable detail of building database queries is deferred to references/databases.md rather than shown inline.

3 / 5

Workflow Clarity

A clear two-step sequence exists, but validation checkpoints are generic boilerplate ('Validate required inputs before execution') rather than concrete, skill-specific verification steps tied to the output.

3 / 5

Progressive Disclosure

The one real reference (references/databases.md, which exists) is clearly signaled inline at Step 2, and the body functions as an overview; minor gaps come from boilerplate sections diluting the structure.

4 / 5

Total

12

/

20

Passed

Description

75%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 distinctive with comprehensive action coverage, but its trigger guidance is only implied via 'Useful for' rather than an explicit 'Use when' clause. Adding concrete trigger phrasing would lift completeness.

Suggestions

Add an explicit 'Use when...' clause with natural trigger phrases (e.g., 'Use when the user requests a search strategy for a systematic review or meta-analysis, or mentions PICOS, PubMed, Cochrane, Embase, or CNKI queries').

Include common synonyms or file-format triggers users naturally mention when asking for literature searches.

DimensionReasoningScore

Specificity

Lists multiple concrete actions (extract medical entities via PICOS, generate search queries) and names all seven target databases, giving comprehensive coverage of the skill's capabilities.

5 / 5

Completeness

Clearly states what the skill does, but the 'when' is only weakly implied via 'Useful for...' rather than an explicit 'Use when...' trigger clause, which caps completeness per the guidelines.

3 / 5

Trigger Term Quality

Includes natural terms like 'meta-analysis topic', 'PICOS elements', 'systematic reviews', and database names, but lacks file extensions and a few common synonyms a user might say.

4 / 5

Distinctiveness Conflict Risk

Occupies a clear niche (medical literature search strategies for seven named databases) with distinct triggers and minimal overlap risk with other skills.

5 / 5

Total

17

/

20

Passed

Validation

87%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

referenced_paths_exist

Referenced path issues: 2 missing

Warning

Total

14

/

16

Passed

Repository
aipoch/medical-research-skills
Reviewed

Table of Contents

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