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bgpt-paper-search

Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server. Returns 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions. Use for literature reviews, evidence synthesis, and finding experimental details not available in abstracts alone.

68

Quality

81%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

71%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 clean, well-structured instruction skill for a remote MCP tool with concrete configuration and a usable example. Main weakness is redundancy across sections and a minor validation/parameter gap.

Suggestions

Deduplicate the returned-fields list — state the 25+ fields once (in Usage) rather than repeating methods/results/sample sizes/quality across the description, Overview, and Usage sections.

Add a brief note on verifying the BGPT MCP server connected successfully before issuing the first search_papers call, since it is a remote server that can fail to connect.

Document the search_papers tool's key parameters (e.g., query, filters, max results) so the agent can construct the call directly rather than from a natural-language example alone.

DimensionReasoningScore

Conciseness

Mostly efficient but repeats the returned-fields list across the description, Overview, and Usage sections, and lightly over-explains what a literature database is ('Unlike traditional literature databases that return titles and abstracts'); could be tightened.

3 / 5

Actionability

Provides copy-paste-ready MCP config JSON and an executable npm command plus a concrete example query, but does not surface the search_papers tool's parameters/schema, leaving a minor gap.

4 / 5

Workflow Clarity

Clear Setup-then-Usage sequence for a simple single-tool skill, but there is a minor validation gap: no checkpoint confirming the remote MCP server actually connected before calling search_papers.

4 / 5

Progressive Disclosure

Well-organized into clearly signaled sections (Overview, When to Use, Setup, Usage, Pricing) with no nested references; a self-contained remote-tool skill appropriately kept in one file.

5 / 5

Total

16

/

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.

A strong, specific description that clearly states both capability and trigger conditions in third person. Minor keyword-synonym gaps prevent a perfect trigger_term_quality score.

DimensionReasoningScore

Specificity

Names the domain and multiple concrete actions ('Search scientific papers and retrieve structured experimental data') plus enumerates specific returned fields (methods, results, sample sizes, quality scores, conclusions), giving comprehensive coverage.

5 / 5

Completeness

Explicitly answers both what ('Search scientific papers and retrieve structured experimental data... Returns 25+ fields') and when ('Use for literature reviews, evidence synthesis, and finding experimental details not available in abstracts alone') with concrete trigger phrases.

5 / 5

Trigger Term Quality

Includes natural terms users would say ('scientific papers', 'literature reviews', 'evidence synthesis', 'abstracts') but is missing common synonyms/extensions a user might mention (e.g., 'research papers', 'studies', 'meta-analysis').

4 / 5

Distinctiveness Conflict Risk

Targets a clear niche (structured experimental data from full-text studies via the BGPT MCP server, 25+ fields with quality scores) with distinct triggers (evidence synthesis, full-text experimental details) and minimal overlap with general search skills.

5 / 5

Total

19

/

20

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
K-Dense-AI/scientific-agent-skills
Reviewed

Table of Contents

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