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matheus-rech

Cochrane Meta-Analysis MCP Server

by matheus-rech

generate_forest_plot

Creates publication-ready forest plots from meta-analysis results, saving as high-resolution PNG following Cochrane standards.

Instructions

Create publication-ready forest plot following Cochrane standards.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
plot_styleNoVisual style of forest plotclassic
output_pathYesPath to save plot (PNG format, 300 DPI)
analysis_resultsYesMeta-analysis results
confidence_levelNoConfidence interval level (0-1)
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the purpose and that output follows Cochrane standards, but does not mention overwriting behavior, required input structure, or any side effects. This is insufficient for a tool without annotation support.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence that communicates the core purpose effectively. It is front-loaded and free of fluff, though it could include a brief note on expected input from perform_meta_analysis to improve usefulness without losing conciseness.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool generates a plot file, but the description omits what the return value is (or if it just saves to output_path), what data structure analysis_results must have, and how this fits with sibling tools. Given no annotations and no output schema, the description should provide more context to be complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all parameters. The description adds no additional meaning to the parameters (e.g., what analysis_results should look like, how plot_style differs). Baseline of 3 is appropriate since the schema handles parameter documentation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool creates a publication-ready forest plot following Cochrane standards. It uses a specific verb ('create'), a specific resource ('forest plot'), and adds a quality criterion ('publication-ready', 'Cochrane standards'), which distinguishes it from siblings like generate_cochrane_report or perform_meta_analysis.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage in a Cochrane-style meta-analysis context, but does not explicitly state when to use this tool versus alternatives like generate_cochrane_report. No when-not-to-use guidance or alternative tools are mentioned, so it relies on the user's understanding of the workflow.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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