perform_meta_analysis

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

With no annotations, the description must carry the full burden of behavioral disclosure. It only mentions the R packages and Cochrane Handbook, which provide methodological context but not behavioral traits such as whether the tool writes outputs, requires pre-validated data, or has side effects. The return value is also undisclosed, especially important given no output schema.

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

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

The description is two sentences, front-loaded with the primary action, and contains no filler. The second sentence adds useful context (Cochrane Handbook) without being verbose.

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

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

This is a complex tool with four parameters, no output schema, and no annotations. The description does not explain what the tool returns, how it connects to sibling tools (e.g., after validate_cochrane_data, before generate_forest_plot), or any limitations. The 'Validated study data' in the schema hints at prerequisites but the description does not elaborate.

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

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

Schema description coverage is 100%, with each parameter (data, model, effect_measure, heterogeneity_test) having a clear description. The tool description adds no additional parameter semantics beyond the schema, so the baseline of 3 is appropriate.

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

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

The description clearly states the tool's function: 'Execute meta-analysis using R metafor/meta packages.' This is a specific verb and resource, and it distinguishes this tool from its siblings (import_revman_data, validate_cochrane_data, generate_forest_plot, assess_publication_bias, generate_cochrane_report), which handle supporting tasks rather than the core analysis.

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

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

The description implies usage context through 'Follows Cochrane Handbook Chapter 10 guidelines,' suggesting this is a standard meta-analysis tool. However, it does not explicitly state when to use this tool versus alternatives like validate_cochrane_data or generate_forest_plot, nor does it provide exclusions or prerequisites.

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