assess_publication_bias

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the methods used but doesn't disclose side effects, dependencies, expected return values, or any caveats about the input data. The absence of such information leaves the agent uncertain about the tool's behavior beyond its basic function.

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 a single sentence that is concise and front-loaded with the core purpose. It avoids unnecessary wording and is easy to scan. However, it is perhaps too terse to provide meaningful behavioral or usage context, so it loses a point for being underspecified rather than merely concise.

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?

The tool has a nested object parameter (analysis_results) and an optional methods array, but the description does not explain how to provide these, what a valid analysis_results object looks like, or what the tool returns. With no output schema, the description is insufficient to guide an agent through a complete workflow, especially given the complexity of the input.

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%, so the baseline is 3. The description adds no additional meaning beyond the schema's parameter descriptions, but since the schema already explains each parameter adequately, it doesn't need to compensate. The description doesn't clarify the relationship between analysis_results and the methods, but this is a minor gap.

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 purpose: 'Perform publication bias assessment using funnel plots, Egger's test, and trim-and-fill method.' This specifies the verb (perform), the resource (publication bias assessment), and the methods involved, effectively distinguishing it from sibling tools like perform_meta_analysis or generate_forest_plot.

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 provides no guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. It doesn't mention that publication bias assessment typically follows a meta-analysis, nor does it reference sibling tools or indicate the required input format for analysis_results.

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