calculate_statistics

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

No annotations are provided, so the description carries full burden. It discloses the return structure (a dictionary with specific keys) and behavioral details like how empty venues are treated. However, it doesn't mention error handling, performance aspects (e.g., for large arrays), or side effects. The description adds some context but isn't comprehensive.

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 appropriately sized and front-loaded with the purpose, followed by structured details on arguments and returns. Every sentence earns its place by clarifying inputs and outputs, though it could be slightly more concise by integrating the argument list into the flow rather than as a separate bullet.

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?

Given 1 parameter with 0% schema coverage and no output schema, the description does well by fully explaining the parameter and return values. It covers the tool's complexity adequately, though it could improve by adding usage context or error scenarios. The lack of annotations and output schema is compensated by the detailed description.

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 0%, so the description must compensate fully. It provides detailed semantics for the single parameter 'results', specifying it as an array of publication objects with required fields ('title', 'authors', 'venue', 'year'). This adds significant meaning beyond the bare schema, fully documenting the parameter's structure and expectations.

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: 'Calculate statistics from a list of publication results.' It specifies the verb ('calculate') and resource ('statistics'), but doesn't explicitly differentiate from siblings like 'search' or 'get_author_publications' which have different functions. The purpose is clear but lacks sibling comparison.

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?

No guidance is provided on when to use this tool versus alternatives. The description doesn't mention prerequisites (e.g., needing publication data first), exclusions, or compare to siblings like 'export_bibtex' or 'get_venue_info'. Usage is implied from the purpose but not explicitly stated.

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