get my anime statistics

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

The annotations already establish that this is a read-only, idempotent, non-destructive, open-world operation. The description adds the data domains and recommendation-oriented purpose, but it does not clarify return structure, aggregation scope, or edge cases; with rich annotations, this is useful but still moderate transparency.

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?

Two tightly written sentences: the first front-loads what data is read, and the second explains the intended combined use. There is no filler or repetition.

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?

For a zero-parameter, read-only statistics tool with no output schema, the description is largely complete: it enumerates the stat categories and states how to use them with the library. It could still specify whether statistics cover all-time or all statuses, but the core operational context is present.

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?

The tool has zero parameters, so the baseline is 4. The description does not need to explain input semantics, and it correctly focuses on what the tool reads and how to combine it with another tool.

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 uses a specific verb ('Read') and names the exact aggregate data returned: totals, mean score, formats, statuses, genres, and tags. It implicitly distinguishes itself from list-oriented siblings by emphasizing statistics and later saying to combine with the anime library pages, though it does not name an alternative explicitly.

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?

It gives a clear use case: infer preferences and combine with all pages of the anime library to recommend unseen titles. This helps an agent understand it is not a replacement for the library listing tool, but it stops short of explicit when-not-to-use guidance or naming the sibling to use for entries.

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