get_category_contributions

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

No annotations are provided, but the description compensates by disclosing the 500-result cap, pagination via offset, and the return format (event_id, event_title, event_start). It does not cover auth or rate limits, but for a read operation it is fairly transparent.

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 concise, front-loaded with the main purpose, followed by return format, use cases, and limit/pagination. Every sentence serves a purpose without unnecessary verbiage.

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 description covers the key behavioral aspects (aggregation, limit, pagination) and mentions the return fields. With an output schema present, it doesn't need to detail return values further. A minor gap is the absence of permission or instance context, but overall it's complete enough.

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 coverage is 100%, so each parameter already has a good description. The description adds minimal extra value beyond the schema, such as mentioning the 500 limit which is already in the schema. Baseline score 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 it gets contributions from all events in a category within an optional date range, highlighting efficiency compared to per-event calls. It differentiates from the sibling get_event_contributions, making the purpose specific and distinct.

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 explicitly states when to use this tool over alternatives ('far more efficient than listing events and calling get_event_contributions for each one') and provides concrete use cases. Although it doesn't explicitly mention when not to use, the guidance is clear and actionable.

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