stats_by_type

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only states the basic aggregation and does not clarify data scope, whether the count is global or filtered, or any assumptions about ticket states. No extra context beyond the obvious operation.

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?

A single, succinct sentence that is front-loaded with the core action and resource. It avoids redundancy and is appropriately sized for a parameterless stats tool.

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 simple aggregation tool with no parameters and an output schema available, the description is mostly complete. It could explicitly state that it covers all tickets, but the lack of parameters implies global scope. The output schema covers return details, so no further description is necessary.

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 schema provides no parameter semantics. The baseline for 0 params is 4, and the description adds no parameter information, but it doesn't need to. The description covers the only relevant semantic aspect by naming the ticket types.

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: returning the number of tickets by type, with the two types explicitly listed (Incident / Service Request). This specific verb+resource combination distinguishes it from sibling stats tools like stats_by_priority or stats_by_status.

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. It doesn't mention scenarios, exclusions, or related tools. The user must infer usage solely from the purpose.

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