Count Mentions

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the read-only safety is known. The description adds meaningful behavioral details beyond annotations: the default exclusions (REJECTED unless statuses includes it, and low-relevance scores hidden unless includeLowRelevance is true) and the explicit lack of sort/limit/offset. This enriches the agent's understanding of how filtering behaves without contradicting the annotations.

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 three tight sentences with no wasted words. The core purpose is front-loaded, usage guidance follows, and the constraint (no sort/limit/offset) is stated clearly at the end. Every sentence earns its place, making it highly efficient for an agent to parse.

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 count tool with 8 optional parameters, 100% schema coverage, and an existing output schema, the description is complete. It covers the tool's purpose, usage guidance, default filtering behavior, and the absence of pagination parameters. Nothing an agent needs to decide whether to call it and what to expect is missing.

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 input schema has 100% parameter description coverage, so the schema already documents each parameter. The description adds value by referencing that the filters are identical to list_mentions and by explaining the default behaviors that affect several parameters (statuses and includeLowRelevance). This provides context beyond the schema's individual field descriptions, though it doesn't detail every parameter.

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 opens with a specific verb and resource: 'Count mentions matching the same filters as list_mentions, returning { total } and no rows.' It clearly states what the tool does and differentiates it from list_mentions by noting it returns only the total and no rows, so an agent can distinguish the two without inspecting schemas.

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 explicitly states when to use it ('Use it for dashboards, to size a triage batch, or to decide whether paging list_mentions is worthwhile') and when not to ('skip this when you fetch rows anyway'), naming the alternative (list_mentions) and the condition that selects it. This leaves no ambiguity about tool selection.

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