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

Annotations already mark the tool as read-only and idempotent. The description adds valuable behavioral context: it is self-aggregating, derived from CF analytics, contains no PII, and is cached 5min-1h depending on window. This goes beyond the annotations to describe data origin and freshness.

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 four sentences, each providing distinct value. The first sentence states the core function, followed by use cases and implementation details. No unnecessary words 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?

Given the tool's simplicity (one optional param) and comprehensive annotations, the description is complete. It covers what is returned, caching behavior, data lineage, and appropriate use cases. No output schema is needed as the return format is adequately described.

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?

There is one optional parameter (window) with an enum and a schema description that already explains the options. The tool description reinforces the behavioral difference between shorter and longer windows, adding marginal value beyond the schema. With 100% schema coverage, this is above baseline.

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 returns top tools, top packs, and total call volume over a selectable window. It includes concrete use cases (discovering hot data, confirming canonical tools) and distinguishes itself from sibling tools that are query/answer or discovery tools.

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?

Three explicit use cases are provided (discovering hot sources, confirming popular tool, aligning with use case). While it does not explicitly mention when not to use, the use cases give clear context for appropriate invocation. It lacks direct comparison to sibling alternatives but the use cases effectively imply differentiation.

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