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

The description adds significant behavioral detail beyond the annotations: it discloses the data source (CF analytics-engine), privacy (no PII), output shape ((pack, tool, count)), and caching behavior (5min-1h depending on window). This goes well beyond the safety hints already present in annotations and enriches the agent's understanding of the tool's behavior.

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 well-structured and front-loaded: the first sentence states the core purpose, followed by a concise bullet list of use cases and a compact factual note. Every sentence earns its place, and the total length is appropriate for the richness of information.

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 tool with one optional parameter, no output schema, and good annotations, the description covers all necessary context: what it returns, use cases, data source, caching, and privacy. It explains the output components ('top tools, top packs, total call volume') even without an output schema, making it complete for an agent to invoke correctly.

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 already describes the 'window' parameter fully, including enum values and the trade-off between shorter vs longer windows. The description mentions the window options but does not add new meaning beyond the schema. Baseline 3 is appropriate given high schema coverage.

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 states the tool's function with a specific verb ('Returns') and resource ('top tools, top packs, total call volume over a recent window'). It clearly distinguishes this from sibling tools by focusing on aggregate trending data of AI agent usage, not individual searches or tool discovery.

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 three explicit use cases with bullet points, which is clear context for when to use the tool. However, it does not explicitly name alternative tools or state 'when NOT to use it', so it does not fully meet the highest bar for exclusions.

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