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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context: 'Self-aggregating signal — derived from CF analytics-engine, no PII, just (pack, tool, count). Cached 5min-1h depending on window.' This explains data provenance, privacy, and caching behavior, enriching beyond the structured metadata.

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 with the core action, then lists use cases with numbered points, and ends with caching/privacy details. It is slightly verbose but every sentence adds meaningful information. The use cases and caveats are concise and earn their place.

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 read-only tool with one parameter, the description is highly complete. It explains the return values (top tools, top packs, total call volume), the aggregation source, lack of PII, and caching behavior. Since there is no output schema, the description adequately covers what the agent needs to know without missing critical aspects.

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% and the parameter description in the schema already explains the window enum, including the distinction between short and long windows. The tool description repeats the window options but does not add new semantic detail beyond what the schema provides, so the baseline of 3 applies.

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: 'Returns the top tools, top packs, and total call volume over a recent window.' It uses a specific verb ('returns') and identifies the resource ('top tools, top packs, total call volume'). The use cases further distinguish it from sibling tools like discover_tools by focusing on current popularity and canonical choice, not just 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 explicit use cases: 'discovering what data sources are hot for current events,' 'confirming a popular tool is the canonical choice before asking your own question,' and 'seeing whether your use case aligns with what most agents need.' It does not explicitly contrast with alternatives or state when not to use it, but the situational 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.