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

Beyond the readOnly/idempotent annotations, the description discloses that the data is self-aggregating from CF analytics-engine, contains no PII, and is cached for 5min-1h depending on the window. This adds meaningful behavioral context about freshness, privacy, and data provenance.

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 compact and front-loaded: the main function is stated in the first sentence, followed by three clearly numbered use cases and a concise data/caching note. Every sentence adds value and nothing is redundant or verbose.

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 trend tool with one optional parameter, the description fully covers what is returned (top tools, top packs, total call volume, pack/tool/count), why it's useful, how it's derived, privacy implications, and caching behavior. The lack of an output schema is compensated by the explicit return data shape.

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 description coverage is 100% for the single optional 'window' parameter, and the schema already explains the semantics of 24h, 7d, and 30d. The description repeats the window options but does not add further parameter-level meaning beyond what the schema provides, so the baseline 3 is appropriate.

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 uses a specific verb ('Returns') with a clear resource (top tools, top packs, total call volume over recent windows), and immediately distinguishes it from sibling tools by focusing on aggregate trending usage across agents. It clearly conveys the tool's unique role as a popularity/consensus signal.

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 lists three concrete use cases: discovering hot data sources, confirming canonical tool choice, and checking alignment with other agents' needs. It doesn't name alternatives or exclusions, but the context is strong and actionable enough for an agent to decide when to invoke it.

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