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

Beyond the readOnly/idempotent annotations, the description discloses meaningful behavioral context: it is self-aggregating, derived from the CF analytics-engine, contains no PII, returns only (pack, tool, count), and is cached 5min-1h depending on window. This adds real value beyond what annotations state and fully characterizes 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 compact and front-loaded: the first sentence states what the tool returns, and the following sentences and bullets add practical use cases and behavioral caveats. Every sentence earns its place with no fluff or repetition of the title.

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 only one optional parameter, a rich schema, and strong annotations, the description fully covers what an agent needs: purpose, return content, use cases, data source, privacy, and caching behavior. There is no output schema, but the description adequately specifies what will be returned (top tools, top packs, total call volume), making it complete for selection and invocation.

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 schema already fully documents the single `window` parameter (100% coverage) with enum values and default, so the baseline is 3. The description adds extra semantics by explaining that shorter windows surface what's hot right now while longer windows show steady-state demand, and it ties caching duration to the window choice, going beyond the schema.

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') and names the exact resource: top tools, top packs, and total call volume over a recent window. It clearly positions itself as a trending/aggregation tool, distinct from sibling tools like ask_pipeworx or discover_tools by focusing on what other agents are calling. The three bullet use cases reinforce the unique purpose.

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 'Useful for' guidance with three concrete scenarios, which gives clear context for when to invoke this tool. It stops short of naming alternative tools or stating when not to use it, so it misses the full 'when-not' guidance that would earn a 5.

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