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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds meaningful behavioral context: it is a self-aggregating signal derived from CF analytics-engine, states 'no PII, just (pack, tool, count)', and discloses caching (5min-1h depending on window)—all beyond what annotations provide.

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 a single paragraph with a clear purpose statement followed by a 'Useful for:' list and provenance note. All sentences contribute, though the list could be slightly trimmed without losing value.

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?

With no output schema, the description states the return content (top tools, top packs, total call volume) and clarifies the data shape as '(pack, tool, count)'. It also covers caching and data source, making it complete for a 1-param read-only tool.

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 fully covers the only parameter 'window' with its enum values and trade-off explanation. The tool description adds no additional parameter semantics beyond mentioning the window, so with 100% schema coverage, the baseline score of 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 clearly states the action ('Returns') and resource ('top tools, top packs, and total call volume'), and frames it specifically as 'what other AI agents are calling on Pipeworx right now.' This distinguishes it from sibling tools like discover_tools by emphasizing the aggregated, social-signal aspect.

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 'Useful for:' list provides three explicit use cases, and the window guidance contrasts short vs long windows. However, it does not explicitly name alternative tools or state when not to use it, so it lacks explicit exclusions.

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