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

Annotations already declare read-only, idempotent, and non-destructive behavior. The description adds valuable context about data aggregation (derived from CF analytics-engine), privacy (no PII), response format ((pack, tool, count)), and caching (5min-1h). This goes beyond the annotations, though it could be more explicit about calculation methodology or edge cases.

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: it opens with the core purpose, then lists outputs, use cases, and technical details in a clear sequence. Numbered use cases and the final data privacy/performance notes are concise and useful; no sentence is wasted.

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 one-parameter tool with no output schema, this description is highly complete: it explains what is returned, how it is computed, privacy guarantees, caching, and the three practical scenarios where an agent might need it. It fully compensates for the lack of an output schema.

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 provides a full description of the 'window' parameter, including enum values, default, and effect. The tool description itself adds no additional parameter semantics, so the baseline 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 identifies the tool's function with specific verbs and resources: "Returns the top tools, top packs, and total call volume over a recent window." It also sets a clear context ("What other AI agents are calling on Pipeworx right now") that distinguishes it from sibling tools like discover_tools or entity_profile.

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 tools, checking alignment) and explains the trade-off between window lengths. However, it does not explicitly name alternative tools or state when NOT to use this tool, so it falls slightly short of a 5.

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