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

Annotations already declare read-only, open-world, idempotent, and non-destructive. The description adds substantial context: self-aggregating signal, derived from CF analytics-engine, no PII, data shape (pack, tool, count), and caching behavior (5min-1h depending on window). This goes well 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 appropriately sized and front-loaded: first sentence states purpose, then returns, then use cases, then technical caveats. Every sentence contributes value, with no fluff or repetition. The 'Useful for' list is concise and actionable.

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 tool with one optional parameter and no output schema, the description is complete. It covers purpose, use cases, data origin, caching, and a hint at the result shape ('just (pack, tool, count)'). There are no critical gaps.

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 covers 'window' at 100% with a clear description. The tool description reinforces the semantics but adds extra behavioral detail tied to the parameter: 'Cached 5min-1h depending on window' and the implication that shorter windows are for hot items, longer for steady-state. This adds value beyond the schema alone.

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 with a specific verb ('Returns') and resource ('what other AI agents are calling on Pipeworx right now'), and defines the scope (top tools, packs, total call volume over a window). It effectively distinguishes itself from sibling tools like discover_tools by focusing on collaborative usage data rather than general 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?

Provides three explicit use cases under 'Useful for', which gives clear context on when to use it. However, it does not explicitly mention when not to use it or name alternative tools like discover_tools, so it stops short of the full 5 for explicit alternatives/exclusions.

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