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

Annotations already indicate a safe, read-only, idempotent operation. The description adds meaningful behavior beyond that: it self-aggregates from CF analytics-engine, contains no PII, and is cached for 5min-1h depending on the window. This extra context justifies a 4.

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, starting with a clear headline, followed by return details, use cases, and data source/caching notes. It is slightly longer than necessary (e.g., repeating the window options), but every sentence contributes value, so it earns a 4.

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 remarkably complete. It explains what is returned, the data source, caching behavior, privacy characteristics, and multiple use cases. No critical information is missing, so this is a 5.

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 documents the only parameter ('window') with an enum and a clear description of how short vs. long windows behave. Since schema_description_coverage is 100%, the baseline is 3, and the description does not add significant new parameter semantics beyond what the schema already provides.

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: showing what other AI agents are calling on Pipeworx, returning top tools, packs, and call volume over a recent window. It is specific and resource-focused, but it does not explicitly distinguish itself from siblings like discover_tools, so it stops short of a 5.

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 concrete use cases: discovering hot data sources, confirming canonical tools, and aligning with agent behavior. This is clear context for when to use the tool, but it does not mention when not to use it or name alternatives, so it earns a 4 rather than a 5.

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