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

The description adds substantial context beyond the annotations: it explains the data is self-aggregating from CF analytics-engine, contains no PII, returns only (pack, tool, count), and is cached for 5min–1h depending on the window. These details inform the agent about data provenance, privacy, freshness, and output shape, which are not available from the annotations alone.

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 front-loaded with the core purpose and then organized with a clear 'Useful for' list and technical notes. It is slightly verbose but every sentence earns its place; the structure aids comprehension without excessive fluff.

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, read-only tool with one optional parameter, the description is complete. It states what is returned (top tools, top packs, call volume), the exact data shape (pack, tool, count), and the caching behavior. No output schema exists, but the description sufficiently covers return values and edge considerations.

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 fully describes the single 'window' parameter, including enum values and their semantic differences (short vs. long windows). The description only repeats this information, adding no new insight, so the baseline score of 3 is appropriate for complete schema coverage.

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: it returns trending information about what AI agents are calling on Pipeworx, specifically top tools, packs, and call volume over selectable windows. This is a specific resource (Pipeworx trending data) with a clear scope, and it distinguishes itself from siblings like discover_tools by focusing on real-time usage trends.

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 explicit use cases (discovering hot data sources, confirming canonical tools, aligning with agent behavior) that tell the agent when to invoke it. However, it lacks explicit 'when not to use' or alternatives, so it does not fully meet the highest bar for guidance.

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