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

Annotations already mark the tool as readOnlyHint, idempotentHint, and non-destructive. The description adds valuable behavioral context: data is derived from CF analytics-engine, contains no PII, and is cached 5min-1h depending on window. This goes well beyond annotations and fully informs the agent.

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, well-organized paragraph of four sentences. It front-loads the core function, then lists use cases, and ends with technical details (derivation, privacy, caching). Every sentence adds value with no redundancy.

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 trend tool with one optional parameter and no output schema, the description covers everything: what is returned, usage windows, use cases, data source, privacy, and caching behavior. The annotations and schema are rich, and the description fills any remaining 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?

Schema coverage is 100% with a description for the 'window' parameter. The description's mention of windows ('24h, 7d, or 30d') reinforces the schema but does not add new information beyond what the schema already provides. Thus 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 tool returns 'the top tools, top packs, and total call volume over a recent window', providing a specific verb and resource. The three listed use cases further clarify its purpose, and it is easily distinguishable from sibling tools like 'discover_tools' or 'ask_pipeworx' due to its focus on trending metrics.

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 lists three concrete use cases (discovering hot data sources, confirming canonical tools, aligning use cases), giving clear context for when to use this tool. However, it does not explicitly exclude scenarios or compare with siblings like 'discover_tools', which could overlap.

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