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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false. The description adds meaningful behavioral context beyond this: it states the data is 'derived from CF analytics-engine, no PII,' and that results are 'Cached 5min-1h depending on window.' These details tell the agent about freshness, source, and privacy, which annotations do not cover.

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 three sentences, front-loaded with the core purpose, followed by use cases, then technical context. No fluff; each sentence earns its place. The use-case list is slightly numbered but remains compact.

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?

Even without an output schema, the description states what is returned ('top tools, top packs, and total call volume') and the data shape ('(pack, tool, count)'). Combined with the simple parameter schema and strong annotations, the description fully equips the agent to use the tool correctly.

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 description already explains the window parameter's trade-off (shorter vs longer windows), and the tool description reinforces it. The additional value comes from linking caching behavior to the window ('Cached 5min-1h depending on window'), which adds a behavioral nuance not present in the schema. However, this is marginal, so a score of 4 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 as a trend aggregator for Pipeworx calls, stating it 'Returns the top tools, top packs, and total call volume.' It distinguishes itself from sibling tools like discover_tools by focusing on what agents are currently using rather than query-based discovery. The verb 'Returns' plus the specific resource makes it unambiguous.

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 'Useful for' section lists three concrete scenarios (discovering hot data sources, confirming canonical tools, aligning use case with agent demand). It does not explicitly state when not to use it or name alternatives, so it falls short of full exclusion guidance, but the use cases provide strong context for when this tool is appropriate.

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