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

Beyond the annotations (readOnlyHint, openWorldHint, idempotentHint, destructiveHint), the description discloses the data source (CF analytics-engine), privacy guarantee (no PII), exact aggregated fields (pack, tool, count), and caching behavior (5min-1h). This is rich operational context that annotations alone do not 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 well-structured: a bold opening statement, a bulleted list of use cases, and a concise technical note on data source, privacy, and caching. Every sentence adds value, and it is front-loaded with the purpose.

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?

The description covers purpose, use cases, data source, privacy, caching, and parameter semantics. However, since there is no output schema, it would be helpful to specify the exact return format (e.g., structure of 'top tools' and 'total call volume'), though the aggregation is simple enough that this is a minor gap.

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 window parameter is fully covered in the schema (100% coverage), but the description adds semantic meaning by explaining the trade-off: 'Shorter windows surface what's hot right now; longer windows show steady-state demand.' This goes beyond the schema enum descriptions and helps the agent choose appropriately.

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 what the tool does: 'What other AI agents are calling on Pipeworx right now. Returns the top tools, top packs, and total call volume over a recent window.' This is a specific verb+resource+output, and it distinguishes itself from sibling tools like discover_tools by focusing on trending call volume from other agents.

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 explicitly lists three use cases: discovering hot data sources, confirming canonical tool choice, and checking use-case alignment. This gives clear context for when to use the tool, though it does not explicitly name alternatives or exclusions, which prevents a 5.

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