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

Annotations declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, indicating a safe, non-destructive read operation. The description adds beyond this: explanation of data source ('derived from CF analytics-engine'), privacy guarantee ('no PII'), and caching behavior ('Cached 5min-1h'). No contradictions.

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 a single sentence defining the core functionality, then lists use cases, and ends with technical details. Every sentence provides essential information without redundancy. Concise and well-organized.

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?

Given the tool's simplicity (one parameter, no output schema or nested objects), the description covers all necessary aspects: purpose, usage, parameter semantics, and behavioral traits (caching, no PII). No gaps are evident for an agent to correctly invoke the tool.

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% for the single parameter 'window.' The description adds semantic guidance: 'Shorter windows surface what's hot right now; longer windows show steady-state demand.' This goes beyond the schema enum values 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 starts with a clear and specific statement: 'What other AI agents are calling on Pipeworx right now.' It explicitly mentions the resource (Pipeworx trending data), the action (returns top tools, packs, call volume), and the temporal scope (recent window). This distinguishes it from siblings like discover_tools or ask_pipeworx.

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 three concrete use cases with bullet points, such as 'discovering what data sources are hot for current events.' While it doesn't explicitly name alternative tools, the context implies when to use trending vs. other tools. The use cases are clear and actionable.

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