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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, destructiveHint false. The description adds valuable behavioral context: self-aggregating signal derived from CF analytics-engine, no PII, cached 5min-1h depending on window. This goes well beyond what annotations 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 concise: a single introductory sentence followed by a brief list of use cases. Every sentence adds value, no redundancy. Information is front-loaded and well-structured.

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?

Despite having no output schema, the description explains the return content (top tools, top packs, total call volume), data source, privacy, caching, and parameter behavior. For a simple tool with one optional parameter, this is fully complete.

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 only parameter 'window' explaining its enum values. The description adds further semantic value by explaining the trade-off: 'Shorter windows surface what's hot right now; longer windows show steady-state demand.' This enriches the schema's description.

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 'top tools, top packs, and total call volume' over a recent window. The verb 'returns' is specific, the resource is 'Pipeworx trending data', and the description distinguishes it from siblings by focusing on popularity metrics rather than search or discovery.

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 choice, and checking alignment with agent trends. It provides context on when to use, though it does not explicitly state when not to use or list alternatives among siblings, which would push it to a 5.

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