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

Annotations already declare readOnlyHint=true and idempotentHint=true, but the description adds valuable context: it is self-aggregating, derived from CF analytics-engine, contains no PII (just pack, tool, count), and is cached for 5min-1h depending on the window. This goes beyond the annotations and explains the data source and freshness.

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 compact (4 sentences) and front-loaded with the core purpose. Each sentence adds value: main function, return contents, use cases, and behavior notes. There is no fluff or repetition of structural information.

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 lacking an output schema, the description clearly lists what is returned (top tools, top packs, total call volume) and explains the data source, privacy, and caching. Given the tool's simplicity (one optional param with enums), the description fully covers the agent's needs for selection and invocation.

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 'window' parameter, and the schema description already explains the meaning of each enum value. The tool description mentions the windows and adds a brief explanation about shorter vs longer windows, but that meaning is largely duplicated from the schema. Baseline of 3 applies when schema does the heavy lifting.

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 opens with a clear, specific statement: 'What other AI agents are calling on Pipeworx right now.' It then details exactly what is returned (top tools, top packs, total call volume) and the time windows. This distinguishes it from siblings like discover_tools or recent_alerts by focusing on aggregate trending call data.

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 (e.g., 'discovering what data sources are hot for current events', 'confirming a popular tool is the canonical choice before asking your own question'). It provides clear context for when to use it, though it does not name alternative tools or state when not to use it.

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