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

Annotations already indicate the tool is read-only, open-world, idempotent, and non-destructive. The description adds that it returns category-bucketed example questions with tool and argument shapes, which is useful behavioral context beyond the annotations.

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 slightly long but well-structured and front-loaded with trigger phrases. Every sentence adds value, detailing the return format, options, and usage. The length is justified by the tool's purpose as an onboarding entry point.

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 no output schema, the description fully explains the return value: category-bucketed example questions with tool and argument shapes. It covers the single parameter, usage scenarios, and the tool's role as an onboarding tool, making it complete for an agent to understand.

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 describes the optional topic parameter with a brief description. The description adds meaning by listing example topics (finance, pharma, etc.) and explaining how omitting the parameter produces a full cross-category spread, enriching the schema's information.

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 purpose: it returns category-bucketed example questions for Pipeworx, serving as an onboarding entry point. It distinguishes itself from siblings like ask_pipeworx by positioning itself as the first tool to use when the agent doesn't know Pipeworx's capabilities.

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 says to use this tool first when the agent doesn't know what Pipeworx can do, providing clear usage guidance. It does not explicitly mention when not to use it or alternatives, but the context is sufficient for appropriate selection.

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