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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behaviors. The description adds value by detailing the response structure (category-bucketed examples with tool+argument shapes) and the effect of the topic parameter, going beyond annotations without contradiction.

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 comprehensive but slightly verbose; however, every sentence adds value. It is well-structured with examples and a clear action item, earning a high score for clarity despite minor length.

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 fully explains the return format (category-bucketed example questions with tool+argument shapes) and the optional parameter behavior. It covers all needed context for effective use.

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%, but the description enriches the topic parameter by listing example values (finance, pharma, etc.) and explaining that omission gives a full cross-category spread. This adds practical meaning beyond the schema.

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 that the tool returns category-bucketed example questions with exact tool and argument shapes, serving as an onboarding entry point. It distinguishes itself from sibling tools like ask_pipeworx by focusing on discovery rather than direct answering.

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?

Explicitly instructs to use this tool first when unfamiliar with Pipeworx, and describes how to use the optional topic parameter to focus on a specific area. Contrasts with meta-tools, providing clear when-to-use guidance.

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