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

Annotations already declare read-only, open-world, idempotent, and non-destructive behavior. The description adds beyond this by explaining that results are drawn from a live catalog of thousands of tools, and that each example includes the exact tool + argument shape. It also notes the output is category-bucketed, which helps the agent anticipate response structure.

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 densely packed with useful information but is somewhat long and meandering. It front-loads example queries and clearly states the purpose early. Every sentence contributes, but the structure could be tightened; however, the richness justifies the 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?

The tool is simple (one optional parameter, no required arguments). The description fully explains what the output looks like (category-bucketed examples with tool+argument shapes), when to use it, and the parameter behavior. With strong annotations and full schema coverage, this description is complete for an agent to confidently 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% (the `topic` parameter is described in the schema). The description adds value by giving concrete examples ('finance', 'pharma', 'betting') and explaining the effect of omitting the parameter (cross-category spread). It reinforces the schema meaning without redundancy.

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's purpose: it is the onboarding entry point that returns category-bucketed example questions, each with the exact tool and argument shape. It distinguishes itself from sibling tools like ask_pipeworx (which likely answers questions) by positioning itself as a discovery/guidance tool.

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 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools.' This gives clear when-to-use guidance and implicitly contrasts with more direct action tools. It also explains the optional topic parameter for focused use.

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