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

The annotations already declare the tool as read-only, open-world, idempotent, and non-destructive. The description adds meaningful behavioral context beyond these: it explains that it draws from a live catalog, returns a specific output structure (category-bucketed questions with tool/argument shapes), and that passing no arguments gives the full spread while passing a topic focuses results. This goes beyond what the annotations provide, though it doesn't go into exhaustive detail about response formatting.

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 a single dense paragraph but every sentence contributes useful information: purpose, usage context, parameter behavior, and return value. It's somewhat long, but not wasteful. The structure could be improved with bullets, but the current format is still scannable and information-rich.

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?

Given the tool's simplicity (0 required parameters, 1 optional) and the absence of an output schema, the description fully covers what it does, when to use it, how to call it, and what to expect in return. It explains the categories, the optional `topic` parameter, and the fact that it draws from a live catalog. No gaps remain.

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 already provides 100% coverage for the single parameter `topic`, listing the exact valid values and explaining that omitting it yields a cross-category spread. The description adds only a brief example ('e.g. "finance", "pharma", "betting"'), which doesn't significantly enhance the schema's meaning. Thus, a baseline of 3 is appropriate.

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 function: it returns category-bucketed example questions with the exact tool and argument shape to answer them. It explicitly identifies itself as the onboarding entry point ('What can I ask Pipeworx?') and distinguishes it from siblings by saying 'Use this FIRST when you do not yet know what Pipeworx can do for you.'

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 gives explicit when-to-use guidance: 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools.' It also mentions alternatives by naming the meta-tools (ask_pipeworx, entity_profile, compare_entities) as things you'll learn to call. However, it doesn't explicitly state when not to use this tool, so it stops short of a 5.

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