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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false, so safety is covered. The description adds context about the return payload: it returns category-bucketed example questions with exact tool + argument shape drawn from a live catalog, and notes that it is the onboarding entry point—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 a single dense paragraph with multiple examples and details, but every sentence contributes: user queries, return format, parameter behavior, and usage guidance. It is slightly verbose but front-loaded with the most important information, earning a 4 rather than a 5.

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 what the tool returns (category-bucketed example questions with exact tool+argument shapes) and how to invoke it (no args or with a topic). It also contextualizes when it should be used first, covering both purpose and behavioral expectations.

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 input schema fully describes the `topic` parameter with an enumerated list of categories and notes that omitting it gives a cross-category spread, so description coverage is 100%. The description adds only example values ('finance', 'pharma', 'betting') that are already listed in the schema, offering no new parameter semantics; baseline 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 opens with a range of user phrasing examples ('What can I ask Pipeworx?', 'what is Pipeworx good for?') and clearly identifies the tool as the onboarding entry point that returns category-bucketed example questions with exact tool+argument shapes. This distinguishes it from siblings like discover_tools and ask_pipeworx by specifying its function and scope.

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 states 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools', giving a clear condition for when to use it. It also contrasts with alternatives by mentioning meta-tools (ask_pipeworx, entity_profile, etc.) and provides parameter usage instructions (no args for full spread, topic to focus).

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