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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds behavioral context beyond these by explaining the return structure (category-bucketed example questions with tool+argument shapes) and how omitting or providing the topic parameter changes the result. No contradiction with 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?

Although the description is lengthy, every sentence contributes value: it opens with common user queries, lists categories, describes the output format, gives invocation guidance, and names related tools. The structure is well-organized and front-loaded, making it dense but not wasteful.

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 having no output schema, the description fully covers what the tool returns (category-bucketed example questions with exact tool and argument shapes) and how to tailor the call. It also situates the tool within the broader toolset, making it complete for an agent to decide when and how to use it.

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 description covers 100% of the single parameter, listing valid focus areas and the default cross-category behavior. The description reinforces this by providing concrete examples ('finance', 'pharma', 'betting') and explicitly stating 'Call with no arguments for the full spread, or pass `topic` to focus', adding a bit of 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 explicitly states the tool's function: it 'returns category-bucketed example questions' and is 'the onboarding entry point'. It clearly identifies the resource (Pipeworx) and distinguishes itself from siblings by naming meta-tools like ask_pipeworx, entity_profile, and compare_entities, with a directive to use it FIRST.

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 provides explicit usage guidance: 'Use this FIRST when you do not yet know what Pipeworx can do for you' and explains how to focus via the topic parameter. It also lists alternatives (meta-tools) to learn about after onboarding, giving clear context for when this tool is appropriate.

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