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

Annotations fully cover safety (readOnly, idempotent, non-destructive). The description adds behavioral context about the return format—category-bucketed example questions with exact tool and argument shapes—and that it draws from a live catalog. 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?

The description is relatively long but well-structured: it starts with user-facing questions, then states purpose, then details return content, categories, and usage. It is front-loaded with key information, though some redundancy exists (e.g., listing categories twice).

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 description fully explains the tool's purpose, return value (example questions with tool shapes), optional parameter usage, and when to call it (first step). Despite no output schema, the description adequately describes the return content. 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?

Schema coverage is 100% (one optional param 'topic'). The description adds value beyond the schema by listing example topics ('finance', 'pharma', etc.) and explaining to omit for a cross-category spread, clarifying usage beyond the basic definition.

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 it's an onboarding entry point that returns category-bucketed example questions with tool shapes. It uses specific verbs ('Returns', 'Call') and explicitly distinguishes itself as the first tool to use when unfamiliar with Pipeworx, differentiating it from siblings like ask_pipeworx and discover_tools.

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 clear context for when to use the tool: 'FIRST when you do not yet know what Pipeworx can do for you' and 'to learn how to call the meta-tools'. It implies alternatives by mentioning other tools, but does not explicitly state when not to use it or contrast with all siblings.

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