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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint false, so the safety profile is clear. The description adds valuable context by describing the returned structure ('category-bucketed example questions... with the exact tool + argument shape') and parameter behavior ('Call with no arguments for the full spread, or pass topic to focus'). 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 longer than ideal, with repeated question paraphrases at the start, but it is appropriately sized for a complex tool with many categories and usage modes. It is front-loaded with the core purpose and quickly moves to return format and usage, with no wasted sentences.

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 format, parameter semantics, and usage context. Since there is no output schema, it covers the return values thoroughly by listing categories and the tool+argument shape. It also explains the live catalog aspect and how to focus with the topic parameter, making it complete for an onboarding 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 description coverage is 100% for the single 'topic' parameter, and the schema already lists the exact focus areas and the omit behavior. The description repeats these values ('finance', 'pharma', 'betting') without adding new meaning beyond a slight emphasis on focusing. Thus it adds minimal value over 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 clearly identifies the tool as an onboarding entry point that 'returns category-bucketed example questions' with exact tool and argument shapes. It uses specific verbs like 'suggest' and 'onboard' and distinguishes itself from siblings like ask_pipeworx by focusing on generating examples rather than answering queries directly.

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 provides a strong when-to-use directive. However, it does not explicitly state when not to use it or name specific alternative tools for other scenarios, though it mentions learning how to call meta-tools.

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