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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds behavioral context beyond that: it returns category-bucketed example questions drawn from the live catalog, and explains the effect of passing or omitting the topic parameter. It does not contradict 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?

Though longer than a one-liner, every sentence earns its place: triggering example questions, output structure, live-catalog source, topic behavior, and explicit usage-first guidance. It is front-loaded with the key purpose and remains information-dense without waste.

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 simple shape (zero required parameters, no output schema) and rich annotations, the description fully covers what the tool does, what it returns, how to vary results, and when to use it. No meaningful behavioral or usage 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% for the single optional topic parameter, so the schema already documents meaning and the omit-for-full-spread behavior. The description adds examples like 'finance', 'pharma', 'betting', but these are illustrative rather than genuinely new semantics, so the 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 opens with a specific verb and resource: it returns category-bucketed example questions with the exact tool and argument shape, and clearly identifies itself as the onboarding entry point. This distinguishes it from sibling tools like ask_pipeworx or discover_tools by framing it as the meta-level guide for what can be asked.

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?

Explicit usage guidance is provided: '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 is a clear directive for when to use it and positions it against related tools by naming the meta-tools to learn about.

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