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

Annotations already cover readOnly, openWorld, idempotent, and destructive hints. The description adds meaningful context beyond annotations: results are drawn from the live catalog, return structure is category-bucketed with exact tool+argument shapes, and behavior varies by whether `topic` is supplied. This goes beyond the annotated safety profile, though it doesn't discuss pagination or error cases.

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 dense, single paragraph that front-loads the core purpose and usage. The opening list of user-style questions ('what can I ask Pipeworx?') is a useful quick-identifier, and every subsequent clause adds necessary information about output, invocation, and positioning. 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?

No output schema exists, so the description must explain return values – it does: 'Returns category-bucketed example questions ... each with the exact tool + argument shape.' It also covers the simple input (optional topic), both invocation modes, and the tool's place in the onboarding flow, making it complete for a tool with these annotations and one optional param.

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 already describes the `topic` parameter with a full list of allowed values at 100% coverage, so baseline is 3. The description adds value by giving concrete examples ('finance', 'pharma', 'betting') and clarifying that omitting the parameter yields a cross-category spread, enriching the schema without redundancy.

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 is 'the onboarding entry point' that returns 'category-bucketed example questions' with 'the exact tool + argument shape' – a specific verb+resource with clear scope. It differentiates from siblings like discover_tools and ask_pipeworx by positioning itself as the first step for deciding what to ask.

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?

It gives explicit usage guidance: 'Use this FIRST when you do not yet know what Pipeworx can do for you' and mentions learning to call meta-tools, implying when to move on. It also explains the two invocation modes – no args for full spread or pass `topic` for focus – making the when-to-use and how-to-use clear.

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