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 context beyond these by detailing the return format: 'category-bucketed example questions... each with the exact tool + argument shape.' It also explains the effect of omitting or passing the `topic` parameter. This is useful behavioral disclosure, though it doesn't mention error conditions or rate limits, which are less critical given 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?

The description is somewhat lengthy but well-structured: it opens with a list of natural-language triggers, then explains the output, usage, and priority. Each sentence carries informational weight, though the initial list could be slightly trimmed without loss of usefulness. It earns a 4 for being mostly efficient.

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 simplicity (one optional parameter, no output schema), the description covers everything needed: what it returns (categorized examples with tool+argument shape), how to invoke it, and when to use it (first interaction, learning meta-tools). It even mentions the live catalog source. This is 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?

The schema already describes the `topic` parameter with 100% coverage. The description adds extra semantics by giving concrete examples ('finance', 'pharma', 'betting') and explaining that omitting it yields a 'cross-category spread' while passing it 'focus[es]' the results. This enriches the schema's dry 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 the tool's purpose: 'the onboarding entry point for an agent that just connected and wants to know what is worth asking.' It specifies the resource (Pipeworx) and verb (returns example questions), and differentiates from siblings like discover_tools by emphasizing it provides 'the exact tool + argument shape' for each question. This is a specific, actionable description.

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 gives explicit usage context: 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools.' It also explains how to use it (no arguments for full spread, or pass `topic`). However, it does not explicitly mention when not to use it or name alternative tools like discover_tools, hence a 4 rather than 5.

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