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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description goes beyond these by detailing the output structure (category-bucketed example questions with tool + argument shapes), the live catalog data source, and the behavior with/without the topic argument. No contradictions 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 a simple one-liner, but every clause earns its place: example queries, core purpose, output details, argument usage, and prioritized guidance. It is front-loaded with user-oriented phrasing ('What can I ask Pipeworx?') and maintains a logical flow. Slightly verbose but well-structured, not tautological.

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 has no output schema, the description fulfills the burden of explaining return values: category-bucketed example questions with exact tool+argument shapes. It also covers the key behavioral nuances (no-arg vs. topic arg, live catalog source, relation to meta-tools). The context signals (1 optional parameter, no output schema) are fully addressed; nothing important is left unexplained.

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 input schema already fully documents the 'topic' parameter with all possible values and the effect of omitting it. The description adds only a few redundant examples ('finance', 'pharma', 'betting') and the phrase 'to focus', which do not materially enhance the schema's already complete coverage. Per the rubric, a score of 3 is appropriate when schema coverage is high and the description adds minimal extra meaning.

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: it is the onboarding entry point for users/agents who want to know what Pipeworx can do, returning category-bucketed example questions with the exact tool and argument shape. It uses a specific verb ('suggest questions') and resource ('Pipeworx'), and distinguishes itself from siblings by framing itself as the 'FIRST' tool to use when unfamiliar with the system.

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 explicit when-to-use guidance: '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 the optional topic parameter and contrasts with the meta-tools (ask_pipeworx, entity_profile, compare_entities, etc.), giving a clear sense of when this tool is appropriate versus alternatives.

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