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

Annotations already establish read-only, open-world, idempotent, non-destructive behavior. The description adds meaningful context: results are drawn from the 'live catalog of thousands of tools,' the output is grouped by category, and each example includes the resolving tool and argument shape. No contradiction; these details go beyond what annotations provide.

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 long but every section serves a purpose: user-phrase examples, return content, invocation modes, and strategic placement. It is front-loaded with natural-language triggers and uses a structured category list rather than prose. Slightly wordy in the opening phrase list, but appropriate for an onboarding tool.

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 carries the return-value burden; it explains the categorical buckets and that each item maps to a concrete tool/argument shape. It covers the zero-parameter call, optional `topic`, and a clear first-use scenario. The live-catalog note sets expectations about freshness, making the description complete for this 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 fully describes `topic` with allowed focus areas and omission behavior, so schema coverage is 100%. The description mostly restates this ('pass topic to focus') and only adds an extra example ('betting') already present in the schema. This meets the baseline but doesn't add substantial new semantics.

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 names the tool as the 'onboarding entry point' and specifies the exact deliverable: category-bucketed example questions paired with the exact tool and argument shape. It clearly distinguishes from sibling discovery tools by its focus on prompting the user with 'what can I ask' rather than raw tool lookup. Specific verb+resource: 'Returns category-bucketed example questions'.

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?

Explicitly instructs to 'Use this FIRST when you do not yet know what Pipeworx can do for you' or to learn how to call the meta-tools, naming ask_pipeworx, entity_profile, compare_entities. This is an explicit when-to-use directive with concrete alternatives. It also explains the no-argument vs `topic` invocation modes.

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