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

Annotations already declare read-only, idempotent, and open-world semantics. The description adds valuable context that it returns 'exact tool + argument shape' for each example question, drawn from a live catalog of thousands of tools, and describes the optional topic behavior. This exceeds merely restating annotations without contradicting them.

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 single dense paragraph, front-loaded with user-perspective examples and covering intent, return contents, category list, invocation variants, and usage instructions. While not terse, every sentence contributes necessary context, and the structure flows logically from what it does to how to use it.

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?

For a tool with one optional parameter and no output schema, the description is fully self-contained: it explains what is returned, the category buckets, how to call it with and without the topic parameter, and when to prefer it over other tools. It even points to meta-tools for learning, providing a complete onboarding picture.

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, and the description enriches it by providing example values ('finance', 'pharma', 'betting') and clarifying that omitting it yields a cross-category spread. This adds meaningful guidance beyond the schema's basic property description.

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?

Clearly identifies the tool as the onboarding entry point that returns category-bucketed example questions, and explicitly lists the categories. It distinguishes itself by stating 'Use this FIRST' and referencing meta-tools like ask_pipeworx, entity_profile, and compare_entities, so the agent knows this is a discovery tool rather than an execution tool.

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?

Gives 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 optional topic filtering with examples and contrasts with specific sibling tools, making alternatives clear.

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