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

Annotations already declare the tool read-only, idempotent, and non-destructive. The description adds useful context: it returns the full spread when called with no arguments, and focuses when `topic` is provided. It also discloses that results are drawn from a live catalog of thousands of tools, which implies dynamic content. Minor gap: it doesn't mention any pagination or limits, but these are unlikely for this tool.

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 average but front-loaded with user-intent phrases, then a clear definition, then call guidance. Every sentence contributes useful information. It could be slightly tightened by trimming the list of example phrasings, but the impact is minimal.

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?

There is no output schema, so the description carries the duty of explaining the return value. It does so thoroughly: category-bucketed example questions, exact tool + argument shape, and the list of categories. For a simple zero-to-one-parameter tool, this is fully complete.

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% (the only parameter `topic` is fully described). The description adds value by giving concrete example values ('finance', 'pharma', 'betting') and explaining the omitted-argument behavior ('Omit for a cross-category spread'), which enriches the schema 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: it returns category-bucketed example questions to help an agent learn what Pipeworx can do. It uses specific verbs ('returns', 'onboarding entry point') and lists concrete categories, distinguishing it from general discovery tools by explicitly framing it as the first use for learning how to call meta-tools.

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 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 how to call with no arguments vs. with a `topic`, and names the alternatives (ask_pipeworx, entity_profile, compare_entities) that the agent should learn about.

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