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 behavioral context beyond annotations by noting the output is 'drawn from the live catalog of thousands of tools' (implying dynamic, current data) and that it teaches tool+argument shapes. It also advises using this as a first step, which is useful operational context.

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 front-loaded with example user queries, immediately making the tool's purpose relatable. Every sentence earns its place: the purpose, the output structure, the optional parameter, and the usage recommendation. At ~130 words it is dense but not bloated, and the use of em-dashes and lists aids readability.

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?

With no output schema, the description explains what the tool returns: 'category-bucketed example questions... with the exact tool + argument shape.' It covers the full call pattern, including the optional topic parameter and the intended use as an onboarding aid. Given the tool's simple interface (one optional parameter), the description is complete and leaves no critical gaps.

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 describes the `topic` parameter with its allowed focus areas and the omit behavior ('Omit for a cross-category spread'). The description only repeats examples ('finance', 'pharma', 'betting') and says 'to focus', adding no new semantic information. With 100% schema coverage, the baseline of 3 is appropriate.

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 identifies this as 'the onboarding entry point' that 'returns category-bucketed example questions... each with the exact tool + argument shape.' It distinguishes from siblings by positioning it as the FIRST tool to use when an agent doesn't know Pipeworx's capabilities, and explicitly names meta-tools (ask_pipeworx, entity_profile) as things this tool teaches how to call.

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 call variants ('no arguments for the full spread, or pass topic to focus') and names alternatives via the meta-tool examples.

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