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

The description adds significant behavioral context beyond annotations: it states the output contains exact tool+argument shapes from a live catalog, and that it can be called with no arguments or a specific topic. 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 detailed but slightly lengthy; however, it is well-structured and front-loads the purpose. Every sentence provides useful information, earning a high score.

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 simple tool with one optional parameter and no output schema, the description covers purpose, usage, output content, and guidance on when to use it. It is fully complete given the tool's complexity and available metadata.

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 description adds meaning beyond the schema by explaining that omitting the topic gives a full spread, while passing a topic focuses the results. It also lists example topic values, which the schema's description does not.

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 returns category-bucketed example questions for onboarding, with explicit examples of user intents. It distinguishes itself from siblings like ask_pipeworx and entity_profile by being the entry point for learning what questions to ask.

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 says to use this tool FIRST when you don't know what Pipeworx can do, and provides instructions for calling with or without the topic parameter. Lacks explicit when-not-to-use vs alternatives but provides clear context.

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