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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds behavioral context by stating it draws from the 'live catalog of thousands of tools' and returns 'category-bucketed example questions', giving insight into the dynamic nature and output structure 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 a dense paragraph, but it is front-loaded with the core purpose ('onboarding entry point') and includes necessary examples, return format details, and usage instructions. Each sentence adds value, though it could be slightly trimmed without losing meaning.

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 compensates by specifying the return content (category-bucketed example questions with tool + argument shape) and covers the main use cases. The rich annotations (read-only, open-world, idempotent) complement the description, making the tool behavior sufficiently clear for a simple parameter set.

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 fully, listing all accepted values and the omission behavior. The description adds examples like 'finance', 'pharma', 'betting' but does not introduce new semantics beyond the schema. Given schema description coverage is 100%, 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 states the tool's purpose as an onboarding entry point that returns category-bucketed example questions, each with the exact tool and argument shape. It uses specific verbs ('returns', 'use FIRST') and distinguishes itself from sibling tools like 'discover_tools' by emphasizing its role in learning what to ask Pipeworx.

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 'Use this FIRST when you do not yet know what Pipeworx can do for you' and provides guidance on calling with no arguments for a full spread or with a 'topic' to focus. It also mentions the alternative meta-tools (ask_pipeworx, entity_profile, etc.) that the user might learn to call, giving clear usage context.

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