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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive behavior. The description adds valuable context beyond annotations by describing what the tool returns (category-bucketed example questions with exact tool+argument shapes) and the optional topic behavior. It does not contradict annotations and provides sufficient transparency about its read-only, discovery-oriented nature.

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 long but well-structured with leading example phrases and a clear breakdown. It front-loads the purpose and usage, then provides details on return contents and topic parameter. Some repetition in the example phrases could be trimmed, but each sentence earns its place by clarifying the tool's value proposition.

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?

Given the tool's purpose as an onboarding guide, the description covers all necessary context: what it returns, how to call it (with/without topic), when to use it first, and its relationship to meta-tools. Even without an output schema, the description sufficiently explains the return format and provides enough detail for effective selection and invocation.

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%, so the parameter is documented. The description adds extra meaning by giving concrete topic examples ('finance', 'pharma', 'betting') and explaining the default behavior when omitted ('cross-category spread'). This goes beyond the schema's enumeration by clarifying expected values and default behavior.

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 it is the onboarding entry point for suggesting questions and returns category-bucketed example questions with tool mappings. It uses specific verbs (suggest, returns) and explicitly distinguishes its role from meta-tools by positioning it as the FIRST tool to use when unfamiliar with Pipeworx capabilities.

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?

Explicit usage guidance is provided: '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 for full spread or pass a topic, giving clear context for when and how to use the tool.

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