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

Annotations already declare readOnlyHint=true, openWorldHint=true, idempotentHint=true, and destructiveHint=false. The description goes beyond this by describing the output structure (category-bucketed example questions with exact tool+argument shape), the source (live catalog), and the behavior of omitting vs passing topic. It effectively communicates what the agent can expect without an output schema.

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 single dense paragraph that front-loads example queries, then explains the return payload, parameter behavior, and usage context. Every sentence earns its place: no filler, no repetition of schema details, and each clause adds a distinct piece of information. It is appropriately sized for the tool's complexity.

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 has an optional parameter, returns a complex categorized structure, and serves as an onboarding guide, the description covers all essential aspects: purpose, usage timing, return value shape, parameter semantics, and relationship to sibling tools. It even explains what the output contains (category-bucketed questions with tool+argument shape) despite the absence of an output schema, making it fully self-contained.

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 schema already provides 100% coverage for the single optional 'topic' parameter, describing its allowed values. The description adds semantic depth by explaining the behavioral difference between omitting it ('full spread') and passing it ('highly focused'), plus giving concrete examples like 'finance', 'pharma', 'betting' that map to the schema's list. This enriches the parameter's meaning beyond the schema description.

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 explicitly states the tool's purpose as 'the onboarding entry point' that returns 'category-bucketed example questions' with 'exact tool + argument shape' for each. It uses specific verbs like 'Returns' and 'Use this FIRST', clearly distinguishing it from sibling meta-tools (e.g., ask_pipeworx, entity_profile). The many example query phrasings make the purpose unmistakable.

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 context: '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 vary usage with or without the topic parameter. However, it does not explicitly state when NOT to use it (exclusions), only implying that it is for initial orientation rather than ongoing use.

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