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

Annotations already declare read-only, idempotent, open-world. Description adds that results are 'drawn from the live catalog of thousands of tools', implying dynamic output, and explains it returns suggestions with exact tool call shapes. 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 front-loaded with user query examples and then explains output, parameters, and usage. It is a single dense paragraph but each sentence contributes useful information; could be slightly trimmed but remains structured and readable.

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 read-only tool with no output schema, the description fully explains what it returns (category-bucketed questions with exact tool + argument shape), the optional topic parameter, and the intended use case. It even mentions the live catalog and categories covered.

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 description already fully documents the 'topic' parameter with allowed values and omission behavior. The description merely repeats examples ('finance', 'pharma', 'betting') and 'topic' usage without adding new semantic detail; hence baseline 3.

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 helps an agent discover what to ask Pipeworx, returning category-bucketed example questions with exact tool and argument shape. It distinguishes itself from sibling meta-tools like ask_pipeworx and discover_tools by positioning itself as the FIRST onboarding entry point.

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, or to learn how to call the meta-tools'. Provides clear guidance on when to invoke and even suggests parameter usage (call with no arguments for full spread, or pass topic to focus).

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