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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds behavior beyond annotations: it returns category-bucketed examples with tool/argument shapes, and mentions the optional topic parameter affects focus. No contradiction 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 natural language example queries, which is useful. It is somewhat long, but each part serves a purpose: examples, return value description, calling pattern, and when to use. Minor redundancy with the schema could be trimmed.

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 tool with no output schema, the description explains what is returned (category-bucketed questions with tool/argument shapes), how to call it with and without parameters, and the specific use case. It also mentions the live catalog and meta-tools, making the context complete enough for an agent.

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 provides 100% coverage of the 'topic' parameter with a list of values and 'omit for cross-category spread'. The description adds examples like 'finance', 'pharma', 'betting' but these are redundant with the schema, providing marginal additional value.

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 identifies suggest_questions as an onboarding entry point that returns category-bucketed example questions, each with the exact tool and argument shape. This specific verb+resource combination distinguishes it from siblings like discover_tools and 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?

The description 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', providing a clear starting point. It does not name alternative tools, but the 'FIRST' emphasis implies when to select this over others.

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