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

Annotations already declare the tool as read-only, open-world, idempotent, and non-destructive. The description adds behavioral context: it returns example questions with exact tool+argument shapes, drawn from the live catalog, and that omitting topic gives a full spread. This supplements annotations effectively without contradiction.

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 somewhat long but every sentence serves a purpose. It starts with common queries (front-loading), then describes output, then usage instructions. It could be slightly more concise, but the structure is logical 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?

Given no output schema, the description thoroughly explains what is returned: category-bucketed example questions with exact tool+argument shapes. It connects to sibling tools (meta-tools like ask_pipeworx) and covers the single parameter's behavior. For a simple onboarding tool, this is complete and informative.

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% with the optional topic parameter. The description adds value by listing specific focus area options (finance, pharma, etc.) and clarifying that omitting topic yields a cross-category spread. This goes beyond the schema's description, which only provides enum-like examples but not the behavioral implications.

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: returning category-bucketed example questions that demonstrate Pipeworx capabilities. It lists multiple synonyms ("what can I ask", "give me ideas", etc.) and explicitly positions itself as the onboarding entry point, distinguishing it from siblings like ask_pipeworx and discover_tools.

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 to use this tool first when unsure what Pipeworx can do, and to learn how to call meta-tools. It explains the optional topic parameter to focus on a specific area. While it doesn't explicitly list when not to use it, the 'first' instruction implies it precedes other tools, providing adequate guidance.

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