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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the description doesn't need to repeat those. It adds useful context: the tool is an onboarding entry point, draws from a live catalog, and returns example questions with tool 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 example queries and a clear statement of purpose. It lists categories and behavior in a structured way. While somewhat long, every sentence adds value, and the information is well-organized.

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 one optional parameter, no output schema, and numerous sibling tools, the description is highly complete. It explains the tool's purpose, usage, return content, and context for when to call it first. Without an output schema, it adequately describes what to expect.

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% (only 'topic' parameter), so baseline is 3. The description adds meaning by listing example values (finance, pharma, etc.) and explaining that omitting topic gives a full spread. This goes beyond the schema's 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 states that the tool returns category-bucketed example questions to help users understand what to ask Pipeworx. It lists specific categories (finance, pharma, etc.) and explains the optional topic parameter. This clearly distinguishes it from sibling tools like ask_pipeworx or entity_profile.

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', and mentions learning how to call meta-tools like ask_pipeworx, entity_profile, compare_entities. This provides excellent when-to-use and when-not-to-use guidance.

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