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

Annotations indicate readOnlyHint, openWorldHint, idempotentHint=true, and destructiveHint=false. The description adds behavioral context by explaining the tool returns dynamic example questions drawn from a live catalog, without contradicting any 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 the purpose and includes a list of example natural language queries that make it clear how to invoke the tool. It is somewhat lengthy but every sentence adds value, and the structure is logical.

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's simple interface (one optional parameter, no output schema) and the annotations that cover safety and behavior, the description provides sufficient context about what the tool returns and when to use it. It explains the return format and the dynamic nature of the catalog.

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 description coverage is 100% with a clear description for the topic parameter. The description adds extra value by explaining that omitting topic gives a full spread and providing example values, enhancing understanding beyond the schema.

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 an onboarding entry point that returns category-bucketed example questions. It uses specific verbs and resources ('returns category-bucketed example questions... each with the exact tool + argument shape') and distinguishes from siblings by indicating it should be used first.

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 clearly states when to use the tool ('FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools.') and how to call it (with or without the topic argument). It does not explicitly state when not to use it, but the context is sufficiently clear.

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