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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds behavioral context by explaining that it returns category-bucketed example questions drawn from a live catalog of thousands of tools, and that it can be called with no arguments or with a topic. This goes beyond the annotations without contradicting them.

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 well-structured and front-loaded with natural language query examples, then explains what the tool returns, followed by usage and when-to-use. Every sentence earns its place, with no wasted words.

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 required parameters and no output schema, the description is remarkably complete. It covers the purpose, return content (category-bucketed questions with tool+argument shape), parameter usage, and explicit usage guidance, making it self-sufficient for an agent to decide when and how to invoke it.

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% for the single 'topic' parameter, and the schema already lists the valid focus areas and the 'omit for cross-category spread' instruction. The description adds examples (e.g., 'finance', 'pharma', 'betting') but these are a subset of what's in the schema, so it adds minimal extra meaning beyond the structured data.

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: it is the onboarding entry point that returns category-bucketed example questions with exact tool and argument shapes. It distinguishes itself from siblings like discover_tools by emphasizing its role as a first-stop for users wondering what to 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 gives explicit when-to-use guidance: 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools.' It also lists example user queries and explains that passing a topic focuses the results, while omitting it returns the full spread.

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