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

Annotations already flag readOnlyHint, openWorldHint, idempotentHint, and destructiveHint, so the safety profile is clear. The description adds valuable behavioral context: it returns category-bucketed example questions with exact tool and argument shapes from the live catalog, and explains how the 'topic' parameter affects the response. It doesn't mention performance or rate limits, but given annotations cover safety, this is sufficient.

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 a single comprehensive sentence that front-loads example queries and conveys the purpose, return value, and usage. It is efficient and every clause contributes meaningful information. While not as tightly structured as a two-sentence summary, it avoids fluff and is appropriately sized for the tool's scope.

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 simple read-only tool with no output schema, the description is fully complete. It explains what the tool returns (category-bucketed questions with tool+argument shape), when to use it, how to invoke it with or without the topic parameter, and its role relative to meta-tools. The agent has all necessary information to select and call this tool correctly.

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 has 100% coverage with a description for the single 'topic' parameter. The description enriches this by clarifying that omitting the parameter returns a full spread, while passing a topic focuses the results. It also provides concrete examples ('finance', 'pharma', 'betting'), which the schema lacks. This goes beyond simple restatement.

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 the tool as an onboarding entry point for an agent to discover what questions it can ask Pipeworx. It uses specific verbs like 'returns category-bucketed example questions' and distinguishes it from siblings by positioning it as the 'FIRST' tool to use when unfamiliar with Pipeworx, unlike discover_tools or 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?

Explicitly states '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 provides clear guidance on when to pass the optional 'topic' parameter versus omitting it, and gives examples. This effectively tells the agent when to use this tool and the context.

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