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 value beyond these by detailing the output structure (category-bucketed questions), the source (live catalog), and the optional parameter behavior. 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 moderately long but each sentence adds value: it enumerates triggering queries, explains the output, and provides usage advice. It is front-loaded with the key queries and essential info. Some minor redundancy could be trimmed but overall efficient for an onboarding tool.

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 that the tool has only one optional parameter and no output schema, the description fully explains what the tool does and what to expect. It covers input possibilities, output structure, and when to use it, making it self-sufficient for an agent.

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 covers the single optional parameter 'topic' with a description. The description adds meaning by listing example values (finance, pharma, etc.) and explaining that omitting it returns a cross-category spread, which goes beyond the schema's generic 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 clearly states the tool's purpose: returns category-bucketed example questions with exact tool+argument shapes, serving as an onboarding entry point. It distinguishes itself from sibling tools like ask_pipeworx or discover_tools by specifying its role as the first stop for users unfamiliar with 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 explicitly says when to use the tool: 'first when you do not yet know what Pipeworx can do', and provides example queries. While it does not explicitly state when not to use it, the context makes the use case clear. The mention of optional topic focusing adds practical guidance.

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