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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the safety profile is covered. The description adds valuable behavioral context about the output: it returns category-bucketed example questions with the exact tool and argument shape, drawn from a live catalog. This goes beyond what annotations provide, though it doesn't describe potential response sizes or edge-case behavior.

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 somewhat long but well-structured: it opens with user-intent phrases, then explains the return value, then call modes, then usage guidance. Each section adds necessary information, though the opening synonym list ('what can you do? / give me ideas') could be trimmed without losing meaning.

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 has no output schema, the description thoroughly explains what the response contains (category-bucketed questions with tool+argument shapes). It also covers the optional parameter and provides a clear usage recommendation. For a simple onboarding tool, this is fully adequate.

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 schema already covers the optional `topic` parameter with a description and allowed values (100% coverage). The description reinforces this by giving concrete examples ('finance', 'pharma', 'betting') and explains the no-argument behavior. This adds value beyond the schema's enum-like list.

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 defines the tool as the onboarding entry point for answering 'what can I ask Pipeworx?' and distinguishes it from sibling tools by focusing on example questions rather than tool discovery. It uses specific verb-noun phrasing ('Returns category-bucketed example questions') and identifies the resource (Pipeworx capabilities). This is a specific, non-tautological purpose.

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 states when to use: 'Use this FIRST when you do not yet know what Pipeworx can do for you' and mentions it teaches how to call meta-tools. It also explains the two call modes (no args vs topic) and lists example topics. This gives clear context and differentiates from alternatives like discover_tools.

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