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

Annotations (readOnlyHint=true, openWorldHint=true, idempotentHint=true, destructiveHint=false) already indicate safety and non-destructive behavior. The description adds value by explaining that the tool returns dynamic example questions from a live catalog and mentions the return structure (category-bucketed). This goes beyond annotations by clarifying the interactive, onboarding nature of the tool. It does not contradict 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 well-structured: it starts with aliases, then explains the return type, then gives usage instructions and advice. Every sentence contributes to clarity, though some aliases are repetitive. It front-loads key information and is efficient overall.

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 one optional parameter, no required fields, full schema coverage, and no output schema, the description is highly complete. It explains when to use it, what it returns (category-bucketed example questions with tool+argument shapes), and how to use it (with or without topic). It also positions it within the tool ecosystem as an onboarding entry point.

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 only parameter (topic) has 100% schema coverage, so the baseline is 3. The description adds minimal extra meaning: it repeats the categories from the schema and notes that omitting gives a cross-category spread. This is helpful but not significantly beyond the schema's own description, which already lists the options and usage.

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: serving as an onboarding entry point for new users to discover what they can ask Pipeworx. It lists aliases and specifies that it returns category-bucketed example questions with tool and argument shapes. This distinguishes it from siblings like ask_pipeworx, which is for asking actual questions rather than suggesting them.

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 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools.' This gives clear when-to-use guidance. It also implies when not to use it: after initial exploration, use the specific meta-tools like ask_pipeworx. The alternative tools are mentioned in the description as 'meta-tools' (ask_pipeworx, entity_profile, etc.), providing context for alternatives.

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