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

Annotations already cover read-only, idempotent, and non-destructive behavior. The description adds beyond that: explains return content (category buckets, live catalog, exact tool+argument shape) and the no-args vs. topic-focused behavior. No contradiction 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 longer than typical but every sentence contributes: example questions, purpose, return details, and usage guidance. It is front-loaded with familiar query phrasings and structured logically from purpose to invocation. 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?

The tool has only one optional parameter, no output schema, and rich annotations. The description fully covers what it returns (category buckets with tool+argument shape), when to use it, and how to invoke it, making it complete for an agent to select and call 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?

Schema coverage is 100% and the schema already describes the 'topic' parameter with valid focus areas. The description repeats the examples ('finance', 'pharma', 'betting') but does not add new semantic meaning beyond the schema, so baseline 3 is appropriate.

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 states a specific purpose: returns category-bucketed example questions with exact tool and argument shape, serving as the onboarding entry point. It clearly distinguishes itself from sibling tools by instructing to use it FIRST before meta-tools like ask_pipeworx and entity_profile.

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 provides when to use: '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 explains call patterns (no args vs. topic focus) and implies alternatives (meta-tools for actual queries).

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