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

Annotations already declare read-only, non-destructive, idempotent behavior. The description adds context about the return content (category-bucketed examples with tool shapes) and that it's an onboarding tool, but does not introduce any behavioral traits beyond what annotations imply.

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 detailed yet structured, starting with common user queries, then explaining output and usage. It's slightly verbose by listing many categories, but every sentence adds value. The front-loading of example queries is effective.

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 no output schema, the description adequately explains the output (category-bucketed questions with tool shapes). It covers all needed context: when to use, how to call with/without topics, and what to expect from the response. The tool's simplicity (1 optional param) is fully addressed.

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% with the single `topic` parameter well-described. The description adds significant value by listing example focus areas (finance, pharma, etc.) and explaining that omitting the parameter gives 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 returns 'category-bucketed example questions' with tool+argument shapes, using specific verbs like 'returns' and 'drawn from the live catalog'. It distinguishes from siblings like ask_pipeworx by positioning itself as an onboarding entry point for exploring capabilities.

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 tells when to use: 'Use this FIRST when you do not yet know what Pipeworx can do for you'. Also explains optional topic parameter to focus, and suggests learning how to call other meta-tools, providing clear guidance on alternatives.

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