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

Annotations already declare safe read-only, idempotent, open-world behavior. The description adds that the output is category-bucketed examples with exact tool+argument shapes, and how to call with or without a topic. 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 somewhat long but front-loaded with alternative phrasings (e.g., 'What can I ask Pipeworx?'), making it scannable. It covers all critical aspects without waste, though it could be tightened slightly.

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 is an onboarding discovery tool with good annotations and a single optional parameter, the description fully covers what the tool does, how to use it, and what to expect in the return (category-bucketed examples). No output schema is needed as the return is described adequately.

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 one optional 'topic' parameter described. The description adds concrete examples of topic values (e.g., 'finance', 'pharma') and explains that omitting topic gives a cross-category spread, which goes beyond the schema's 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 defines the tool as an onboarding entry point that returns category-bucketed example questions with tool+argument shapes. It specifies verb+resource (suggest questions) and distinguishes from siblings like ask_pipeworx by stating it's for learning what the agent can do.

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 states when to use this tool: 'Use this FIRST when you do not yet know what Pipeworx can do for you, or to learn how to call the meta-tools.' Also provides guidance on arguments (no args vs topic) and hints at alternatives by mentioning meta-tools.

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