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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds behavioral context: returns live examples from a catalog, and is safe to call without side effects. 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 front-loaded with trigger phrases and purpose, followed by return details and usage instructions. It is slightly verbose due to multiple trigger examples, but each part earns its place.

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?

Without an output schema, the description fully covers the return format: category-bucketed example questions with tool+argument shapes. It also explains when and how to use the tool, making it complete for an onboarding tool.

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%, but the description adds value by explaining the default behavior (no arguments for full spread) and providing example topics ('finance', 'pharma'), which the schema does not give.

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: returning category-bucketed example questions with tool+argument shapes. It distinguishes from siblings by positioning itself as an onboarding entry point, unlike ask_pipeworx which is a meta-tool for answering queries.

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?

Explicit guidance on when to use this tool: 'Use this FIRST when you do not yet know what Pipeworx can do for you'. It also explains how to call meta-tools after and provides options for topic focus vs. full spread.

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