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

Annotations already declare read-only, idempotent, non-destructive. Description adds behavioral context on return structure (category-bucketed examples with exact tool shapes) and that it draws from a live catalog.

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?

Description includes many alternative phrasings and details but remains well-organized and front-loaded with purpose. Slightly verbose for maximum conciseness but no wasted sentences.

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?

Complete description covering purpose, usage, return format, parameter semantics, and when to invoke. Given no output schema, it sufficiently explains what the tool returns.

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 has full coverage for the optional 'topic' parameter. Description enhances with examples ('finance', 'pharma', 'betting') and clarifies that omitting gives a cross-category spread.

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 as an onboarding entry point for new users, listing what Pipeworx can do and returning category-bucketed example questions. It distinguishes itself from siblings by being a meta-tool for learning.

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 says to use it first when unfamiliar or to learn about meta-tools. Provides context like 'call with no arguments for full spread' and optional topic filtering, but does not directly contrast with every sibling.

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