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

Annotations already mark it read-only and non-destructive; the description adds the behavioral outcome: which engines are searched, a ranked source list, and an 'appears in X of N' gap. No contradiction with the 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?

Two sentences front-load the core purpose and return shape, then give usage triggers. Every clause earns its place; there is no filler or redundancy.

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 a simple two-parameter schema, read-only annotations, and a rich output schema, the description covers inputs, engines, output semantics, and when to use it. Nothing needed for correct invocation is missing.

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%, so the schema already documents query and domain. The description adds buyer-query context and concrete examples ('best real estate agent in Tampa', 'example.com') that help an agent map user intent to the two parameters.

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 opens with a concrete verb-object pair: 'find the exact sources ChatGPT, Perplexity, Claude, and Gemini cite' for a given query and domain, then specifies the returned ranked source list and domain-presence gap. This makes the tool's function unmistakable and clearly distinct from the audit/booking siblings.

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?

It gives explicit triggers: 'Use this whenever a user wants to know where AI gets its answers about their industry, which pages AI trusts for a query, or whether their business shows up in AI recommendations.' It does not name alternatives or when-not-to-use, but the invocation context is clear.

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