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

Even though readOnlyHint and destructiveHint already signal a safe read operation, the description goes well beyond annotations. It discloses the exact output shape, the order-balancing methodology, the free-tier limit, the key-based scaling, and the pre-registered result that the forecast did not beat the simplest guess. This is rich, honest behavioral disclosure.

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 the main purpose and organized logically through output, constraints, and caveat. It is mostly efficient, though the sentence 'The same people see page A and page B' somewhat repeats the earlier 'on the same simulated people' clause, adding minor 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 there is no output schema, the description fully compensates by listing the returned call, reason, movement counts, top objections, and report link. It also covers key operational context: public URL requirement, free allowance, key-based scaling, and reliability caveat. An agent has enough information to invoke the tool correctly and interpret its results.

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 high at 80%, so the schema already documents most parameters. The description adds meaningful semantics beyond that: URLs must be publicly reachable, the same simulated people see both pages, and the free allowance caps tests at 10 simulated people without a key. These details clarify the count and URL parameters in ways the schema alone does not.

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 a specific verb and resource: compare two web pages and get Mimiq's call on which to ship. It also gives concrete examples like preview deployment versus production. However, it does not explicitly distinguish itself from sibling tools such as compare_copy or test_page, so it stops short of full sibling differentiation.

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?

The description provides clear use context: comparing two pages on the same simulated audience to make a shipping decision. It adds practical constraints such as needing public URLs, the free allowance, and the caveat that the forecast should be treated as a fast first read. It does not explicitly state when not to use this tool or which sibling to prefer, so exclusions are missing.

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