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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so safety is covered. The description adds genuine behavioral context beyond that: missing values stay unknown and insufficient observations cannot establish a winner, warning the agent against over-interpreting sparse results.

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 tightly written sentences with the core action front-loaded and the interpretation caveat following. Nothing is wasted or redundant.

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?

An output schema exists, so return values need not be explained, and the safety profile is carried by annotations. The description is complete for a simple read tool, though it leaves parameter semantics entirely to the schema.

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 description coverage is 0% for two required parameters, so the burden falls on the description, which mentions neither brandId nor experimentId. The parameter names are largely self-explanatory, but the description contributes no added meaning (e.g., which brand the experiment is scoped to).

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?

States a specific verb and resource: compares latest stored metrics for a saved experiment, and specifies the scope includes coverage and timestamps. It reads clearly as distinct from list_experiments, but never explicitly names or differentiates itself from its 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?

The description gives no when-to-use guidance, no prerequisites, and does not point to alternative tools such as list_experiments or compare_intelligence. The second sentence is interpretive framing about results, not usage direction.

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