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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful context that these are 'saved observational' experiments rather than measured results, clarifying the nature of what is returned. It does not mention pagination behaviour, so it is not fully exhaustive.

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 short sentences, the scoping statement front-loaded and the sibling routing second. No filler, no restatement of the tool name, every clause 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?

An output schema exists, so return values need no explanation, and the read-only nature is carried by annotations. What remains is that pagination semantics for limit/cursor are never mentioned, a minor gap for a list tool with a cursor parameter.

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%, so the description carries the burden; it partially compensates by scoping the call to 'the selected brand' (mapping to the required brandId). It says nothing about limit or cursor, leaving the two pagination parameters entirely undocumented in both schema descriptions and prose.

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 (List) and a precisely scoped resource (saved observational content experiments) qualified by the brand selection. The word 'observational' cleanly separates it from the results-oriented sibling get_experiment, so an agent can distinguish the two without opening a schema.

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 routes the agent: use this to enumerate experiments, use get_experiment for measured results and coverage. That is a named alternative plus the condition that selects it, which is exactly the when-to-use guidance this dimension rewards.

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