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

Annotations already cover read-only/idempotent/non-destructive, so the description adds genuine value with the credential requirement and the concrete 403 failure mode for sandbox keys from self-registration. Only pagination/result size is left undisclosed.

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?

Three tightly packed sentences: purpose and returned fields first, then the filter, then prerequisites. No filler, and the failure mode is stated as a concrete status code.

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?

With no output schema, the description usefully lists what each item contains and covers auth/workspace preconditions. Only result volume/pagination behavior is missing for a list tool that could return many experiments.

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% and the enum values document the status field fully; the description's sentence about 'drafts, active, paused or completed' mostly restates the enum. It adds filtering intent but no syntax or defaults beyond the schema.

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 ('List your workspace's price experiments') and enumerates the fields returned (key, name, status, variants, target sample size), which distinguishes it from get_experiment_definition / get_experiment_results 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?

Explicitly says when to pass the status filter and what each state yields, plus the prerequisites (Last Price credential, claimed workspace). It doesn't name a sibling alternative, but the usage context is clear.

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