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

The annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds meaningful behavioral context beyond that: it details the returned fields, explains that assignedUnitCount null means counts could not be read rather than zero enrollment, and points to get_experiment_results for performance.

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 core action and then enumerates the returned data in a dense but useful first sentence. Every subsequent sentence adds distinct value: id discovery, null-count semantics, the performance alternative, and the skill prerequisite.

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?

There is no output schema, so the description carries the burden of explaining return content, and it does so by listing the major fields and group-level configuration changes. It also covers the important null-count caveat and performance alternative, making the definition complete for a read-only single-experiment fetch.

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 100%, so the schema already documents projectId, environment, and experimentId. The description only indirectly helps by saying to use list_experiments to find ids; it does not add further meaning about how projectId or environment scoping works.

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 gives a specific verb and resource: 'Fetch one experiment by id'. It enumerates exactly what the result contains, including state, unit type, schedule, base configuration, targeting, group allocations, and configuration changes, which clearly distinguishes it from list_experiments and get_experiment_results.

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 explicitly names list_experiments as the way to find ids and get_experiment_results as the better performing alternative when appropriate. It also states a required prerequisite to load the understand-experiments skill first, leaving little ambiguity about when and how to use the tool.

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