Compare Experiments

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

With no annotations provided, the description carries the behavioral disclosure burden. It is transparent about the return payload (test results, failing tests, exit codes, change size, duration, artifact counts, conditional recommendation) and explicitly notes that destroyed experiments remain comparable because findings were recorded pre-teardown.

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 purpose, then uses clear 'USE THIS' and 'RETURNS' signals to organize usage and behavior. Every sentence contributes distinct information; the examples make the usage guidance concrete without padding.

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 the simple two-parameter schema and presence of an output schema, the description covers the decision context, prerequisites implied by sibling tools, and the key edge case (destroyed experiments). Nothing critical is missing for correct invocation.

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 both parameters (experiment_ids, labels). The description adds no further parameter-level detail, which is acceptable at the baseline for fully documented schemas.

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 opens with a specific verb and resource: 'Compare two or more experiments side by side.' This clearly distinguishes it from sibling tools like create_experiment, get_experiment, and list_experiments.

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 'USE THIS when...' section gives explicit scenarios (multiple candidate fixes, runtime versions, dependency upgrades) where the tool should be chosen. It does not enumerate alternatives or explicit when-not-to-use cases, but the context is unambiguous.

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