plan_experiment

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

Annotations declare readOnlyHint=true, but the description says 'then run it', implying execution side effects. This contradicts the read-only hint and the description does not clarify the actual behavior.

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 a single front-loaded sentence with no filler, but its brevity sacrifices semantic clarity.

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 tool's complexity (5 params, nested objects, output schema) and the readOnly contradiction, the description is too thin. It doesn't explain what binding entails, preconditions, or how it relates to run_experiment.

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?

The schema covers 80% of parameters with descriptions (adapter, parameters, experiment_name, investigation_id; only hypothesis_id lacks description). The description adds no additional parameter-level detail, so it earns the baseline for high schema coverage.

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 states it binds a declared experiment and runs it, with sequencing after workflow/capability discovery. However, 'bind' is ambiguous and the 'run it' part overlaps with sibling run_experiment, so it doesn't fully distinguish itself.

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 provides implied sequencing ('After workflow and capability discovery') but no explicit comparison to alternative tools like run_experiment or plan_fault_experiment. It lacks when-not-to-use guidance.

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