analyze_scaling

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds useful context by clarifying that no trial collection occurs, but it does not go further into output behavior or other side effects; this matches the expected bar when annotations cover the core 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 one tight sentence, front-loads the action, and contains no filler. Every word 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?

The tool is simple: one required parameter, rich annotations, and an output schema. The description, combined with annotations and output schema, gives an agent everything needed to invoke it correctly; return-value details are already covered by the output schema.

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?

With 0% schema description coverage, the description carries the burden for parameter semantics, but it only partially compensates by saying 'existing experiment,' implying experiment_id must reference an already-created experiment. The single self-descriptive parameter plus this context is adequate, yet the description does not specify formats, sources, or further constraints 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?

The description states a specific verb ('Summarize'), a clear resource ('an existing experiment'), and a distinguishing scope ('without collecting missing trials'). This lets an agent immediately tell it apart from trial-collection tools like run_experiment and plan_experiment without opening their schemas.

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 clearly conveys when to use this tool: when an experiment already exists and a summary is needed without gathering additional trials. It provides an implicit exclusion ('without collecting missing trials') though it does not explicitly name alternative tools for when trials are missing.

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