analyze_scaling

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

Annotations already declare readOnlyHint and idempotentHint, but the description adds a valuable behavioral nuance: the tool does not collect missing trials. This goes beyond the generic read-only annotation and helps the agent understand the tool's scope of action, even though it doesn't describe return formats or side effects.

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, grammatically complete sentence of eight words. It is front-loaded with the verb and contains no redundant or extraneous words.

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 param) and has an output schema, so return value details are covered elsewhere. However, the description leaves ambiguity about what 'scaling' specifically refers to and what the summary includes, especially in the context of many sibling analyze_* tools. Basic guidance exists but lacks domain-specific context.

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 has one parameter (experiment_id) with no description, and the description does not explain what this ID refers to, how to obtain it, or any constraints. With 0% schema coverage, the description fails to compensate, leaving the agent to infer the parameter's meaning from context.

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') and resource ('existing experiment'), and adds a distinguishing qualifier ('without collecting missing trials') that separates it from related tools like run_experiment or plan_experiment. This clearly identifies what the tool does and how it differs from 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?

It provides a clear usage context: use when you want to summarize an existing experiment. The phrase 'without collecting missing trials' serves as an exclusion, telling the agent not to use this tool if trial collection is needed. However, it does not explicitly name alternative tools, so it stops short of full guidance.

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