suggest_optimization_profile

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

Annotations already declare readOnly, idempotent, non-destructive, closed-world behavior, so the bar is lower. The description adds one meaningful boundary — it does not select a paid model — but says nothing about how a profile is chosen, what it contains, or how to use the result downstream.

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?

Two short sentences, with the action front-loaded and the constraint second. No wasted words, though the terseness contributes to the underspecification elsewhere.

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?

An output schema exists, so return values need not be explained, and annotations cover the safety profile. The gaps are the undefined notion of a 'profile' and the undocumented prompt parameter for a tool whose whole purpose is profile selection.

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 0%, so the single 'prompt' parameter is undocumented anywhere. The description only implies via 'for a task' that the prompt is the task text, but gives no format, length, or content expectations to compensate for the coverage gap.

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?

States a specific verb (Choose/suggest) and resource (a proportional local optimization profile) for a task. The qualifiers 'proportional' and 'local' plus the boundary 'does not select a paid model' partially distinguish it from optimize_prompt, though what a 'profile' concretely is remains undefined.

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?

Gives one explicit triggering condition, 'Use when complexity is unclear,' which is real guidance. However it names no sibling alternative (e.g., optimize_prompt, evaluate_prompt) and gives no when-not condition beyond the paid-model exclusion.

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