configure_model

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

No annotations are provided, so the description carries the full burden of disclosing behavioral traits. It indicates a state-changing operation (setting model, effort, terminal mode) but does not explain side effects, persistence, scope (current session vs global), or reversibility. This lack of detail beyond the immediate action is a notable gap for a mutation-type tool without annotation support.

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 concise sentence followed by examples. It is front-loaded with the primary purpose, and every element earns its place. There is no fluff or redundancy, making it optimally brief for an AI agent to parse quickly.

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?

For a simple configuration tool with only one parameter and no output schema, the description is largely complete: it states the action, the outputs are not needed, and the instruction parameter is well-documented in the schema. The main gap is the lack of behavioral transparency (persistence/scope), but given the tool's simplicity, the overall completeness is strong. A slight deduction is warranted for the missing side-effect disclosure.

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 input schema already has a fully descriptive parameter ('instruction' with examples), giving 100% schema coverage. The description reinforces this with additional examples, but adds little beyond what the schema provides. The baseline of 3 is appropriate; the description adds marginal value only through extra example phrases.

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 clear action: 'Set model, effort level, and terminal mode.' This is a specific verb with concrete resources. The example phrases further clarify the scope (e.g., 'Use Opus for coding', 'Set high effort', 'Run in background mode'). This distinguishes it from sibling tools like configure_workers or execute_task, making the purpose unmistakable.

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 example natural language commands that demonstrate when to invoke the tool ('Say 'Use Opus for coding' or 'Set high effort'...'), establishing clear contexts for use. It does not explicitly list alternatives or exclusions, but the examples make usage evident. This ranks slightly below a perfect score because it lacks explicit 'when not to use' guidance, but the context is strong.

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