Predict Cost

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

Annotations already indicate readOnlyHint=true and idempotentHint=true, so the description adds value by specifying that predictions are 'based on historical samples for similar call patterns'. This gives context beyond annotations, though it could disclose limitations like accuracy depending on data.

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 sentence with no redundancy, but it could be slightly more structured (e.g., separating purpose from method). Still, it's concise and front-loaded.

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 (one parameter, output schema present), the description is complete. It covers what the tool does and how it works, with no obvious gaps.

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 parameter 'code' is fully described in the schema (100% coverage), and the description adds only the context of historical samples, not additional semantics for the parameter. Baseline 3 is appropriate since the schema does the heavy lifting.

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 clearly states the verb 'predict' and the resource 'token cost and latency of executing code', distinguishing it from siblings like execute_code or get_metrics. It answers what the tool does precisely.

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 implies usage for cost estimation before execution but provides no explicit when-to-use, when-not-to-use, or alternatives. It lacks guidance on when this tool is preferred over siblings.

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