run_benchmark

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

No annotations are provided, so the description carries the full burden. It discloses the workflow (validate, slice, upload, report stats), explicitly states the print is not started automatically, and explains the skip_validation parameter. However, it doesn't describe failure behavior or return format.

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 concise and well-structured: a one-line summary, a paragraph explaining key behavior, and a list of parameters with clear explanations. Every sentence adds value.

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 (5 parameters, no output schema, no annotations), the description provides enough information to use it correctly. It covers purpose, behavior, and parameters. Missing details about the 'report stats' output, but overall sufficient.

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 coverage is 0%, but the description includes an Args section that explains all five parameters (model_path, printer_name, printer_id, profile_path, skip_validation) with their purposes and defaults, compensating fully for the lack of schema descriptions.

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 tool's purpose: 'Prepare a benchmark print: validate → slice → upload → report stats.' It uses specific verbs and resources, and distinguishes from siblings like 'run_calibrate' or 'run_quick_print' by focusing on benchmark prints.

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 clear context: 'The print is NOT started automatically — benchmarks should be manually observed.' It implies manual observation is required but doesn't explicitly contrast with alternative tools or state when not to use it.

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