Physics MCP Server

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

With no annotations provided, the description carries full burden and does well by explaining the physics principle, providing a detailed return structure, and including a practical example. It doesn't mention computational limitations, error conditions, or validation rules, but covers the core behavior adequately for a calculation tool.

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?

Well-structured with clear sections: purpose explanation, parameter documentation, return specification, and example. The example is detailed but relevant. Minor room for improvement in tightening the physics explanation, but overall efficient and front-loaded with the core calculation purpose.

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 calculation tool with no annotations and no output schema, the description provides excellent coverage: clear purpose, detailed parameters with units, comprehensive return structure, and a practical example. It doesn't cover edge cases or error handling, but for this complexity level, it's nearly complete.

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?

With 0% schema description coverage, the description fully compensates by providing clear parameter explanations with units, formats (including JSON string alternative), and default values. Each parameter's physical meaning and typical values (like air density=1.225) are documented, adding significant value beyond the bare schema.

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 specific verb 'calculate' and resource 'Magnus force on a spinning ball', distinguishing it from sibling tools like calculate_drag_force or calculate_lift_force. It provides physics context about the force being perpendicular to velocity and spin axis, and mentions real-world applications like curve balls in sports.

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 through the physics context and example, suggesting it's for calculating aerodynamic effects on spinning objects. However, it doesn't explicitly state when to use this versus alternatives like calculate_drag_force or calculate_lift_force, nor does it mention prerequisites or exclusions.

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