Physics MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: it calculates velocity and acceleration from position data, extracts a specified component, and returns a dictionary with computed values. It clarifies the return format and includes an example, though it could mention assumptions about input data quality or numerical methods used.

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 well-structured and front-loaded with the core purpose, followed by parameter details, return values, and an example. Most sentences earn their place, though the example could be slightly more concise. It avoids unnecessary repetition and stays focused on key information.

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 moderate complexity (3 parameters, no annotations, no output schema), the description is largely complete. It covers purpose, parameters, returns, and includes an example. However, it could improve by addressing potential edge cases or error conditions, which would enhance completeness for a computational tool.

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 schema description coverage is 0%, so the description must compensate fully. It successfully adds meaning beyond the schema by explaining each parameter: 'times' as time values in seconds, 'positions' as position vectors in meters, and 'component' with its options and default. This provides essential context missing from the 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 tool's purpose with specific verbs ('generate', 'calculates', 'extracts') and resources ('motion graph data', 'position, velocity, acceleration vs time'). It distinguishes itself from siblings like 'calculate_acceleration_from_position' by emphasizing comprehensive data generation for graphing rather than single calculations.

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 example and parameter explanations, suggesting it's for analyzing motion data. However, it lacks explicit guidance on when to use this tool versus alternatives like 'calculate_instantaneous_velocity' or 'fit_trajectory', and does not 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.