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 checks equilibrium with a tolerance, computes net force and magnitudes, and returns a dict with specific keys. It also implies a deterministic calculation without side effects, though it does not mention error handling or computational limits.

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: it starts with the core purpose, provides essential context, details parameters and returns, and includes a practical example. Each sentence adds value without redundancy, making it efficient and easy to parse for an AI agent.

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 (2 parameters, no annotations, no output schema), the description is complete: it explains purpose, usage, parameters, return values, and provides an example. It covers all necessary aspects for an AI agent to understand and invoke the tool correctly, compensating for the lack of structured data.

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. It adds significant meaning beyond the schema: it explains that 'forces' are 'List of force vectors [[x,y,z], ...] in Newtons (or JSON string)' and 'tolerance' is 'Tolerance for equilibrium check (fraction, default 0.01)'. This clarifies data formats, units, and default values, fully documenting both parameters.

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: 'Check if forces are in equilibrium: ΣF = 0. Verifies whether a system of forces is balanced (net force = 0).' It specifies the verb ('check', 'verifies'), resource ('forces'), and scope ('equilibrium', 'balanced'), distinguishing it from siblings like 'check_torque_balance' or 'check_equilibrium' by focusing specifically on force balance.

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: 'Essential for statics problems and structural analysis.' This gives guidance on when to use it, though it does not explicitly state when not to use it or name alternatives among siblings. The example further illustrates usage in a bridge support scenario, reinforcing appropriate contexts.

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