Physics MCP Server

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 that the tool returns a dictionary mapping categories to units, which is useful behavioral context. However, it lacks details on performance, error handling, or data freshness, leaving some gaps in transparency for a read-only operation.

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 front-loaded with the core purpose, followed by a detailed return structure and example. While slightly verbose due to listing all categories, each sentence adds necessary clarity, and the structure is logical and efficient for a tool with no input parameters.

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 has 0 parameters, no annotations, and no output schema, the description provides complete context for its purpose and output format. It lists all supported categories with examples, making it sufficiently comprehensive for a simple read operation, though minor details like update frequency are omitted.

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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately focuses on output semantics, listing the categories and units returned, which adds value beyond the schema. A baseline of 4 is applied as it compensates well for the lack of output 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: 'List all supported unit conversions.' It specifies the verb 'List' and the resource 'supported unit conversions,' distinguishing it from sibling tools like 'convert_unit' which performs actual conversions rather than listing available ones.

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 context by stating it returns a dictionary of supported unit categories, suggesting it should be used to discover available conversions before using 'convert_unit.' However, it does not explicitly state when to use it versus alternatives or provide exclusions, keeping it from a perfect score.

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