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quantumleeps

mcp-units

by quantumleeps

check_compatibility

Verifies whether two units measure the same physical quantity, enabling valid conversions between them.

Instructions

Check if two units are dimensionally compatible (i.e., can be converted).

Returns whether the units share the same physical dimension.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
unit_aYes
unit_bYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
unit_aYes
unit_bYes
compatibleYes
explanationYes
dimensionality_aYes
dimensionality_bYes
Behavior3/5

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It adequately states that the tool returns a boolean indicating dimensional compatibility, implying it is read-only with no side effects. However, it does not explicitly mention that it does not modify data or require special permissions, leaving some ambiguity.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise at two sentences, with no superfluous words. It front-loads the core action ('Check if two units are dimensionally compatible') and adds a clarifying parenthetical and return value explanation. Every part earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity, the description provides a basic understanding but lacks completeness. It does not specify the format of unit strings or mention the output schema (which likely indicates the boolean return). For a tool with siblings, more context on when to use it would improve completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has no descriptions for the two required parameters (unit_a, unit_b), and the description does not provide any additional meaning about them. It fails to explain that these are strings representing unit expressions, or what format is expected. With 0% schema coverage, the description offers no parameter-level guidance.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool checks if two units are dimensionally compatible, with the elaboration that it checks if they can be converted. This is distinct from sibling tools like 'convert' (which performs conversion) and 'list_compatible_units' (which lists all compatible units), making the purpose highly specific.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no guidance on when to use this tool versus its siblings. For example, it does not suggest using this tool before calling 'convert' to verify compatibility, nor does it mention that 'list_compatible_units' could provide a list of compatible units. The description gives no context on appropriate usage scenarios.

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

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