Evaluate unit-aware quantity expressions and optionally verify the result matches an expected unit, catching dimensional errors.
Dimensional analysis (Pint). Evaluate a quantity expression like '5 meter / second * 2 second'; optionally check it matches expected_unit.
| Name | Required | Description | Default |
|---|---|---|---|
| expression | Yes | ||
| expected_unit | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full behavioral burden. It usefully names the engine (Pint), which sets expectations about supported unit syntax, but it never says what happens on a unit mismatch (error vs. boolean) or confirms the operation is side-effect free.
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?
Two compact sentences with the core action and the example front-loaded; every clause carries information and nothing is redundant.
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?
An output schema exists, so return values need no explanation, and both parameters are covered. The remaining gap is behavioral: mismatch semantics and failure modes are undefined for a tool with no annotations.
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?
Schema coverage is 0%, so the description must compensate, and it largely does: it explains that 'expression' is a quantity expression (with a worked example) and that 'expected_unit' is an optional comparison target. Syntax edge cases (e.g., accepted unit aliases) remain undocumented.
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?
States a specific verb and resource: evaluate a quantity expression via dimensional analysis, with a concrete example ('5 meter / second * 2 second'). The purpose is unmistakable, though it never explicitly contrasts itself with the adjacent verify_math sibling.
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?
Usage is only implied by the example and by 'optionally check it matches expected_unit'. There is no statement of when to prefer this over verify_math or run_code, and no exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.