Calculate the geometric mean of positive values to find average growth rates. Provide a list of numbers to compute the central tendency for multiplicative data.
Calculate the geometric mean of positive values.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
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 does add one genuinely useful constraint not present in the schema — that values must be positive — since the schema accepts any number including negatives and zero. However, it says nothing about what happens on invalid input (error vs. NaN), empty arrays, or how the result is returned.
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?
A single front-loaded sentence with no filler. Every word earns its place and the key constraint appears immediately.
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?
For a one-parameter math utility with an output schema (so return format needn't be explained) and no annotations, purpose plus input-domain constraint is close to sufficient. The main missing piece is error behavior for zero/negative or empty input.
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% and the single parameter is just an untyped-by-description array of numbers. The phrase 'of positive values' does add a real semantic constraint on the input domain that the schema does not express. It still leaves open whether the array may be empty, whether duplicates or ordering matter.
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 (Calculate) and resource (geometric mean) plus a scope qualifier (positive values). This is clearly distinct from the sibling harmonic_mean or mean, but the description never names the alternatives, so it relies on the agent's own domain knowledge to differentiate.
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?
No when-to-use guidance, no mention of when geometric mean is preferred over the arithmetic mean or harmonic_mean siblings, and no exclusions. Usage is only implicitly inferable from the mathematical name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.