Calculates the most common number in a list to identify the value that occurs most often in a data set, revealing the statistical mode of your data.
Finds the most common number in a list of numbers. For several operations or chained steps in one call, use batch_calc.
| Name | Required | Description | Default |
|---|---|---|---|
| numbers | Yes | Array of numbers to find the mode of |
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, and it says nothing about how ties (multiple equally common values) are handled, what happens with an empty array, or what the return value looks like. For a statistics operation where multimodal input is common, this is a meaningful gap.
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 short sentences with zero waste: the purpose leads, and the batch_calc alternative follows. Nothing is padded or restated from the tool name.
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?
The tool is simple with one well-documented parameter and no output schema, so little is required. However, with no annotations and no explanation of tie-breaking or the return shape, an agent cannot fully predict the result of an ambiguous call.
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 description coverage is 100% and the single 'numbers' parameter is fully documented in the schema itself, so the description adds no parameter detail. Baseline 3 applies; no format, ordering, or type constraints are added beyond the 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?
States a specific verb and resource: 'Finds the most common number in a list of numbers.' This clearly distinguishes it from statistical siblings like mean, median, min, and max, so an agent can select it without inspecting the schema.
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?
Explicitly routes multi-operation or chained work to batch_calc, which is genuine alternative guidance. It does not state when this tool is inappropriate (e.g. multimodal or empty input), so it falls short of full when/when-not coverage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.