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IBM

MCP Math Server

by IBM

deterministic_miller_rabin

Perform deterministic primality testing for integers using the Miller-Rabin algorithm with known witnesses for specific ranges.

Instructions

Deterministic Miller-Rabin test using known witnesses for specific ranges. (Domain: arithmetic, Category: advanced_primality)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the test is 'deterministic' and uses 'known witnesses for specific ranges,' which hints at reliability constraints, but doesn't explain what happens outside those ranges, error conditions, computational complexity, or output format. For a primality testing tool with zero annotation coverage, this is insufficient.

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

Conciseness4/5

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

The description is concise and front-loaded in a single sentence, with no wasted words. It efficiently conveys the core functionality, though it could benefit from additional context without sacrificing brevity.

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

Completeness2/5

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

Given the complexity of primality testing, no annotations, no output schema, and low parameter coverage, the description is incomplete. It lacks details on ranges, witnesses, result interpretation, and error handling, making it inadequate for reliable tool invocation in a mathematical context.

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

Parameters2/5

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

The input schema has 1 parameter (n) with 0% description coverage. The description adds that 'n' is tested for primality, but doesn't specify valid ranges, integer constraints, or handling of edge cases (e.g., negative numbers, small values). Given the low schema coverage, the description provides minimal compensation, leaving the parameter poorly documented.

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

Purpose4/5

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

The description clearly states the tool performs a 'Deterministic Miller-Rabin test' with 'known witnesses for specific ranges,' which is a specific verb+resource combination. It distinguishes from sibling tools like 'miller_rabin_test' by specifying it's deterministic rather than probabilistic, though it doesn't explicitly contrast with other primality tests like 'aks_primality_test' or 'fermat_primality_test'.

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?

The description provides minimal guidance: it mentions 'specific ranges' but doesn't clarify what those ranges are or when to use this deterministic version versus probabilistic alternatives like 'miller_rabin_test.' No explicit when-to-use or when-not-to-use criteria are given, leaving the agent with little practical direction.

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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