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mcp-parigp

mcp-parigp

by daedalus
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

Mod

Create a modular number or polynomial by specifying a value and a modulus, enabling modular arithmetic computations in number theory.

Instructions

Create a modular number or polynomial.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "a": "<a>",
      "b": "<b>"
    },
    "name": "Mod"
  }
}

Input Schema

NameRequiredDescriptionDefault
aYesValue.
bYesModulus (integer or polynomial).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations provided, the description must fully disclose behavioral traits, but it only says 'Create a modular number or polynomial.' It does not mention whether the result is a special object, how negative moduli are handled, or if the output type matches the input type (e.g., polynomial input yields polynomial modular result). The lack of detail hurts transparency.

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 a single short sentence that immediately states the tool's action. It is concise and front-loaded, with no extraneous information. However, it could be slightly longer to include key behavioral details without losing conciseness.

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 tool has two required parameters, no output schema, and no annotations, the description should provide more context such as the type of return value, default behavior, or examples. The current description is too sparse to allow an agent to invoke it correctly without additional knowledge.

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 covers both parameters with descriptions, but those descriptions are minimal: 'Value.' and 'Modulus (integer or polynomial).' The tool description adds no further meaning beyond the schema's own text. Since schema coverage is 100%, a baseline of 3 is justified, but the lack of additional context (e.g., constraints on value relative to modulus) reduces the score to 2.

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 creates a modular number or polynomial, which conveys its specific purpose. Although it distinguishes from most siblings by being the only modular creation tool, it does not explicitly differentiate from closely related operations like addition or multiplication modulo a prime. Overall, the purpose is clear but lacks sibling differentiation.

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 no guidance on when to use this tool versus alternatives such as 'znorder' or 'lift'. It neither states the context for use nor excludes any scenarios. This leaves the agent without direction on selecting this tool among many similar mathematical operations.

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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