Skip to main content
Glama
Sign In
mcp-parigp

mcp-parigp

by daedalus
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

quadregulator

Compute the regulator of a real quadratic field from its discriminant. Optionally set the precision for the calculation.

Instructions

Compute the regulator of real quadratic field.

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": {
      "D": "<D>"
    },
    "name": "quadregulator"
  }
}

Input Schema

NameRequiredDescriptionDefault
DYesDiscriminant of real quadratic field.
precisionNoOptional precision.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description must disclose behavior. It states the computation goal but omits side effects (none expected), error conditions (e.g., invalid D), or output format. The return type (a real number) is not mentioned.

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 single-sentence description is concise and front-loaded. No extraneous information. However, it is slightly terse and could benefit from a brief example or clarification of precision effect.

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 no output schema and a simple parameter set, the description should explain what the regulator is and how precision affects results. It does not mention that the regulator is a non-negative real or that D must be a positive non-square integer. The tool is underspecified for an AI agent.

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

Parameters3/5

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

Both parameters have descriptions in the schema, achieving 100% coverage. The tool description does not add extra meaning beyond the schema's explanations of 'Discriminant...' and 'Optional precision.' Baseline of 3 is appropriate.

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 computes the regulator of a real quadratic field. The verb 'Compute' and resource 'regulator' are specific. While it doesn't explicitly differentiate from siblings like 'qfbclassno' or 'quadratic_forms', the purpose is unambiguous for a mathematical tool.

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?

No guidance is provided on when to use this tool versus alternatives or any prerequisites (e.g., D must be a fundamental discriminant). The description is minimal and does not help an agent decide between this and related number theory functions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Deploy Server

Other Tools