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mcp-parigp

mcp-parigp

by daedalus
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

ellj

Compute the j-invariant of an elliptic curve given its curve structure or polynomial.

Instructions

Compute the j-invariant of an elliptic curve.

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": {
      "E": "<E>"
    },
    "name": "ellj"
  }
}

Input Schema

NameRequiredDescriptionDefault
EYesElliptic curve structure or polynomial.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior2/5

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

No annotations are provided, so the description must cover behavioral traits. It only states the computation, but does not disclose whether it modifies state, requires authentication, or has side effects. It is insufficiently transparent for a tool with no annotations.

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

Conciseness5/5

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

The description is a single, front-loaded sentence with no wasted words. It efficiently conveys the core functionality with optimal conciseness.

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

Completeness3/5

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

Given the simplicity (one parameter, no output schema), the description is adequate but incomplete. It does not mention the return type (j-invariant value) or prerequisites (e.g., E must be an elliptic curve structure). For a mathematical tool, additional context about inputs and outputs would improve completeness.

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?

The input schema has 100% description coverage for the single parameter 'E'. The description adds no additional meaning beyond the schema's description ('Elliptic curve structure or polynomial.'). Baseline 3 is appropriate as the schema already provides sufficient semantic detail.

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

Purpose5/5

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

The description clearly states the verb 'compute' and the specific resource 'the j-invariant of an elliptic curve'. It is distinct from sibling tools like ellap (point counting) or ellmul (multiplication). The purpose is unambiguous.

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. For example, it does not mention that the elliptic curve should be initialized with ellinit first, or that this is a read-only operation. The description is too minimal for usage context.

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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