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mcp-parigp

mcp-parigp

by daedalus
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

eisenstein

Calculate Eisenstein series E_k(q) with weight k (even >=2), optional harmonic rank and precision.

Instructions

Compute the Eisenstein series E_k(q).

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": {
      "k": "<k>"
    },
    "name": "eisenstein"
  }
}

Input Schema

NameRequiredDescriptionDefault
kYesWeight (even >= 2).
nNoHarmonic rank (default 1).
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 should disclose behavioral traits. It only says 'Compute the Eisenstein series', omitting details like return type, potential errors, or computational traits (e.g., series expansion nature).

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 sentence that efficiently conveys the core purpose. No extraneous words; it is appropriately concise for a straightforward mathematical function.

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 specialized nature of Eisenstein series and the presence of many sibling modular form tools, the description lacks context (e.g., weight restrictions, series representation, relationship to other modular forms). No output schema exists, increasing the need for description 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?

Schema description coverage is 100%, so the schema already documents all parameters. The description adds no extra meaning beyond the schema's field descriptions; baseline 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 'Compute the Eisenstein series E_k(q)', which specifies the verb and resource. However, it does not differentiate from sibling tools like eta or theta, but it is specific enough for an expert.

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 (e.g., eta, theta, modular_lambda) or what conditions (e.g., k even >=2) are necessary beyond the schema.

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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