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mcp-sympy

mcp-sympy

by daedalus
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

sympy_matrix_LU

Perform LU decomposition on a symbolic matrix. Input a matrix as a string to receive its lower and upper triangular factors.

Instructions

LU decomposition.

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": {
      "matrix": "<matrix>"
    },
    "name": "sympy_matrix_LU"
  }
}

Input Schema

NameRequiredDescriptionDefault
matrixYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.5/5.0
Behavior2/5

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

No annotations provided, and the description does not disclose any behavioral traits such as input format requirements, error handling, or output structure. The agent gains no extra insight beyond the tool name.

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

Conciseness2/5

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

Description is extremely brief ('LU decomposition')—underspecified rather than concise. It lacks essential details and would benefit from a sentence or two about usage and output.

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?

Despite having an output schema, the description provides no context about what the tool returns (L and U matrices, permutation). For a single-parameter tool, more information is needed to ensure correct invocation.

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?

Input schema has one parameter 'matrix' (string) with 0% description coverage. The description does not explain the expected format (e.g., list of lists, sympy expression), failing to add value beyond the schema.

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?

Description says 'LU decomposition', which is a specific and well-known matrix factorization. It clearly indicates the action and resource, distinguishing it from other matrix tools like inverse or determinant.

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 on when to use LU decomposition versus alternatives (e.g., solve, determinant). The description lacks context for appropriate use cases.

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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