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wemake-python-mcp

wemake-python-mcp

by guff192
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

explain_rule

Enter a wemake-python-styleguide violation code (like WPS432) to get a clear explanation of the rule, helping you understand linting errors and how to resolve them.

Instructions

Explain a wemake-python-styleguide rule by code (e.g. WPS432, 432).

Args: code: WPS violation code (e.g. 'WPS432' or '432').

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": {
      "code": "<code>"
    },
    "name": "explain_rule"
  }
}

Input Schema

NameRequiredDescriptionDefault
codeYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior2/5

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

With no annotations provided, the description must disclose behavioral traits itself. It only states the purpose and parameter format but does not describe return behavior, error handling, or any side effects. For a read-only explanation tool, some mention of expected output or failure modes would be helpful; the absence leaves the agent with unmet expectations.

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 concise and front-loaded: a single purpose sentence followed by a clear 'Args' section. It avoids unnecessary words and is appropriately sized for a simple one-parameter tool.

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

Completeness4/5

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

Given the tool's simplicity (one parameter, output schema available), the description adequately covers purpose and parameter semantics. It does not elaborate on behavior or usage contexts, but the output schema likely documents return values. A small decrement is warranted due to the lack of usage guidance and behavioral transparency.

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

Parameters5/5

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

The input schema has 0% description coverage, but the tool description compensates fully by documenting the 'code' parameter with format and examples ('WPS432' or '432'). This adds meaning beyond the raw schema and ensures the agent knows exactly what to pass.

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 tool's purpose: 'Explain a wemake-python-styleguide rule by code'. It uses a specific verb (explain) and resource (wemake-python-styleguide rule), and the scope is unambiguous. This distinguishes it from sibling tools like lint_file or update_rule_db, which operate on files or the rule database rather than providing rule explanations.

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. The description and parameter documentation do not mention any conditions, prerequisites, or exclusions relative to sibling tools such as lint_code or lint_project. The usage context is implied by the name but not explicitly stated.

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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