DeepSeek-MCP

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refactor_code

Refactor code to adhere to Clean Code, SOLID principles, and optimal patterns. Optionally specify a refactoring goal for targeted improvements.

Instructions

Provide refactored version of code adhering to Clean Code, SOLID principles, and optimal patterns

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": "refactor_code"
  }
}

Input Schema

Name	Required	Description
`code`	Yes	Code to refactor
`model`	No	Model to use (default: deepseek-reasoner)
`provider`	No	AI Provider
`refactor_goal`	No	Specific refactoring goal (e.g. extract functions, convert to async, apply pattern)

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Aug 4, 2026

TDQS

B3.4/5.0

Behavior2/5

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

With no annotations, the description carries full responsibility for behavioral disclosure. It does not specify whether the tool returns refactored code as a string, modifies files in place, preserves original behavior, or has any side effects. This is a significant gap for a transformation tool.

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 redundant words. It efficiently captures the core purpose and quality targets, making it easy to parse and act upon.

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, no annotations, and four parameters, the description is notably incomplete. It omits return value expectations, usage context, and behavioral constraints, leaving an agent without sufficient guidance for proper invocation and result handling.

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 baseline is 3. The description mentions 'Clean Code, SOLID principles, and optimal patterns', which adds context to the refactor_goal parameter but does not detail parameter formats or relationships beyond what the schema already provides.

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 action ('Provide refactored version of code') and the resource ('code'), with explicit quality criteria (Clean Code, SOLID, optimal patterns). This distinguishes it from sibling tools like review_code (analysis only) and generate_code (creation from scratch).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for improving existing code but does not explicitly state when to use it versus alternatives like generate_code or review_code. There are no exclusions or alternative recommendations, leaving the agent to infer the appropriate context.

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