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Code Editor MCP Server

Code Editor MCP Server

by TripQi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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convert_file_encoding

Convert file encodings between formats like UTF-8, GBK, and GB2312. Specify source and target encodings, error handling, and mismatch policy for controlled conversion.

Instructions

Convert files between encodings (utf-8, gbk, gb2312).

Args: file_paths: List of absolute file paths. source_encoding: Current encoding. target_encoding: Desired encoding. error_handling: "strict" | "replace" | "ignore" mismatch_policy: "warn-skip" | "fail-fast" | "force"

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": {
      "file_paths": "<file_paths>",
      "source_encoding": "<source_encoding>",
      "target_encoding": "<target_encoding>"
    },
    "name": "convert_file_encoding"
  }
}

Input Schema

NameRequiredDescriptionDefault
file_pathsYes
source_encodingYes
target_encodingYes
error_handlingNostrict
mismatch_policyNowarn-skip

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior3/5

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

No annotations provided. The description adds value by explaining error_handling and mismatch_policy, but it does not disclose whether files are modified in place or if backups are created, nor any side effects.

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 (8 lines) and uses a clear structured args list. Every sentence adds necessary information without redundancy.

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?

The tool has 5 parameters and no schema descriptions; the description adequately explains params but lacks details on return value or whether files are overwritten. The existence of output schema is not reflected.

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?

With 0% schema coverage, the description fully explains all 5 parameters, including the enum values for error_handling and mismatch_policy, which is essential for correct usage.

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 ('Convert files between encodings'), specifies supported encodings (utf-8, gbk, gb2312), and is distinct from sibling tools like read_file or file_ops.

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 this tool versus alternatives (e.g., converting a single file vs batch). Does not explain when to choose error_handling or mismatch_policy options.

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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