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Galgame MCP

Galgame MCP

by YeXuanHs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

image_convert

Convert image files between PNG, TLG5, TLG6, and other supported formats. Specify input and output paths to perform the conversion.

Instructions

Convert between PNG, TLG5, TLG6 and other supported image formats.

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": {
      "input": "<input>",
      "output": "<output>"
    },
    "name": "image_convert"
  }
}

Input Schema

NameRequiredDescriptionDefault
inputYes
formatNoTarget format; default from output extension
outputYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.1/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It only states the conversion action and supported formats, but does not disclose potential side effects, whether it overwrites existing files, error conditions, or the output structure. The mention of 'other supported image formats' is vague and provides no additional behavioral detail.

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 that conveys the core purpose efficiently. Every word earns its place, with no superfluous details or padding. It is appropriately concise.

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?

For a tool with three parameters and no output schema, the description is too minimal to be complete. It lacks critical context such as return behavior, file overwrite semantics, supported format lists, or error scenarios. Compared to more thorough descriptions for similarly scoped tools, this is insufficient.

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?

The input schema has only 33% coverage (only 'format' has a description), yet the description does not compensate by explaining the 'input' or 'output' parameters. It implies these are image files but does not clarify that they are file paths, the role of 'output' as destination, or how 'format' relates to file extensions. The description adds minimal meaning beyond the schema.

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 function with a specific verb ('Convert') and resource (image formats), listing explicit formats like PNG, TLG5, and TLG6. This distinguishes it from sibling tools such as image_probe (which inspects images) and image_pack_xp3 (which packs images into archives). The purpose is unambiguous.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention image_probe for inspecting images or image_pack_xp3 for packaging, nor does it state any prerequisites or exclusions. There is no explicit 'when to use' or 'when not to use' context.

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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