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Galgame MCP

Galgame MCP

by YeXuanHs
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

vnt_query

Query an extracted Galgame bundle to search translated text, paginate results, and isolate untranslated lines.

Instructions

Search/page an extracted AI bundle.jsonl (after vnt_extract).

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": {
      "work": "<work>"
    },
    "name": "vnt_query"
  }
}

Input Schema

NameRequiredDescriptionDefault
qNo
workYes
limitNo
offsetNo
untranslated_onlyNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It only says 'Search/page' without disclosing that this is a read-only operation, how results are ordered, whether pagination is required, or any side effects. This is a significant transparency gap for a tool with no schema descriptions.

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

Conciseness4/5

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

The description is a single, front-loaded sentence that wastes no words. It earns its place, though it is too terse to be excellent—being concise is not the same as being complete.

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?

With 5 parameters, 0% schema coverage, no annotations, and no output schema, this one-sentence description is inadequate. It doesn't explain pagination, filtering behavior, or return format, so an agent cannot confidently invoke the tool without external knowledge.

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

Parameters1/5

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

Schema description coverage is 0%, so the description must compensate. However, it adds no explanation for any of the five parameters (q, work, limit, offset, untranslated_only). The agent gets no semantic guidance beyond the raw schema, making this dimension critically deficient.

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 uses a specific verb 'Search/page' and a clear resource 'extracted AI bundle.jsonl', and it explicitly ties usage to 'after vnt_extract', distinguishing it from sibling tools like vnt_extract, vnt_insert, and vnt_update. It clearly states the tool's scope.

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

Usage Guidelines4/5

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

The description provides a clear usage context ('after vnt_extract'), telling the agent when the tool is applicable. However, it does not include exclusions or alternative tool suggestions, so it falls short of a full 5.

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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