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Lingie.Mcp

Lingie.Mcp

by MechaBabyAi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
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lingie_list_workflows

Lists available Lingie workflows for image, video, and audio generation, returning each workflow's id, name, category, and free status. Use it to identify and select a workflow before submitting a generation job.

Instructions

列出灵姬中可用的工作流（图片生成/视频生成/音频等）。返回 id、名称、类别、是否免费。生成分两步：先用 lingie_workflow_capabilities 查看参数，再用 lingie_run_workflow 提交。

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "lingie_list_workflows"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description carries the burden. '列出' and the return fields imply a read-only discovery operation, and the two-step note prevents confusing it with execution, but it does not mention any limits, auth expectations, or pagination.

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?

Two concise sentences deliver purpose, output fields, and follow-up workflow. No filler or redundancy, and the most important information is front-loaded.

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?

For a zero-parameter list tool with no output schema, the description provides the purpose, output fields, and next steps, which is enough to invoke and interpret it. It stops short of explaining potential edge cases or response variations, but those are not necessary for correct usage here.

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

Parameters4/5

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

The input schema has no parameters and 100% schema coverage, so there is nothing to document. The description correctly focuses on output and follow-up tools rather than inventing parameter guidance.

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 opens with a specific verb and resource ('列出...工作流') and immediately scopes it to available generation types. It also names the return fields (id, name, category, free), which distinguishes it from parameter-inspection and submission tools.

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?

It clearly places the tool in a workflow: use workflow_capabilities to inspect parameters and run_workflow to submit. This tells the agent where list_workflows fits, though it does not explicitly state exclusion cases or when to prefer a sibling.

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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