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Lingie.Mcp

Lingie.Mcp

by MechaBabyAi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Local

lingie_run_result

Check status of an AI generation task using its run ID. While pending, get progress updates; when complete, download output files and receive local paths.

Instructions

查询灵姬生成任务（run_id）并取回结果：仍在生成时返回状态与进度；已完成时把输出文件下载到本地并返回文件路径列表。配合 lingie_run_workflow 超时降级后的轮询使用。

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": {
      "run_id": "<run_id>"
    },
    "name": "lingie_run_result"
  }
}

Input Schema

NameRequiredDescriptionDefault
run_idYeslingie_run_workflow 返回的 run_id

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description bears the behavioral disclosure burden. It discloses the key side effect: when the task is complete, output files are downloaded locally and a file-path list is returned. It does not mention repeated-call behavior or error semantics, but the main non-obvious behavior is surfaced.

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 dense sentence, front-loaded with the action and resource, then the conditional result behavior, then the usage context. There is no filler or redundant restatement.

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?

With only one parameter and no output schema, the definition covers the main states (running vs completed), the delivered artifact (file paths), and the intended workflow position. It could add an explicit note about how it differs from lingie_run_status, but that is a minor gap given the tool's low complexity.

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 coverage is 100%, and the schema already explains that run_id is the value returned by lingie_run_workflow. The description only mentions run_id in passing and adds no extra semantic detail beyond the schema, so the baseline 3 applies.

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 states a specific verb-resource pair: query a generation task by run_id and retrieve its result. It clearly separates the two conditional behaviors—status/progress while generating versus downloading output files and returning paths on completion—which distinguishes it from the status-only sibling lingie_run_status.

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 explicitly says it is meant to be used with polling after lingie_run_workflow times out, giving concrete context for when to call it. It does not explicitly contrast it with lingie_run_status, but the intended usage position is clear enough.

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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