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upamune
by upamune

human_mouth_tool

Speak specified utterances aloud using human vocal capabilities through a human-operated interface.

Instructions

人間が口を使って指定された言葉を発話します。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
utteranceYes

Implementation Reference

  • The handler function for human_mouth_tool. It generates a unique task ID, formats the utterance as a task instruction, adds it to the database using db_utils, polls asynchronously for completion using wait_for_task_completion, and returns the human-provided response.
    @mcp.tool()
    async def human_mouth_tool(utterance: str, ctx: Context) -> Dict[str, str]:
        """人間が口を使って指定された言葉を発話します。"""
        task_id = str(uuid.uuid4())
        formatted_utterance = f"👄 口を使って発話: {utterance}"
    
        # タスクをデータベースに追加
        db_utils.add_task(task_id, formatted_utterance)
    
        # ログ出力
        sys.stderr.write(f"Human task created: {task_id}. Waiting for completion...\n")
    
        # 結果を待機(非同期ポーリング)
        result = await wait_for_task_completion(task_id)
    
        # ログ出力
        sys.stderr.write(f"Human task {task_id} completed.\n")
    
        return {"response": result}
  • JSON schema definition for the human_mouth_tool, specifying input 'utterance' parameter and output 'response' field.
    {
        "name": "human_mouth_tool",
        "description": "人間が口を使って指定された言葉を発話します。",
        "input_schema": {
            "type": "object",
            "properties": {
                "utterance": {"type": "string", "description": "発話する内容"}
            },
            "required": ["utterance"]
        },
        "output_schema": {
            "type": "object",
            "properties": {
                "response": {"type": "string", "description": "発話に対する応答"}
            },
            "required": ["response"]
        }
    },
  • The @mcp.tool() decorator registers the human_mouth_tool with the FastMCP server.
    @mcp.tool()
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 states the tool causes speech, implying a behavioral effect, but doesn't disclose any traits like whether it requires human availability, has rate limits, affects other tools, or what happens if the utterance is invalid. For a tool with no annotations, this is a significant gap in behavioral context.

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, efficient sentence in Japanese that directly states the tool's function. It's front-loaded with the core purpose and has no unnecessary words, making it appropriately concise and well-structured.

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?

Given the tool's complexity (a human action tool with no annotations, 1 parameter at 0% schema coverage, and no output schema), the description is incomplete. It lacks details on behavioral traits, parameter usage, output expectations, and differentiation from siblings, leaving gaps for effective tool selection and invocation.

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?

The description adds minimal meaning beyond the input schema. It mentions '指定された言葉' (specified words), which aligns with the 'utterance' parameter, but schema description coverage is 0%, so the schema provides no details. The description doesn't elaborate on parameter format, constraints, or examples, offering only basic semantic context.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: '人間が口を使って指定された言葉を発話します' (A human uses their mouth to speak specified words). It specifies the verb (speak) and resource (words), but doesn't explicitly differentiate from siblings like human_ear_tool (hearing) or human_hand_tool (manual actions). The purpose is clear but lacks sibling distinction.

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 doesn't mention any context, prerequisites, or exclusions, nor does it reference sibling tools. Usage is implied (when speech is needed), but there's no explicit guidance.

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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