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upamune
by upamune

human_ear_tool

Listen to environmental sounds, identify specific audio sources, or transcribe conversations using human hearing capabilities.

Instructions

人間が耳を使って音を聞き、状況を説明します。

例:
- 周囲の環境音の確認
- 特定の音源の識別
- 会話の聞き取り

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
instructionYes

Implementation Reference

  • The complete handler implementation for 'human_ear_tool', including @mcp.tool() registration decorator, input schema via type annotations and docstring, and core logic: generates UUID task ID, formats instruction, persists to database via db_utils.add_task, awaits completion via wait_for_task_completion helper, logs progress, and returns observation in 'sound' key.
    @mcp.tool()
    async def human_ear_tool(instruction: str, ctx: Context) -> Dict[str, str]:
        """人間が耳を使って音を聞き、状況を説明します。
    
        例:
        - 周囲の環境音の確認
        - 特定の音源の識別
        - 会話の聞き取り
        """
        task_id = str(uuid.uuid4())
        formatted_instruction = f"👂 耳を使って聴取: {instruction}"
    
        # タスクをデータベースに追加
        db_utils.add_task(task_id, formatted_instruction)
    
        # 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 {"sound": result}
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 mentions the action ('聞き' - listen) and outcome ('状況を説明します' - describe situations), but lacks critical behavioral details: it doesn't specify what kind of human is involved (e.g., their hearing capabilities, language skills), doesn't mention limitations (e.g., hearing range, background noise interference), and doesn't describe the format or reliability of the description output. For a tool with no annotation coverage, this leaves significant gaps in understanding how it behaves.

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 appropriately sized with a clear opening statement followed by three bullet-point examples. Each sentence earns its place by clarifying the tool's purpose and potential use cases. However, it could be more front-loaded with a more comprehensive purpose statement that includes differentiation from siblings.

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 complexity of a human sensory tool with no annotations, no output schema, and 1 undocumented parameter, the description is incomplete. It doesn't address key contextual elements: what constitutes a valid 'instruction', what the output looks like (despite no output schema), reliability factors, or limitations compared to sibling tools. The examples provide some context but don't compensate for the missing structural information.

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 1 parameter with 0% description coverage, and the tool description provides no information about the 'instruction' parameter. The examples hint at possible instructions ('周囲の環境音の確認' - check surrounding environmental sounds), but don't explain parameter syntax, format, or constraints. With low schema coverage, the description fails to compensate by adding meaningful parameter semantics.

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 what the tool does: '人間が耳を使って音を聞き、状況を説明します' (A human uses ears to listen to sounds and describe situations). It provides a specific verb ('聞き' - listen) and resource ('音' - sounds), though it doesn't explicitly differentiate from sibling tools like human_eye_tool or human_mouth_tool. The examples help clarify the scope but don't establish clear boundaries with siblings.

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

Usage Guidelines3/5

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

The description provides implied usage through examples ('周囲の環境音の確認', '特定の音源の識別', '会話の聞き取り'), suggesting contexts where this tool is appropriate. However, it doesn't explicitly state when to use this tool versus alternatives like human_eye_tool for visual tasks or human_mouth_tool for speaking. No explicit exclusions or prerequisites are mentioned.

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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