Skip to main content
Glama
upamune
by upamune

human_weather_tool

Request human assistance to check and report current weather conditions at a specific location through interactive collaboration.

Instructions

人間が現在地の天気を確認して報告します。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The core handler function decorated with @mcp.tool(). It creates a database task with a fixed instruction to check current weather, polls asynchronously for human-provided result using wait_for_task_completion, logs progress, and returns the weather information.
    @mcp.tool()
    async def human_weather_tool(ctx: Context) -> Dict[str, str]:
        """人間が現在地の天気を確認して報告します。"""
        task_id = str(uuid.uuid4())
        instruction = f"🌤️ 現在地の天気を確認してください"
    
        # タスクをデータベースに追加
        db_utils.add_task(task_id, 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 {"weather": result}
  • JSON schema definition for human_weather_tool, specifying no input parameters and output as a 'weather' string.
    {
        "name": "human_weather_tool",
        "description": "人間が現在地の天気を確認して報告します。",
        "input_schema": {
            "type": "object",
            "properties": {},
            "required": []
        },
        "output_schema": {
            "type": "object",
            "properties": {
                "weather": {"type": "string", "description": "現在地の天気情報"}
            },
            "required": ["weather"]
        }
    }
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It implies a human-in-the-loop process (checking and reporting), but doesn't specify critical traits like latency (how long it takes for the human to respond), reliability, or any constraints (e.g., availability during certain hours). For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 without any wasted words. It's front-loaded with the core purpose, making it easy for an agent to parse quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (human-involved weather checking) and lack of annotations or output schema, the description is minimally adequate. It covers the basic purpose but misses details on behavioral traits, output format, or usage context. With no structured fields to rely on, the description should do more to compensate, but it only meets the minimum viable threshold.

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 0 parameters with 100% coverage, so no parameters need documentation. The description doesn't add parameter details, which is appropriate here. A baseline of 4 is applied as it effectively handles the lack of parameters without introducing confusion.

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: '人間が現在地の天気を確認して報告します' (A human checks and reports the weather at the current location). It specifies the verb (check and report), resource (weather), and scope (current location). However, it doesn't explicitly differentiate from sibling tools like 'human_eye_tool' or 'human_nose_tool', which might have overlapping sensory functions, so it doesn't reach the highest score.

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 prerequisites, exclusions, or context for usage compared to sibling tools. The agent must infer usage based on the purpose alone, which is insufficient for optimal tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/upamune/human-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server