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MCP Reminder

by sheacoding

add_alarm

Set alarms with natural language time input like 'tomorrow at 10am' or specific dates to receive notifications for important events through the MCP Reminder server.

Instructions

添加闹钟

Args: time: 闹钟时间,支持自然语言如"下午2点30分"、"明天上午10点"或精确时间"2025-09-02 14:30" description: 闹钟描述(可选)

Returns: 包含闹钟ID和确认信息的字典

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
timeYes
descriptionNo

Implementation Reference

  • The add_alarm tool implementation in src/mcp_reminder/server.py. It uses mcp.tool() to register the tool and handles the input validation, alarm creation, and storage.
    @mcp.tool()
    def add_alarm(time: str, description: str = "") -> dict:
        """
        添加闹钟
    
        Args:
            time: 闹钟时间,支持自然语言如"下午2点30分"、"明天上午10点"或精确时间"2025-09-02 14:30"
            description: 闹钟描述(可选)
    
        Returns:
            包含闹钟ID和确认信息的字典
        """
        # 解析时间
        parsed_time = parse_time(time)
        if not parsed_time:
            return {
                "success": False,
                "error": f"无法解析时间: {time},请使用如'下午2点30分'或'2025-09-02 14:30'格式"
            }
    
        # 创建闹钟
        alarm = Alarm(
            time=parsed_time,
            description=description
        )
    
        # 保存闹钟
        storage.add_alarm(alarm)
    
        logger.info(f"添加闹钟: {alarm.time}, 描述: {alarm.description}")
    
        return {
            "success": True,
            "alarm_id": alarm.id,
            "time": alarm.time,
            "description": alarm.description,
            "message": f"闹钟已设置在 {alarm.time}" + (f": {description}" if description else "")
        }
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that the tool adds an alarm and returns a dictionary with ID and confirmation, but lacks critical details: whether this requires specific permissions, if alarms are persistent across sessions, what happens on duplicate alarms, rate limits, or error conditions. For a mutation tool with zero annotation coverage, this is a significant gap.

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 and front-loaded, starting with the purpose, followed by clear sections for Args and Returns. Each sentence adds value: the purpose statement, parameter explanations, and return format. There's no redundant information, though the structure could be slightly more polished (e.g., using bullet points).

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 moderate complexity (2 parameters, no output schema, no annotations), the description is partially complete. It covers the basic purpose and parameters well but lacks behavioral context (e.g., permissions, persistence) and doesn't fully explain the return value beyond '字典' (dictionary). For a mutation tool, this leaves gaps that could hinder agent understanding.

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 description adds substantial meaning beyond the input schema, which has 0% description coverage. It explains that 'time' supports natural language (e.g., '下午2点30分') or precise formats, and that 'description' is optional. This compensates well for the schema's lack of details, though it doesn't specify exact formats or validation rules for 'time'.

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 as '添加闹钟' (add alarm) in Chinese, which translates to a specific verb+resource combination. It distinguishes itself from siblings like 'dismiss_alarm' or 'get_pending_alarms' by focusing on creation rather than management or querying. However, it doesn't explicitly differentiate from 'add_todo' in terms of use case, which slightly limits clarity.

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 when to choose 'add_alarm' over 'add_todo' for time-based reminders, or how it relates to 'check_all_reminders' or 'get_pending_alarms'. There's no context about prerequisites, such as system availability or user permissions, leaving usage entirely implicit.

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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