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vincenthopf

Gemini Web Automation MCP

by vincenthopf

wait

Pause execution for specified seconds to manage timing in web automation tasks, preventing rapid polling and allowing processes to complete.

Instructions

Wait for a specified number of seconds before continuing.

Use this when you need to pause between operations, such as:
- Waiting between status checks to avoid rapid polling
- Giving a web task time to make progress
- Rate limiting your requests
- Waiting for external processes to complete

Args:
    seconds: Number of seconds to wait (1-60)

Returns:
    Dictionary containing:
    - ok: Boolean indicating success
    - waited_seconds: How long the wait lasted
    - message: Confirmation message

Examples:
    - wait(5)  # Wait 5 seconds
    - wait(10)  # Wait 10 seconds

Best Practice:
    Use this instead of immediately polling check_web_task multiple times.
    Recommended wait time between status checks: 3-5 seconds.

Note: Maximum wait time is 60 seconds to prevent timeout issues.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
secondsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • server.py:311-311 (registration)
    Registration of the 'wait' tool using the @mcp.tool() decorator.
    @mcp.tool()
  • The handler function for the 'wait' tool. Validates input (1-60 seconds), sleeps asynchronously using anyio.sleep, logs progress, and returns success status with waited duration.
    async def wait(seconds: int) -> dict[str, Any]:
        """
        Wait for a specified number of seconds before continuing.
    
        Use this when you need to pause between operations, such as:
        - Waiting between status checks to avoid rapid polling
        - Giving a web task time to make progress
        - Rate limiting your requests
        - Waiting for external processes to complete
    
        Args:
            seconds: Number of seconds to wait (1-60)
    
        Returns:
            Dictionary containing:
            - ok: Boolean indicating success
            - waited_seconds: How long the wait lasted
            - message: Confirmation message
    
        Examples:
            - wait(5)  # Wait 5 seconds
            - wait(10)  # Wait 10 seconds
    
        Best Practice:
            Use this instead of immediately polling check_web_task multiple times.
            Recommended wait time between status checks: 3-5 seconds.
    
        Note: Maximum wait time is 60 seconds to prevent timeout issues.
        """
        # Validate input
        if seconds < 1:
            return {
                "ok": False,
                "error": "Wait time must be at least 1 second"
            }
    
        if seconds > 60:
            return {
                "ok": False,
                "error": "Wait time cannot exceed 60 seconds. For longer waits, call this tool multiple times."
            }
    
        logger.info(f"Waiting for {seconds} seconds...")
    
        # Use anyio sleep for async compatibility
        import time
        await anyio.sleep(seconds)
    
        logger.info(f"Wait completed: {seconds} seconds")
    
        return {
            "ok": True,
            "waited_seconds": seconds,
            "message": f"Successfully waited {seconds} seconds"
        }
  • Input schema definition in the docstring: seconds (int, 1-60). Output schema: dict with ok, waited_seconds, message (and error on failure).
    seconds: Number of seconds to wait (1-60)
Behavior5/5

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 thoroughly explains the tool's behavior, including the wait duration range (1-60 seconds), the return structure (dictionary with ok, waited_seconds, message), and practical constraints like timeout prevention. This goes beyond what the input schema alone provides.

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 well-structured and front-loaded, starting with the core purpose, followed by usage guidelines, parameter details, returns, examples, and best practices. Every section adds value without redundancy, and the length is appropriate for a tool with behavioral complexity and no annotations.

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

Completeness5/5

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

Given the tool's behavioral complexity (timing, constraints), lack of annotations, and the presence of an output schema, the description is complete. It covers purpose, usage, parameters, returns (though output schema exists, it adds clarification), examples, and best practices, leaving no gaps for an AI agent to understand and invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema has 0% description coverage, so the description must fully compensate. It adds significant meaning by explaining the 'seconds' parameter as 'Number of seconds to wait (1-60)', providing the semantic context, valid range, and examples (wait(5), wait(10)), which are not present in the schema's minimal title and type definition.

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 clearly states the tool's purpose with a specific verb ('wait') and resource ('specified number of seconds'), distinguishing it from sibling tools like check_web_task or start_web_task. It explicitly defines the action of pausing execution, which is distinct from the web-related operations of its siblings.

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

Usage Guidelines5/5

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

The description provides explicit guidance on when to use this tool, listing specific scenarios (e.g., avoiding rapid polling, rate limiting, waiting for external processes) and naming an alternative (check_web_task) in the 'Best Practice' section. It also includes when-not-to-use guidance by specifying a maximum wait time to prevent timeouts.

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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