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Jem-HR
by Jem-HR

send_video

Send video messages via WhatsApp Business API to share visual content with optional captions, footers, and reply functionality.

Instructions

Send a video message.

Args: to: Phone number or WhatsApp ID video: Video URL or media ID caption: Optional video caption footer: Optional footer text reply_to_message_id: Message ID to reply to

Returns: Dictionary with success status and message ID

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYes
videoYes
captionNo
footerNo
reply_to_message_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The complete implementation of the send_video tool - includes both the @mcp.tool() registration decorator and the handler function that sends video messages via WhatsApp API
    @mcp.tool()
    async def send_video(
        to: str,
        video: str,
        caption: Optional[str] = None,
        footer: Optional[str] = None,
        *,
        reply_to_message_id: Optional[str] = None,
    ) -> dict:
        """
        Send a video message.
        
        Args:
            to: Phone number or WhatsApp ID
            video: Video URL or media ID
            caption: Optional video caption
            footer: Optional footer text
            reply_to_message_id: Message ID to reply to
        
        Returns:
            Dictionary with success status and message ID
        """
        try:
            result = wa_client.send_video(
                to=to,
                video=video,
                caption=caption,
                footer=footer,
                reply_to_message_id=reply_to_message_id,
            )
            
            logger.info(f"Video sent to {to}")
            message_id = getattr(result, 'id', str(result)) if result else None
            return {"success": True, "message_id": message_id}
        except Exception as e:
            logger.error(f"Failed to send video: {str(e)}")
            return {"success": False, "error": str(e)}
  • Tool registration via @mcp.tool() decorator with function signature defining input parameters and return type
    @mcp.tool()
    async def send_video(
        to: str,
        video: str,
        caption: Optional[str] = None,
        footer: Optional[str] = None,
        *,
        reply_to_message_id: Optional[str] = None,
    ) -> dict:
  • Schema documentation defining the tool's purpose, input parameters, and return structure
    """
    Send a video message.
    
    Args:
        to: Phone number or WhatsApp ID
        video: Video URL or media ID
        caption: Optional video caption
        footer: Optional footer text
        reply_to_message_id: Message ID to reply to
    
    Returns:
        Dictionary with success status and message ID
    """
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 'send' implies a write operation but doesn't cover critical aspects like authentication needs, rate limits, error handling, or whether the video is uploaded or referenced by URL/ID. The return format is mentioned but lacks detail on error cases.

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 well-structured with a brief purpose statement followed by Args and Returns sections. It's front-loaded and efficient, though the Args section could be slightly more concise (e.g., combining optional notes). Every sentence adds value without redundancy.

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 5 parameters with 0% schema coverage and no annotations, the description does a decent job explaining parameters and return values. However, as a mutation tool (sending messages), it lacks details on behavioral traits like auth, errors, or side effects. The output schema exists, so return values are covered, but overall completeness is moderate due to missing operational context.

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?

Schema description coverage is 0%, so the description must compensate. It effectively explains all 5 parameters: 'to' as phone number/WhatsApp ID, 'video' as URL or media ID, and optional fields like caption, footer, and reply_to_message_id. This adds clear meaning beyond the bare schema, though it doesn't specify format details (e.g., URL requirements).

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 verb 'send' and resource 'video message', making the purpose immediately understandable. It distinguishes from siblings like send_audio or send_image by specifying video content, though it doesn't explicitly contrast with send_message (which might handle text).

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?

No guidance is provided on when to use this tool versus alternatives like send_message or send_audio. The description lacks context about prerequisites (e.g., WhatsApp setup), exclusions, or comparisons to sibling tools, leaving the agent to infer usage scenarios.

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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