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Jem-HR
by Jem-HR

remove_reaction

Remove a reaction from a WhatsApp message by specifying the recipient, message ID, and optional sender to manage message interactions.

Instructions

Remove a reaction from a message.

Args: to: Phone number or WhatsApp ID message_id: ID of message to remove reaction from sender: Optional sender phone ID

Returns: Dictionary with success status

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYes
message_idYes
senderNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Implementation Reference

  • The remove_reaction tool handler - an async function decorated with @mcp.tool() that removes reactions from WhatsApp messages. It takes parameters 'to', 'message_id', and optional 'sender', calls wa_client.remove_reaction(), logs the action, and returns a success status dictionary.
    async def remove_reaction(
        to: str,
        message_id: str,
        *,
        sender: Optional[str] = None,
    ) -> dict:
        """
        Remove a reaction from a message.
        
        Args:
            to: Phone number or WhatsApp ID
            message_id: ID of message to remove reaction from
            sender: Optional sender phone ID
        
        Returns:
            Dictionary with success status
        """
        try:
            result = wa_client.remove_reaction(
                to=to,
                message_id=message_id,
                sender=sender,
            )
            
            logger.info(f"Reaction removed from message {message_id}")
            result_data = str(result) if result else None
            return {"success": True, "result": result_data}
        except Exception as e:
            logger.error(f"Failed to remove reaction: {str(e)}")
            return {"success": False, "error": str(e)}
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states the action is 'Remove' (implying mutation) and mentions a return dictionary with success status, but lacks critical details: permission requirements, whether the operation is reversible, error conditions, or rate limits. For a mutation tool with zero annotation coverage, this is insufficient.

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 efficiently structured with a clear purpose statement followed by parameter explanations and return value note. Every sentence adds value, though the formatting with 'Args:' and 'Returns:' sections could be more integrated. It's appropriately sized for a tool with three parameters.

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 a mutation tool with no annotations, 3 parameters (0% schema coverage), and an output schema present, the description is minimally adequate. It explains parameters semantically and mentions the return structure, but lacks behavioral context about permissions, side effects, or error handling. The output schema existence reduces the need to detail return values, but more operational guidance would improve completeness.

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 provides clear semantic explanations for all three parameters: 'to' as 'Phone number or WhatsApp ID', 'message_id' as 'ID of message to remove reaction from', and 'sender' as 'Optional sender phone ID'. This adds meaningful context beyond the bare schema, though it doesn't specify format requirements or constraints.

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 specific action ('Remove a reaction') and target resource ('from a message'), distinguishing it from sibling tools like 'send_reaction' which adds reactions. It uses precise language that immediately communicates the tool's function without ambiguity.

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 about when to use this tool versus alternatives. While the purpose distinguishes it from 'send_reaction', there's no explicit mention of prerequisites, constraints, or typical use cases. The description assumes context but doesn't provide usage instructions.

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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