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yokan-board
by yokan-board

update_column_color

Change the highlight color of a column on a Yokan Kanban board to visually organize and categorize workflow stages.

Instructions

Updates the highlight color of a specified column.

Args: board_id (int): The ID of the board containing the column. column_id (str): The ID of the column to update. color (str): The new highlight color for the column (e.g., "red", "#FF0000"). auth (AuthContext): The authentication context containing user ID and token.

Returns: yokan_models.Column: The updated column object.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
board_idYes
column_idYes
colorYes
authYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
tasksNo
titleYes
minimizedNo
highlightColorNo

Implementation Reference

  • The handler function 'update_column_color' that implements the MCP tool logic for updating a column's color. It is registered using the '@app_instance.tool' decorator and wrapped with '@error_handler'.
    @app_instance.tool
    @error_handler
    async def update_column_color(
        board_id: int,
        column_id: str,
        color: str,
        auth: AuthContext,
    ) -> yokan_models.Column:
        """Updates the highlight color of a specified column.
    
        Args:
            board_id (int): The ID of the board containing the column.
            column_id (str): The ID of the column to update.
            color (str): The new highlight color for the column (e.g., "red", "#FF0000").
            auth (AuthContext): The authentication context containing user ID and token.
    
        Returns:
            yokan_models.Column: The updated column object.
        """
        board = await yokan_client.get_board(board_id=board_id, token=auth.token)
        if "columns" not in board.data or column_id not in board.data["columns"]:
            raise McpError(error=ErrorData(code=NOT_FOUND, message="Column not found"))
    
        column = board.data["columns"][column_id]
        column["highlightColor"] = color
    
        await yokan_client.update_board(
            board_id=board_id, name=board.name, data=board.data, token=auth.token
        )
        return yokan_models.Column(**column)
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. While it states this is an update operation (implying mutation), it doesn't disclose critical behavioral traits: required permissions (e.g., board ownership), whether changes are reversible, rate limits, error conditions, or what happens if invalid color values are provided. The description mentions authentication but doesn't explain what permissions the auth context needs.

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 purpose statement followed by Args and Returns sections. The first sentence clearly states the tool's purpose. The parameter explanations are efficient, though the auth parameter description could be more specific about required permissions. No wasted sentences, though the structure is slightly verbose for a simple tool.

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

Completeness4/5

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

Given this is a mutation tool with no annotations but with output schema (yokan_models.Column), the description provides adequate context. It explains all parameters meaningfully and specifies the return type. However, for a write operation, it should ideally mention permission requirements or side effects. The presence of output schema reduces the need to describe return values in detail.

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 successfully adds meaning for all 4 parameters: board_id ('The ID of the board containing the column'), column_id ('The ID of the column to update'), color ('The new highlight color for the column' with examples), and auth ('The authentication context containing user ID and token'). This provides clear semantic context beyond the bare schema types.

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 ('Updates the highlight color') and target resource ('of a specified column'), distinguishing it from sibling tools like update_column (which likely updates other column properties) and update_board/update_task (which target different resources). The verb+resource combination is precise and unambiguous.

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

Usage Guidelines3/5

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

The description implies usage when needing to change a column's color, but provides no explicit guidance on when to use this versus alternatives like update_column (which might handle other column properties) or when not to use it (e.g., if only read access is available). No prerequisites or exclusions are mentioned, leaving usage context partially implied rather than explicitly defined.

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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