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yokan-board
by yokan-board

update_column

Modify column names in Yokan Board to organize project workflows and maintain accurate task categorization.

Instructions

Updates the name of a column.

Args: board_id (int): The ID of the board containing the column. column_id (str): The ID of the column to update. name (str): The new name for the column. 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
nameYes
authYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
tasksNo
titleYes
minimizedNo
highlightColorNo

Implementation Reference

  • The tool "update_column" is registered with `@app_instance.tool` and `@error_handler` and implemented by the async function `update_column`, which modifies the title of a column in a Kanban board.
    @app_instance.tool
    @error_handler
    async def update_column(
        board_id: int,
        column_id: str,
        name: str,
        auth: AuthContext,
    ) -> yokan_models.Column:
        """Updates the name of a column.
    
        Args:
            board_id (int): The ID of the board containing the column.
            column_id (str): The ID of the column to update.
            name (str): The new name for the column.
            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["title"] = name
        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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states this is an update operation but doesn't cover critical aspects like required permissions, whether changes are reversible, error conditions (e.g., invalid IDs), or side effects. The description adds minimal context beyond the basic action.

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 and appropriately sized. It front-loads the purpose in the first sentence, followed by clear 'Args' and 'Returns' sections. Every sentence adds value, with no redundant information. Minor improvement could be made by integrating the sections more fluidly.

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 complexity (a mutation with 4 parameters), no annotations, and an output schema (which covers return values), the description is moderately complete. It explains the action and parameters but lacks behavioral details like error handling or permissions. The output schema reduces the need to describe returns, but more context on usage and constraints would enhance completeness.

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

Parameters3/5

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

Schema description coverage is 0%, so the schema provides no parameter documentation. The description includes an 'Args' section that lists and briefly describes all four parameters, adding essential meaning (e.g., 'board_id' is for the containing board, 'name' is the new name). However, it doesn't elaborate on constraints (e.g., name length limits) or the 'AuthContext' structure beyond what's in the schema.

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: 'Updates the name of a column.' It specifies the verb ('Updates') and resource ('name of a column'), making the action explicit. However, it doesn't distinguish this from sibling tools like 'update_column_color' or 'update_board', which would require mentioning it's specifically for renaming columns.

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 prerequisites (e.g., needing board/column IDs), exclusions, or comparisons to siblings like 'update_column_color' for color changes or 'reorder_columns' for position updates. Usage is implied only by the tool name and parameters.

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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