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yokan-board
by yokan-board

get_tasks

Retrieve tasks from a Yokan Board, with optional filtering by column to organize workflow and track progress.

Instructions

Retrieves all tasks for a given board, optionally filtered by column.

Args: board_id (int): The ID of the board to retrieve tasks from. auth (AuthContext): The authentication context containing user ID and token. column_id (Optional[str], optional): The ID of the column to filter tasks by. If None, retrieves tasks from all columns. Defaults to None.

Returns: List[Dict]: A list of dictionaries, where each dictionary represents a task.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
board_idYes
authYes
column_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The handler implementation for the 'get_tasks' tool, which fetches tasks from a Yokan board, optionally filtered by column.
    @app_instance.tool
    @error_handler
    async def get_tasks(
        board_id: int,
        auth: AuthContext,
        column_id: Optional[str] = None,
    ) -> List[Dict]:
        """Retrieves all tasks for a given board, optionally filtered by column.
    
        Args:
            board_id (int): The ID of the board to retrieve tasks from.
            auth (AuthContext): The authentication context containing user ID and token.
            column_id (Optional[str], optional): The ID of the column to filter tasks by. If None, retrieves tasks from all columns. Defaults to None.
    
        Returns:
            List[Dict]: A list of dictionaries, where each dictionary represents a task.
        """
        board = await yokan_client.get_board(board_id=board_id, token=auth.token)
        if "columns" not in board.data:
            return []
    
        if column_id:
            if column_id not in board.data["columns"]:
                raise McpError(error=ErrorData(code=NOT_FOUND, message="Column not found"))
            return board.data["columns"][column_id].get("tasks", [])
    
        all_tasks = []
        for col in board.data["columns"].values():
            all_tasks.extend(col.get("tasks", []))
        return all_tasks
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 this is a retrieval operation but doesn't mention authentication requirements (though auth parameter implies it), rate limits, pagination behavior, or what happens with invalid board_id/column_id values. The description adds minimal behavioral context beyond the basic operation.

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?

Well-structured with purpose statement followed by Args and Returns sections. The description is appropriately sized with no redundant information. Minor improvement could be integrating the optional filtering into the main purpose statement more seamlessly.

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 the tool's moderate complexity (3 parameters, no annotations, but has output schema), the description is reasonably complete. It explains the operation, parameters, and return format. The output schema existence means it doesn't need to detail return values. Could benefit from more behavioral context given the lack of annotations.

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?

With 0% schema description coverage, the description provides excellent parameter semantics. It explains board_id purpose, auth context contents, and column_id's optional filtering behavior with clear default value explanation. The only gap is not explaining AuthContext structure, but the schema covers that.

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 ('Retrieves all tasks'), target resource ('for a given board'), and optional scope ('optionally filtered by column'). It distinguishes this from sibling tools like get_board or get_columns by focusing specifically on tasks.

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 context through the optional column_id parameter, suggesting this tool can be used for both board-wide and column-specific task retrieval. However, it doesn't explicitly state when to use this versus alternatives like get_board (which might include tasks) or create_task for adding tasks.

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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