Skip to main content
Glama
yokan-board
by yokan-board

reorder_columns

Rearrange column positions within a Yokan Kanban board by specifying the desired order of column IDs.

Instructions

Reorders columns within a board.

Args: board_id (int): The ID of the board containing the columns. column_ids (List[str]): A list of column IDs in the desired new order. auth (AuthContext): The authentication context containing user ID and token.

Returns: int: The ID of the updated board.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
board_idYes
column_idsYes
authYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The reorder_columns tool handler updates the board's columnOrder in the data object and calls the YokanClient to update the board.
    async def reorder_columns(
        board_id: int,
        column_ids: List[str],
        auth: AuthContext,
    ) -> int:
        """Reorders columns within a board.
    
        Args:
            board_id (int): The ID of the board containing the columns.
            column_ids (List[str]): A list of column IDs in the desired new order.
            auth (AuthContext): The authentication context containing user ID and token.
    
        Returns:
            int: The ID of the updated board.
        """
        board = await yokan_client.get_board(board_id=board_id, token=auth.token)
        board.data["columnOrder"] = column_ids
        return await yokan_client.update_board(
            board_id=board_id, name=board.name, data=board.data, token=auth.token
        )
Behavior2/5

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

With no annotations provided, the description carries full burden but only states the basic operation. It doesn't disclose behavioral traits like whether this is a destructive mutation, what permissions are needed, how errors are handled, or what happens to tasks in reordered columns. The description is minimal beyond the core function.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is front-loaded with the core purpose, followed by structured Args and Returns sections. Every sentence earns its place with no wasted words, making it efficient and easy to parse.

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, 0% schema coverage, but an output schema (returns int ID), the description is moderately complete. It covers parameters and return value, but lacks behavioral context like side effects or error conditions, which is a gap for a tool that modifies data.

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%, but the description compensates by explaining all three parameters: board_id identifies the board, column_ids specifies the new order as a list, and auth provides authentication context. It adds meaningful semantics beyond the bare schema types, though it could detail format constraints (e.g., column_ids must match existing columns).

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 ('reorders columns') and resource ('within a board'), distinguishing it from siblings like update_column or move_task. It precisely defines what the tool does without being vague or tautological.

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 update_column or get_columns. The description lacks context about prerequisites, permissions, or scenarios where reordering is appropriate versus other column modifications.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/yokan-board/yokan-board-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server