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aleksakarac

Obsidian MCP Extended

by aleksakarac

move_kanban_card_tool

Move a Kanban card between columns by exact text match. Preserves metadata and formatting for workflow updates.

Instructions

Move a card between columns on a Kanban board (filesystem-native, offline).

Finds a card by matching its text, removes it from the source column, and adds it to the destination column. Preserves all metadata, subtasks, and formatting.

When to use:

  • Moving tasks through workflow stages

  • Dragging cards between columns programmatically

  • Batch workflow updates

  • Automated status changes

Performance:

  • < 500ms for boards with 1,000 cards

Returns: Success status, source/destination columns, and card details

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYesPath to Kanban board file (relative to vault)
card_textYesText of the card to move (must match exactly)
from_columnYesSource column name
to_columnYesDestination column name
positionNoWhere to insert in destination columnend
vault_pathNoPath to vault (optional, uses OBSIDIAN_VAULT_PATH env if not provided)
ctxNo
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses that the tool preserves metadata, subtasks, formatting, and mentions performance (<500ms for 1k cards) and return value structure. However, it does not discuss error handling (e.g., card not found) or reversibility, but the core behavioral traits are adequately covered.

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 well-structured with clear sections: main action, when to use, performance, returns. It is concise, front-loaded with the core task, and contains no redundant sentences. Every element adds value.

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?

For a tool with 7 parameters (4 required) and no output schema, the description covers purpose, usage, behavioral traits, performance, and return values. It lacks details on error cases but is otherwise thorough. The presence of sibling tools and context signals adds to 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 86%, so the schema already documents parameters well. The description adds general context (e.g., 'Finds a card by matching its text') but does not provide additional semantic meaning beyond what the schema offers. Baseline 3 is appropriate.

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 tool's purpose: 'Move a card between columns on a Kanban board' and elaborates on the process. It differentiates from sibling tools like add_kanban_card_tool and toggle_kanban_card_tool through its specific verbs and context.

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

Usage Guidelines4/5

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

The description provides a 'When to use' list with concrete scenarios (e.g., moving tasks through workflow stages, batch updates). While it doesn't explicitly state when not to use or list alternatives, the context signals show many sibling tools, and the guidelines are clear enough for typical use cases.

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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