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monday MCP Server

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Remove AI from Column

remove_ai_from_column
DestructiveIdempotent

Disable AI automation on a monday.com board column by removing AI recipes and extensions while preserving the column.

Instructions

Remove AI from a column on a monday.com board. Use this tool when the user wants to disable AI on a column, turn off AI automation, stop AI from running on a column, or delete the AI behavior from a column. This deletes all AI automation recipes and the app feature extension associated with the column. The column itself is not deleted — only its AI behavior is removed.

Use get_board_schema to find column IDs before calling this tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
board_idYesThe ID of the board containing the column
column_idYesThe ID of the column to remove AI from
Behavior5/5

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

The description goes beyond annotations by detailing exactly what is deleted ('all AI automation recipes and the app feature extension') and confirming the column itself is not deleted. This provides crucial context for the destructive action, complementing the destructiveHint and idempotentHint.

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 concise with five sentences, each adding value. It front-loads the purpose, then provides synonyms and behavioral details, and ends with a prerequisite. No unnecessary words.

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

Completeness5/5

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

Given the tool's simplicity (2 params, no output schema) and the presence of annotations, the description covers all essential aspects: purpose, usage, behavioral effects, and parameter guidance. It is complete and leaves no gaps.

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 coverage is 100% with clear parameter descriptions. The tool description does not add new meaning beyond the schema, only indirectly hints at how to obtain column_id. Baseline score of 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 action ('Remove AI from a column') with specific verb and resource. It also provides synonyms like 'disable AI' and 'turn off AI automation', and distinguishes from sibling tools like 'configure_ai_column' and 'delete_column'.

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 explicitly says when to use the tool ('when the user wants to disable AI...') and gives a prerequisite ('Use get_board_schema to find column IDs'). However, it does not mention when not to use it or list alternative tools, missing full guidelines.

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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