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create_column

Add a typed column to a board, with validation rules, required flags, and closed-choice options, so data matches the expected format from the start.

Instructions

Add a typed column to a board. Valid types: text, rich_text, number, status, date, datetime, duration, people, checkbox, dropdown, label, priority, link, email, phone, relation, lookup, rollup, formula, rating, currency, file. Choose by meaning — date for dates, phone for phones, number/currency for amounts, dropdown/status (with settings.options as an array of labels) for closed choices; text is for free text only. An obvious name/type mismatch is rejected with the suggested type; pass force:true to override. Rules go in settings.validation: { unique, min, max, minLength, maxLength, pattern, patternMessage } — enforced on every write (UI, MCP, App API). Closed choices (dropdown/status) reject values outside settings.options unless settings.allowCustom is true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesHuman-readable name
typeYesColumn type: text, rich_text, number, status, date, datetime, duration, people, checkbox, dropdown, label, priority, link, email, phone, relation, lookup, rollup, rating, currency, file
forceNoCreate the column even when the name suggests a different type
boardIdYesBoard id (from list_boards / create_board)
settingsNoType-specific settings. For dropdown/status/priority: options, either as labels ["A","B"] or as full objects [{value,label,color}] — labels are expanded server-side, and colors are assigned if you do not supply them.
projectIdYesProject id (from list_projects / create_project)
isRequiredNoRequire a non-blank value on every App API create

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv0.13.0
    • addedInput schema / properties / boardId / description
      Added value: +"Board id (from list_boards / create_board)"
    • addedInput schema / properties / isRequired / description
      Added value: +"Require a non-blank value on every App API create"
    • addedInput schema / properties / name / description
      Added value: +"Human-readable name"
    • addedInput schema / properties / projectId / description
      Added value: +"Project id (from list_projects / create_project)"
    • addedInput schema / properties / type / description
      Added value: +"Column type: text, rich_text, number, status, date, datetime, duration, people, checkbox, dropdown, label, priority, link, email, phone, relation, lookup, rollup, rating, currency, file"
  2. First observedv0.7.0

TDQS

A4.7/5.0
Behavior5/5

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

The description discloses important behaviors: obvious name/type mismatches are rejected with a suggested type, force overrides this, validation rules are enforced on every write, and closed-choice types reject values outside options unless allowCustom is true. This goes well beyond the minimal annotations.

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 dense and front-loaded, but it repeats the full type list already present in the schema's type property. The extra guidance is valuable, but the list could have been shortened without losing meaning.

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?

The description covers the tool's purpose, parameter semantics, validation behavior, and key edge cases. Even without an output schema, the agent has enough context to call the tool correctly and understand the consequences.

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

Parameters5/5

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

The schema already describes every parameter, and the description adds substantial meaning: type selection semantics, settings.options formats, colors being assigned server-side, validation rule shape, and the meaning of force. This gives the agent a clear model of all relevant parameters.

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 states the specific action: adding a typed column to a board. It clearly distinguishes this from sibling tools like update_column, delete_column, and reorder_columns.

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 gives practical guidance on when to use the tool and how to choose column types, including the meaning-based type selection advice and the force:true override. It does not explicitly contrast with update_column or other column tools, but the intended use is clear.

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