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smartsuite_create_field

Create fields of any type in a SmartSuite table, including rollup and lookup fields, with optional AI prompts and configurable parameters. Preview changes before applying.

Instructions

Create a field of any type in an application (including rollup and lookup fields — not just formulas). Requires readwrite/admin mode AND SMARTSUITE_ENABLE_SCHEMA_WRITE=true. You supply fieldType + label and an OPTIONAL sparse params object; SmartSuite fills type defaults, so most fields need no params. Provide params only where they matter, e.g.: singleselectfield/multipleselectfield/statusfield → {choices:[{label, value_help_text?, weight?}]} where value_help_text is the option DESCRIPTION shown in the dropdown and weight is its NUMERIC value (used by formulas/rollups); e.g. {choices:[{label:"High", value_help_text:"Ship this week", weight:3}]}. Choice colors and order are auto-assigned if omitted so the dropdown renders correctly (status choices take no weight/description); linkedrecordfield → {linked_application:"", entries_allowed:"single"|"multiple"} (backlink auto-created); rollupfield → {linked_field:"", field_selection:"", function:"sum"|"count"|"min"|"max"|"average"|"concatenate"|...}; lookupfield → {linked_field, field_selection}; numberfield → {precision, separator}; currencyfield → {currency:"USD"}; textfield → {max_length}. (For formula fields use smartsuite_create_formula_field.) AI FIELDS: to make a field AI-populated, pass aiPrompt — a plain-text prompt where {{field_slug}} inserts a live reference to another field (e.g. "Summarize {{title}} for {{s096c9e74e}}"). The tool builds the correct rich-text instructions with field-reference pills and enables the AI agent; put the AI model/credential and other ai_agent settings in params.ai_agent if needed. (This is the reliable way to set dynamic AI prompts — do NOT hand-build ai_agent.instructions.) The slug is generated and the field is placed in the record-view layout. Dry-run preview unless confirm:true.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
labelYesField display label.
paramsNoOptional sparse field params; omit to accept type defaults. See the tool description for which params each type needs.
confirmNoMust be true to create (default false = preview).
aiPromptNoOptional: make this an AI-populated field. Plain-text prompt where {{field_slug}} inserts a live reference to another field. The tool builds the rich-text AI instructions (with field pills) and enables the AI agent.
fieldTypeYesSmartSuite field type, e.g. textfield, textareafield, richtextareafield, numberfield, currencyfield, percentfield, datefield, duedatefield, singleselectfield, multipleselectfield, statusfield, yesnofield, linkedrecordfield, userfield, emailfield, phonefield, linkfield, filefield, addressfield, ratingfield, durationfield, timefield, checklistfield, tagsfield, colorpickerfield.
applicationIdYesThe application (table) ID.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changedv1.0.0
    • removedInput schema / properties / afterFieldSlug
      Removed value: -{
-  "description": "Optional: place the new field after this field slug (default: end).",
-  "type": "string"
-}
  2. First observedv0.9.8

TDQS

A4.8/5.0
Behavior5/5

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

Annotations carry only readOnlyHint=false, so the description bears the full behavioral burden and discharges it thoroughly: dry-run preview unless confirm:true, SmartSuite auto-filling defaults, auto-assigned choice colors/order, auto-created backlinks, AI instructions auto-built with field-reference pills plus an explicit 'do NOT hand-build ai_agent.instructions' warning, auto-generated slug, and auto-placement in the record-view layout. No contradiction with 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 long, but for a tool covering 20+ field types plus an AI sub-feature, every block earns its place: purpose and requirements are front-loaded, followed by the sparse-params pattern, type-specific examples, sibling routing, the AI special case, and closing behavioral notes. Dense and logically ordered; only marginally trimable.

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 6-parameter tool with nested objects and no output schema, the description is nearly complete on invocation and behavior, including the non-obvious dry-run default and the env-var gate. The one gap is that it never states what the tool returns on successful creation or what the dry-run preview actually shows, though slug generation is mentioned.

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?

Schema coverage is 100%, and the schema's params field explicitly defers to the description ('See the tool description for which params each type needs'). The description delivers concrete per-type semantics beyond the schema: choices with value_help_text/weight, linked_application/entries_allowed, linked_field/field_selection/function, precision/separator, currency, max_length, and the aiPrompt {{field_slug}} mechanism.

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?

States a specific verb+resource ('Create a field of any type in an application') and immediately distinguishes scope by adding 'including rollup and lookup fields — not just formulas', then routes formula work to smartsuite_create_formula_field. An agent can tell this tool apart from its siblings without opening the schema.

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

Usage Guidelines5/5

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

Explicitly names the alternative ('For formula fields use smartsuite_create_formula_field'), states hard prerequisites (readwrite/admin mode and SMARTSUITE_ENABLE_SCHEMA_WRITE=true), and gives the sparse-params rule ('Provide params only where they matter'). Also clarifies the dry-run vs confirm:true execution path, leaving no ambiguity about when this tool actually creates.

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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