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SmartSuiteFoundry

SmartSuite MCP Server

smartsuite_update_field

Update a field's label, params, or AI prompt in SmartSuite. Preview changes before applying, with selective merging of params and full replacement of choices for select fields.

Instructions

Update a field's label and/or params (any type). Requires readwrite/admin mode AND SMARTSUITE_ENABLE_SCHEMA_WRITE=true. params is a PATCH — only the keys you pass are changed (shallow-merged onto the existing params); everything else (choices, nested, links) is preserved. Read the field first with smartsuite_describe_field to see current params. Note: choices is replaced wholesale, not merged — to edit select options pass the FULL choices array (each choice may set value_help_text=description and weight=numeric value; colors auto-assigned if omitted). Applies asynchronously. Dry-run preview unless confirm:true. (For help text use smartsuite_set_field_help_text; for formula expressions use smartsuite_update_formula_field.) AI PROMPT: pass aiPrompt (plain text with {{field_slug}} references) to (re)build the field's dynamic AI instructions; it preserves the existing ai_agent model/settings and replaces only the prompt.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesThe field slug to update.
labelNoNew label (optional).
paramsNoOptional params patch (shallow-merged onto existing params). For select fields, omitted choice colors are auto-assigned.
confirmNoMust be true to apply (default false = preview).
aiPromptNoOptional: rebuild the field's AI prompt. Plain-text with {{field_slug}} references; preserves existing ai_agent model/settings.
applicationIdYesThe application (table) ID.
Behavior5/5

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

Discloses PATCH semantics, shallow merge, wholesale replacement of choices, async application, dry-run mode, and aiPrompt behavior. Annotations only indicate it's not read-only; description adds extensive detail.

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?

Though lengthy, every sentence carries essential information for a complex operation. Front-loaded with core purpose, but could be slightly more terse without losing clarity.

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?

Covers all aspects: prerequisites, parameter behaviors, usage patterns, alternatives, and async/dry-run details. Adequate given no output schema and moderate complexity.

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 coverage is 100% but description adds meaningful explanation of params (shallow-merged, choices replaced wholesale) and aiPrompt (preserves existing settings), going beyond basic schema descriptions.

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 explicitly states it updates a field's label and/or params, distinguishing it from related tools like smartsuite_set_field_help_text and smartsuite_update_formula_field.

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?

Provides explicit prerequisites (readwrite/admin mode, SMARTSUITE_ENABLE_SCHEMA_WRITE=true), recommends reading the field first, and lists alternatives for help text and formula updates.

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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