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SmartSuiteFoundry

SmartSuite MCP Server

smartsuite_analyze_formulas

Read-only

Analyze formula fields in SmartSuite applications: get summary of all formulas with validity, complexity, and structural metrics, or drill into a specific formula's dependency graph and compute cross-table impact index.

Instructions

Review and analyze formula fields in a SmartSuite application. Without fieldSlug: returns every formula field with its return type, validity (valid:false = broken formula), native complexity score + tier, and structural metrics (function count, nesting depth, reference counts) — sortable by name or score. With fieldSlug: returns full detail for one formula plus its dependency graph (resolved [field].[field] reference chains across linked tables) as both an ASCII tree and a Mermaid flowchart. Set deep:true to also compute the cross-table Impact Index (samples record counts and link fan-out — several extra API calls).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
deepNoWhen fieldSlug is set, also compute the chain-aware Impact Index (record count × link fan-out). Heavier — fires extra record-list calls. Default false.
sortByNoSummary sort order (default name). Ignored when fieldSlug is set.
fieldSlugNoOptional. A specific formula field slug to get full detail + dependency graph. Omit for an application-wide summary of all formula fields.
applicationIdYesThe application ID
Behavior4/5

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

Describes return values (validity, complexity, structural metrics, dependency graph, impact index) and notes extra API calls for deep:true. Annotations already indicate read-only, no contradiction.

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?

Efficiently organized by mode, though packed with details. Could be slightly more concise but well-structured.

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?

No output schema, but description comprehensively details return values for both modes. Covers edge cases (deep:true) and format (ASCII tree, Mermaid flowchart).

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% so baseline 3. Adds extra meaning: fieldSlug triggers full detail+dependency graph, sortBy ignored when fieldSlug set, deep:true triggers heavier computation.

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?

Clearly states two modes: summary of all formula fields (without fieldSlug) and detailed analysis of one formula (with fieldSlug). Distinguishes from siblings like smartsuite_validate_formula and smartsuite_create_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 Guidelines4/5

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

Explains when to use each mode and the deep parameter. Lacks explicit 'when not to use' but context is sufficient.

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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