Rule: Domo App Platform AI (Toolkit-First)

This rule is toolkit-first. Use AIClient from @domoinc/toolkit.

Legacy endpoint-first guidance has been archived to archive/legacy-rules/domo-ai-endpoints.md.

Canonical Client

yarn add @domoinc/toolkit

import { AIClient } from '@domoinc/toolkit';

Critical: AIClient methods are static

Do not instantiate AIClient for these methods.

Wrong:

const ai = new AIClient();
await ai.text_to_sql('...');

Correct:

await AIClient.text_to_sql('...');

Text Generation

const response = await AIClient.generate_text(
  'Explain this sales trend in simple terms',
  { template: 'You are a business analyst. ${input}' },
  { tone: 'professional' },
  undefined,
  { temperature: 0.7 }
);

const body = response.data || response.body || response;
const text = body.output || body.choices?.[0]?.output;

Additional AI Methods

text_to_sql schema argument must be an array

Wrong:

await AIClient.text_to_sql('Show top vendors by spend', {
  dataSourceName: 'vendorPayments',
  columns: [{ name: 'amount', type: 'number' }]
});

Correct:

await AIClient.text_to_sql('Show top vendors by spend', [
  {
    dataSourceName: 'vendorPayments',
    description: 'Vendor payment invoices',
    columns: [
      { name: 'vendor', type: 'string' },
      { name: 'amount', type: 'number' },
      { name: 'date', type: 'date' }
    ]
  }
]);

Signature reference

(Approximate; check installed toolkit typings for exact current signature.)

AIClient.text_to_sql(
  input: string,
  dataSourceSchemas?: DataSourceSchema[], // array
  promptTemplate?: any,
  parameters?: Record<string, string>,
  model?: string,
  modelConfiguration?: Record<string, Object>
): Promise<Response<TextAIResponse>>;

Why array: this supports multi-table SQL generation (including join-aware SQL) when multiple schemas are provided.

text_to_sql usage note

text_to_sql is great for ad-hoc SQL, but /sql/v1 does not automatically apply dashboard/page filters. If filter-awareness is required in embedded cards, use Query API (/data/v1 via @domoinc/query) for execution.

const sqlResult = await AIClient.text_to_sql('Show total sales by region', [
  {
    dataSourceName: 'Sales',
    description: 'Sales transactions',
    columns: [{ name: 'region', type: 'string' }, { name: 'amount', type: 'number' }]
  }
]);

const beastModeResult = await AIClient.text_to_beastmode(
  'Calculate year over year growth percentage',
  { dataSourceName: 'Revenue', columns: [{ name: 'revenue', type: 'number' }, { name: 'date', type: 'date' }] }
);

Response Handling Rule

AIClient responses are not always shaped like other toolkit clients:

• often uses response.data
• may include both output and choices

Use defensive parsing plus a strict string guard:

const body = response?.data ?? response?.body ?? response;
const outputCandidate = body?.output ?? body?.choices?.[0]?.output;
const output = typeof outputCandidate === 'string' ? outputCandidate.trim() : '';

if (!output) throw new Error('AI returned no usable output');

Canonical Rules References

• Toolkit AI methods and caveats: .cursor/rules/04-toolkit.mdc
• Naming/response gotchas: .cursor/rules/09-gotchas.mdc

Checklist

• AIClient methods use snake_case (generate_text, text_to_sql, etc.)
• AIClient methods are called statically (for example AIClient.text_to_sql(...), not instance methods)
• AIClient.text_to_sql second argument is DataSourceSchema[] (array), not a single object
• Responses parsed from data/body fallback
• Output extraction includes string guard and empty-output handling
• Error handling and loading state in UI