import { MCPToolSchema } from '@objectstack/spec/ai';

export const SearchAccountsTool = MCPToolSchema.parse({
  name: 'search_accounts',
  description: 'Search CRM accounts by name, industry, or revenue range',
  inputSchema: {
    type: 'object',
    properties: {
      query: { type: 'string', description: 'Search term for account name' },
      industry: { type: 'string', description: 'Filter by industry vertical' },
      minRevenue: { type: 'number', description: 'Minimum annual revenue threshold' },
    },
    required: ['query']
  }
});

packages/crm/src/
├── crm_mcp_tools.mcp.ts        # Tool schemas (what the AI sees)
├── actions/
│   ├── ai_smart_briefing.action.ts  # Tool handler (what runs)
│   └── deal_copilot.action.ts

// In the action handler — always use ObjectQL, never raw SQL
const accounts = await broker.find('account', {
  filters: [
    ['name', 'contains', query],
    ['industry', '=', industry]
  ],
  fields: ['name', 'industry', 'annual_revenue', 'owner'],
  limit: 20
});

import { MCPResourceSchema } from '@objectstack/spec/ai';

export const PipelineSummaryResource = MCPResourceSchema.parse({
  uri: 'hotcrm://crm/pipeline-summary',
  name: 'Pipeline Summary',
  description: 'Current sales pipeline with stage distribution and velocity metrics',
  mimeType: 'application/json'
});

hotcrm://{cloud}/{resource-name}

import { MCPPromptSchema } from '@objectstack/spec/ai';

export const DealAnalysisPrompt = MCPPromptSchema.parse({
  name: 'deal_analysis',
  description: 'Analyze deal health with risk assessment and close probability',
  arguments: [
    {
      name: 'opportunity_id',
      description: 'The opportunity record to analyze',
      required: true
    }
  ]
});

import { AIOrchestrationSchema } from '@objectstack/spec/ai';

export const SalesOrchestration = AIOrchestrationSchema.parse({
  name: 'sales_deal_pipeline',
  label: 'Sales Deal Intelligence Pipeline',
  description: 'Multi-step AI analysis triggered when an opportunity changes stage',

  trigger: {
    type: 'record_change',
    object: 'opportunity',
    field: 'stage'
  },

  steps: [
    {
      id: 'classify_risk',
      type: 'ai_task',
      model: 'gpt-4o',
      prompt: 'Classify this deal risk as low, medium, or high based on: {{deal_summary}}',
      outputVariable: 'risk_level'
    },
    {
      id: 'summarize_deal',
      type: 'ai_task',
      model: 'gpt-4o',
      prompt: 'Generate a 3-sentence executive summary for: {{opportunity.name}}',
      outputVariable: 'deal_summary_text'
    },
    {
      id: 'recommend_action',
      type: 'ai_task',
      model: 'gpt-4o',
      prompt: 'Based on risk={{risk_level}}, recommend the single best next action',
      outputVariable: 'recommended_action'
    }
  ],

  postActions: [
    {
      type: 'fieldUpdate',
      object: 'opportunity',
      field: 'risk_level',
      value: '{{classify_risk.output}}'
    },
    {
      type: 'emailAlert',
      condition: "risk_level = 'high'",
      template: 'high_risk_deal_alert',
      recipients: ['${opportunity.owner.email}', '${opportunity.owner.manager.email}']
    }
  ],

  execution: {
    mode: 'sequential',
    timeoutSeconds: 120
  }
});

import { PredictiveModelSchema } from '@objectstack/spec/ai';

export const LeadScoringModel = PredictiveModelSchema.parse({
  name: 'lead_scoring',
  label: 'Lead Conversion Predictor',
  description: 'Gradient-boosting classifier predicting lead-to-opportunity conversion',
  object: 'lead',
  target: {
    field: 'is_converted',
    type: 'binary_classification'
  },
  features: [
    { field: 'industry', type: 'categorical' },
    { field: 'company_size', type: 'numerical' },
    { field: 'lead_source', type: 'categorical' },
    { field: 'engagement_score', type: 'numerical' },
    { field: 'email_opens', type: 'numerical' },
    { field: 'website_visits', type: 'numerical' },
  ],
  training: {
    algorithm: 'gradient_boosting',
    splitRatio: { train: 0.7, validation: 0.15, test: 0.15 },
    crossValidation: { folds: 5 },
    minRecords: 5000
  }
});

┌─────────────┐     ┌──────────────┐     ┌─────────────┐
│  Resources   │────▶│  AI Agent    │────▶│   Tools     │
│ (read data)  │     │ (reasoning)  │     │ (take action)│
└─────────────┘     └──────┬───────┘     └─────────────┘
                           │
                    ┌──────▼───────┐
                    │   Prompts    │
                    │ (templates)  │
                    └──────────────┘

packages/crm/src/
├── account.object.ts              # Data model
├── crm_mcp_tools.mcp.ts          # MCP tools (search, update, create)
├── crm_mcp_resources.mcp.ts      # MCP resources (pipeline, forecast)
├── crm_prompts.mcp.ts            # MCP prompts (deal analysis, next action)
├── actions/
│   ├── ai_smart_briefing.action.ts    # Tool handler
│   └── deal_copilot.action.ts         # Tool handler

packages/ai/src/
├── sales_orchestration.orchestration.ts  # Multi-step pipeline
├── lead_scoring.predictive.ts            # ML model definition
├── churn_prediction.predictive.ts        # ML model definition
└── deal_forecast.predictive.ts           # ML model definition