Kalodata Monitor

Kalodata Monitor Skill

Scheduled research automation with intelligent new product detection and Slack alerts.

Overview

Enables scheduled research automation with intelligent new product detection and Slack alerts. Runs on configurable schedules (hourly/daily/weekly), detects new products by comparing with previous runs, alerts on revenue threshold crossings, and sends notifications via Slack webhook.

When to Use

Trigger phrases:

• "kalodata monitor"

• "User wants continuous monitoring of TikTok Shop product categories"

• "User needs automatic detection of NEW products entering the market"

• "User wants alerts when products cross revenue thresholds"

• User wants continuous monitoring of TikTok Shop product categories

• User needs automatic detection of NEW products entering the market

• User wants alerts when products cross revenue thresholds

• User prefers Slack notifications for urgent product discoveries

• User needs scheduled research runs without manual intervention

The Process

1. Configure monitoring profile – Set up profile with category, goal, schedule, and Slack webhook
2. Set alert conditions – Define revenue thresholds and other alert criteria
3. Run or schedule monitoring – Execute profile manually or let it run on schedule
4. Review alerts – Check Slack for notifications and new product findings
5. Take action – Investigate new products and make business decisions

When NOT to Use

• Task is outside your authorization scope
• You need to implement controls (use implementing-* skills)
• Task is about analysis, not action (use analyzing-* skills)
• You don't have access to target systems
• Task requires compliance expertise (consult professionals)
• Task is about defense, not offense (use defensive skills)

Red Flags

• Expecting real-time monitoring (this skill runs on scheduled intervals, not streaming)
• Using this for one-time research tasks (use kalodata-research-automation instead)
• Monitoring unrelated categories or markets (stick to TikTok Shop Indonesia)
• Ignoring alert configuration (alerts without thresholds are just noise)

Verification

• Monitor profile saves without errors and loads on subsequent runs
• New products are correctly detected by comparing with previous run data
• Slack alerts send successfully and appear in configured channel
• Revenue threshold alerts trigger when products cross configured limits
• Scheduled runs execute without manual intervention

Do Not Use This Skill When

• User only needs one-time research (use kalodata-research-automation)
• User needs real-time product tracking (this is scheduled, not real-time)
• Task is unrelated to TikTok Shop Indonesia market monitoring

Quick Start

This section covers quick start for the kalodata-monitor skill. Key operations include input validation, core processing, and output verification. Refer to the skill overview for detailed usage instructions.

Basic Usage

import { createMonitor, loadMonitorConfig, createProfile } from './index.js';

const config = loadMonitorConfig('./.kalodata-monitor');
const monitor = createMonitor(config);

const profile = createProfile({
  id: 'beauty-trending',
  name: 'Beauty Trending',
  category: 'Beauty',
  goal: 'trending',
  schedule: 'daily',
  slackWebhook: 'https://hooks.slack.com/services/xxx',
});

monitor.saveProfile(profile);
const result = await monitor.runProfile('beauty-trending');
console.log(`Found ${result.newProducts.length} new products`);

CLI Usage

# Set credentials
export KALODATA_SESSION=your_session
export KALODATA_CF_CLEARANCE=your_cf_clearance

# List profiles
node index.js list

# Add a new monitor
node index.js add "Beauty Trends" Beauty trending daily

# Run a specific profile
node index.js run profile-123

# Run all enabled profiles
node index.js run

Core Features

• Core operation execution with comprehensive error handling
• Input validation and output quality assurance
• Integration with existing workflows and toolchains
• Detailed logging for debugging and audit trails

1. Monitor Profiles

Each profile defines what to monitor and when:

interface MonitorProfile {
  id: string;
  name: string;
  category: string;      // Product category name or ID
  goal: string;         // Research goal (trending, emerging, etc.)
  schedule: 'hourly' | 'daily' | 'weekly';
  alerts: AlertCondition;
  topProducts?: number; // Default: 20
  slackWebhook?: string;
  enabled?: boolean;
}

2. Alert Conditions

Configure when to trigger notifications:

interface AlertCondition {
  revenueMin?: number;              // Absolute revenue threshold
  revenueGrowthMultiplier?: number;  // Multiplier vs previous run
  opportunityScoreMin?: number;       // Minimum opportunity score (0-100)
  revenueCrosses?: number;            // Alert when crossing this revenue
}

3. New Product Detection

Automatically compares current run with previous run to identify:

• Products that didn't exist in the last run
• Products crossing revenue thresholds
• Products with rising opportunity scores

4. Slack Notifications

Rich Slack messages with:

• Profile summary
• New products list with key metrics
• Revenue threshold crossings
• Click-through to product details

5. Data Persistence

Stores in .kalodata-monitor/ directory:

• config.json - All profile configurations
• {profile-id}.json - Previous run snapshots for comparison

Configuration

{
  "enabled": true,
  "autoRun": false,
  "timeout": 30000,
  "retries": 3
}

Set environment variables as needed for authentication and endpoints.

Environment Variables

KALODATA_SESSION=your_session_cookie
KALODATA_CF_CLEARANCE=your_cf_clearance_token

Profile Configuration

Create monitors via CLI or programmatically:

CLI Commands

Examples

# Basic usage
invoke <skill-name> with appropriate parameters

# Advanced usage with options
invoke <skill-name> --option value --verbose

Daily Beauty Trends Monitor

node index.js add "Daily Beauty" Beauty trending daily $SLACK_WEBHOOK

Weekly Emerging Products

node index.js add "Weekly Emerging" Beauty emerging weekly

Hourly High-Opportunity Products

node index.js add "Hourly High-Opp" Electronics trending hourly

Integration with Research Automation

The monitor uses kalodata-product-research under the hood:

const result = await monitor.runProfile(profileId);

// Result contains:
{
  profileId: string,
  products: ProductSnapshot[],      // All products from this run
  newProducts: ProductSnapshot[],    // NEW since last run
  crossedThreshold: ProductSnapshot[], // Products crossing thresholds
  alerts: Alert[],                   // Generated alerts
}

Scheduling

For continuous monitoring, add to cron:

# Run every hour
0 * * * * cd /path/to/project && node index.js scheduled

# Run daily at 6 AM
0 6 * * * cd /path/to/project && node index.js scheduled

Dependencies

This skill builds on:

• kalodata-product-research: Core research capabilities
• kalodata-research-automation: Full research workflow

Output Format

CLI output is designed for human readability:

📋 Monitor Profiles:

  ✅ Beauty Trending
     Category: Beauty | Goal: trending | Schedule: daily
     Last run: 2/19/2026, 10:30:00 AM

🚀 Running all enabled profiles...

📊 Run Results:
  New products: 5
  Threshold crossings: 2
  Alerts: 3

✅ Slack notification sent successfully

Process

1. Analyze the task requirements
2. Apply domain expertise
3. Verify output quality

Anti-Rationalization Table