demand-sensing-integrator

Real-time demand sensing skill integrating POS data, market signals, and external factors for responsive planning

509 stars

Best use case

demand-sensing-integrator is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Real-time demand sensing skill integrating POS data, market signals, and external factors for responsive planning

Teams using demand-sensing-integrator should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/demand-sensing-integrator/SKILL.md --create-dirs "https://raw.githubusercontent.com/a5c-ai/babysitter/main/library/specializations/domains/business/logistics/skills/demand-sensing-integrator/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/demand-sensing-integrator/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How demand-sensing-integrator Compares

Feature / Agentdemand-sensing-integratorStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Real-time demand sensing skill integrating POS data, market signals, and external factors for responsive planning

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Demand Sensing Integrator

## Overview

The Demand Sensing Integrator provides real-time demand sensing capabilities by integrating POS data, market signals, and external factors for responsive planning. It enables short-term forecast refinement and rapid inventory repositioning in response to changing demand patterns.

## Capabilities

- **POS Data Integration**: Integrate point-of-sale data for real-time demand visibility
- **Social Media Signal Processing**: Monitor social media for demand indicators and trend detection
- **Weather Impact Modeling**: Incorporate weather forecasts and their impact on demand
- **Event-Driven Demand Adjustment**: Adjust demand expectations based on local and global events
- **Short-Term Forecast Refinement**: Refine near-term forecasts using real-time signals
- **Inventory Repositioning Triggers**: Generate alerts for inventory repositioning based on demand shifts
- **Promotional Response Tracking**: Track actual promotional response versus planned lift

## Tools and Libraries

- POS Integration APIs
- Social Listening APIs
- Weather APIs
- ML Models (demand sensing)

## Used By Processes

- Demand Forecasting
- Reorder Point Calculation
- Multi-Channel Fulfillment

## Usage

```yaml
skill: demand-sensing-integrator
inputs:
  item:
    sku: "SKU001"
    category: "outdoor_furniture"
    locations: ["STORE001", "STORE002", "DC001"]
  real_time_data:
    pos_sales_last_7_days:
      - date: "2026-01-18"
        units: 45
      - date: "2026-01-19"
        units: 52
      - date: "2026-01-20"
        units: 48
      - date: "2026-01-21"
        units: 65
      - date: "2026-01-22"
        units: 78
      - date: "2026-01-23"
        units: 82
      - date: "2026-01-24"
        units: 95
  external_factors:
    weather_forecast:
      location: "Northeast Region"
      forecast: "unseasonably_warm"
      temperature_variance: "+15F"
      duration_days: 7
    events:
      - event: "home_improvement_show"
        location: "Boston"
        dates: ["2026-01-25", "2026-01-26", "2026-01-27"]
        expected_impact: 1.3
  baseline_forecast:
    next_7_days: [50, 50, 55, 52, 48, 45, 45]
outputs:
  demand_signals:
    trend: "accelerating"
    trend_strength: "strong"
    signals_detected:
      - signal: "weather_driven_demand"
        confidence: 92
        impact_factor: 1.45
      - signal: "event_proximity"
        confidence: 78
        impact_factor: 1.15
      - signal: "positive_sales_trend"
        confidence: 95
        impact_factor: 1.25
  adjusted_forecast:
    next_7_days: [105, 115, 125, 110, 95, 75, 65]
    adjustment_factor: 1.67
    confidence: 85
  inventory_alerts:
    - location: "STORE001"
      current_inventory: 25
      projected_demand_7_days: 85
      stockout_risk: "high"
      recommended_action: "expedite_replenishment"
      transfer_from: "DC001"
      quantity: 75
    - location: "STORE002"
      current_inventory: 40
      projected_demand_7_days: 70
      stockout_risk: "medium"
      recommended_action: "increase_replenishment"
  promotional_tracking:
    active_promotions: []
    organic_demand_increase: true
```

## Integration Points

- Point of Sale Systems
- E-commerce Platforms
- Weather Services
- Social Media APIs
- Demand Planning Systems

## Performance Metrics

- Forecast accuracy improvement
- Signal detection accuracy
- Inventory repositioning effectiveness
- Stockout prevention rate
- Response time to demand shifts

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