Cycle Count Scheduler

SkillProductivity

AI-driven cycle counting schedule and variance analysis skill to maintain inventory accuracy with minimal operational disruption

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the Cycle Count Scheduler skill

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/business/logistics/skills/cycle-count-scheduler/SKILL.md and read by ahel’s review.

Overview

The Cycle Count Scheduler is an AI-driven skill that optimizes cycle counting schedules and performs variance analysis to maintain inventory accuracy with minimal operational disruption. It uses ABC classification, statistical sampling, and historical accuracy data to prioritize counting activities and identify root causes of inventory discrepancies.

Capabilities

  • ABC-Based Count Frequency Determination: Set count frequencies based on inventory value, velocity, and criticality classifications
  • Statistical Sampling Design: Design statistically valid sampling plans that provide accuracy confidence with minimal counting effort
  • Count Schedule Optimization: Schedule counts during low-activity periods to minimize operational disruption
  • Variance Threshold Alerting: Monitor count variances against thresholds and trigger alerts for significant discrepancies
  • Root Cause Analysis Automation: Analyze variance patterns to identify systemic issues and recommend corrective actions
  • Perpetual vs. Physical Reconciliation: Compare perpetual inventory records with physical counts and manage adjustments
  • Audit Trail Documentation: Maintain complete documentation of counts, variances, and adjustments for compliance

Tools and Libraries

  • WMS APIs
  • Statistical Sampling Libraries
  • Inventory Audit Tools
  • Analytics Platforms

Used By Processes

  • Cycle Counting Program
  • ABC-XYZ Analysis
  • FIFO-LIFO Inventory Control

Usage

skill: cycle-count-scheduler
inputs:
  inventory_profile:
    total_skus: 5000
    abc_distribution:
      A_items: 500
      B_items: 1500
      C_items: 3000
  count_parameters:
    target_accuracy: 99.5
    counting_capacity_skus_per_day: 100
    available_count_days_per_week: 5
  current_accuracy:
    A_items: 98.5
    B_items: 97.8
    C_items: 96.2
outputs:
  count_schedule:
    - classification: "A"
      count_frequency: "weekly"
      skus_per_week: 100
      priority_skus: ["SKU001", "SKU002", "SKU003"]
    - classification: "B"
      count_frequency: "monthly"
      skus_per_week: 75
    - classification: "C"
      count_frequency: "quarterly"
      skus_per_week: 60
  weekly_schedule:
    monday: { zone: "ZONE_A", skus: 45 }
    tuesday: { zone: "ZONE_A", skus: 45 }
    wednesday: { zone: "ZONE_B", skus: 50 }
    thursday: { zone: "ZONE_B", skus: 50 }
    friday: { zone: "ZONE_C", skus: 45 }
  projected_accuracy_improvement:
    A_items: 99.8
    B_items: 99.2
    C_items: 98.5

Integration Points

  • Warehouse Management Systems (WMS)
  • Inventory Management Systems
  • Financial Systems (for adjustments)
  • Compliance/Audit Systems
  • Mobile Counting Devices

Performance Metrics

  • Inventory record accuracy (IRA)
  • Count variance rate
  • Adjustment dollar value
  • Count productivity (SKUs per hour)
  • Time to count completion

Signals

GitHub stars
2k
Forks
112
Last commit
Sep 2026
Advanced
Item type
skill
Key
cycle-count-scheduler
Source
github.com/a5c-ai/babysitter