Logistics kpi tracker

Skill a5c-ai/babysitter/library/specializations/domains/business/logistics/skills/logistics-kpi-tracker

Comprehensive logistics performance measurement skill with KPI tracking, benchmarking, and improvement recommendationsFrom its SKILL.md

Install

npx -y skills add a5c-ai/babysitter --skill logistics-kpi-tracker

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

4.2 KB, 976 tokens by cl100k_base, as published. Nobody here has run it

Logistics KPI Tracker

Overview

The Logistics KPI Tracker provides comprehensive logistics performance measurement with KPI tracking, benchmarking, and improvement recommendations. It monitors key metrics across all logistics functions and identifies opportunities for operational improvement.

Capabilities

OTIF (On-Time In-Full) Tracking: Track on-time and in-full delivery performance against commitments
Perfect Order Rate Calculation: Calculate perfect order rates considering all order fulfillment dimensions
Fill Rate Analysis: Monitor fill rates at order, line, and unit levels
Order Cycle Time Measurement: Track order cycle times from order placement to delivery
Cost Per Order/Unit Tracking: Calculate and monitor logistics costs at various levels
Benchmark Comparison: Compare performance against industry benchmarks and best practices
Improvement Opportunity Identification: Identify areas for operational improvement based on KPI analysis

Tools and Libraries

BI Platforms (Tableau, Power BI)
Data Warehousing
Logistics Dashboards
Statistical Analysis Libraries

Used By Processes

All logistics processes (cross-cutting)

Usage

skill: logistics-kpi-tracker
inputs:
  reporting_period:
    start: "2026-01-01"
    end: "2026-01-24"
  data_sources:
    orders: true
    shipments: true
    inventory: true
    costs: true
  benchmarks:
    otif: 95.0
    perfect_order_rate: 90.0
    fill_rate: 98.0
    order_cycle_time_days: 3.0
    cost_per_order: 12.50
  comparison:
    prior_period: true
    prior_year: true
outputs:
  kpi_summary:
    otif:
      actual: 93.5
      target: 95.0
      variance: -1.5
      trend: "improving"
      prior_period: 92.8
      prior_year: 91.2
    perfect_order_rate:
      actual: 88.2
      target: 90.0
      variance: -1.8
      trend: "stable"
      components:
        on_time: 93.5
        in_full: 96.2
        damage_free: 99.1
        accurate_documentation: 98.5
    fill_rate:
      actual: 97.5
      target: 98.0
      variance: -0.5
      trend: "stable"
    order_cycle_time:
      actual_days: 2.8
      target_days: 3.0
      variance: 0.2
      trend: "improving"
    cost_per_order:
      actual: 11.85
      target: 12.50
      variance: 0.65
      trend: "improving"
  performance_breakdown:
    by_channel:
      ecommerce: { otif: 91.2, fill_rate: 96.8 }
      wholesale: { otif: 95.8, fill_rate: 98.2 }
      retail: { otif: 94.1, fill_rate: 97.8 }
    by_region:
      northeast: { otif: 94.5, fill_rate: 98.1 }
      southeast: { otif: 92.8, fill_rate: 97.0 }
      midwest: { otif: 93.9, fill_rate: 97.5 }
  improvement_opportunities:
    - area: "On-Time Delivery"
      current: 93.5
      target: 95.0
      gap: 1.5
      root_causes:
        - "Carrier performance in Southeast region"
        - "Dock congestion at DC002"
      recommendations:
        - "Carrier performance review with underperformers"
        - "Implement dock scheduling system at DC002"
      potential_improvement: 2.0
    - area: "Fill Rate"
      current: 97.5
      target: 98.0
      gap: 0.5
      root_causes:
        - "Safety stock levels insufficient for high-velocity items"
      recommendations:
        - "Review and adjust safety stock for A-class items"
      potential_improvement: 0.8

Integration Points

Enterprise Resource Planning (ERP)
Warehouse Management Systems (WMS)
Transportation Management Systems (TMS)
Order Management Systems
Business Intelligence Platforms

Performance Metrics

OTIF percentage
Perfect order rate
Fill rate
Order cycle time
Cost per order

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 0 of the 12 instructions most operations skills give in 976 tokens

Counted across 483 of the 484 authors here whose files we hold, read 2026-08-07

Collect monitoring data throughout the simulationin 14 of 483, across 6 files
Set the random seed for reproducibilityin 14 of 483, across 6 files
Validate simulations against analytical solutionsin 12 of 483, across 4 files
Clarify goals, constraints, and inputsin 11 of 483, across 2 files
Implement contract tests for integration pointsin 11 of 483, across 2 files
Implement strangler fig infrastructure with API gatewayin 11 of 483, across 2 files
Audit modernized components for security vulnerabilitiesin 11 of 483, across 2 files
Avoid Python blocking calls in processesin 10 of 483, across 3 files
Use resource context managers for automatic cleanupin 9 of 483, across 2 files
Maintain consistent time unitsin 9 of 483, across 2 files
Validate outcomes against success criteriain 8 of 483, across 1 file
Analyze the legacy codebase for technical debtin 8 of 483, across 1 file

Said here and by no other author read

Track on-time and in-full delivery performance
Calculate perfect order rates
Monitor fill rates at order, line, and unit levels
Track order cycle times
Calculate and monitor logistics costs
Compare performance against industry benchmarks

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.