Agent skill

last-mile-delivery-optimizer

Final delivery leg optimization skill including dynamic scheduling, time-window management, and delivery confirmation

View SKILL.md on GitHub Repository
Stars 514
Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/a5c-ai/babysitter/tree/main/library/specializations/domains/business/logistics/skills/last-mile-delivery-optimizer

Metadata

Additional technical details for this skill

domain
business
category
distribution
priority
medium
specialization
logistics

SKILL.md

Last-Mile Delivery Optimizer

Overview

The Last-Mile Delivery Optimizer focuses on the final delivery leg optimization including dynamic scheduling, time-window management, and delivery confirmation. It maximizes delivery density, manages customer expectations, and coordinates various delivery methods including traditional carriers and crowdsourced options.

Capabilities

  • Delivery Density Optimization: Maximize deliveries per route by clustering nearby addresses
  • Time Window Scheduling: Schedule deliveries within customer-preferred time windows
  • Driver Dispatch Optimization: Assign deliveries to drivers based on location, capacity, and skills
  • Proof of Delivery Automation: Capture signatures, photos, and timestamps for delivery confirmation
  • Failed Delivery Management: Handle failed deliveries including rescheduling and alternative locations
  • Customer Communication Integration: Send proactive updates on delivery status and ETA
  • Crowdsourced Delivery Coordination: Integrate with gig economy platforms for flexible capacity

Tools and Libraries

  • Routing APIs
  • Last-Mile Platforms
  • Driver Apps
  • Customer Notification Systems

Used By Processes

  • Last-Mile Delivery Optimization
  • Route Optimization
  • Multi-Channel Fulfillment

Usage

yaml
skill: last-mile-delivery-optimizer
inputs:
  deliveries:
    - delivery_id: "DEL001"
      address: "123 Main St, Boston, MA"
      coordinates: { lat: 42.3601, lng: -71.0589 }
      time_window: { start: "14:00", end: "18:00" }
      packages: 2
      special_instructions: "Leave at front door"
      customer_phone: "+1-555-0123"
    - delivery_id: "DEL002"
      address: "456 Oak Ave, Boston, MA"
      coordinates: { lat: 42.3651, lng: -71.0549 }
      time_window: { start: "10:00", end: "14:00" }
      packages: 1
      signature_required: true
  drivers:
    - driver_id: "DRV001"
      current_location: { lat: 42.3501, lng: -71.0650 }
      capacity_packages: 50
      shift_end: "20:00"
      skills: ["signature_capture", "heavy_items"]
  optimization_parameters:
    optimize_for: "delivery_density"
    max_route_time_hours: 8
    customer_notification: true
outputs:
  delivery_routes:
    - driver_id: "DRV001"
      route:
        - delivery_id: "DEL002"
          sequence: 1
          eta: "11:30"
          eta_window: { start: "11:15", end: "11:45" }
        - delivery_id: "DEL001"
          sequence: 2
          eta: "15:30"
          eta_window: { start: "15:15", end: "15:45" }
      total_deliveries: 2
      total_distance_km: 12.5
      estimated_completion: "16:00"
  customer_notifications:
    - delivery_id: "DEL001"
      notification_type: "eta_update"
      scheduled_time: "14:00"
      message: "Your delivery is on the way. Expected arrival: 3:30 PM"
  metrics:
    deliveries_per_route: 15.5
    average_delivery_time_minutes: 8
    on_time_delivery_rate: 96.5

Integration Points

  • Transportation Management Systems (TMS)
  • Order Management Systems
  • Customer Communication Platforms
  • Driver Mobile Apps
  • GPS/Telematics Systems

Performance Metrics

  • Deliveries per route
  • On-time delivery rate
  • First-attempt success rate
  • Cost per delivery
  • Customer satisfaction score

Recommended Agent Skills

Expand your agent's capabilities with these related and highly-rated skills.

a5c-ai/babysitter

gsd-tools

Central utility skill for GSD operations. Provides config parsing, slug generation, timestamps, path operations, and orchestrates calls to other specialized skills. Acts as the unified entry point that the original gsd-tools.cjs provided via its lib/ modules (commands, config, core, init).

514 31
Explore
a5c-ai/babysitter

model-profile-resolution

Resolve model profile (quality/balanced/budget) at orchestration start and map agents to specific models. Enables cost/quality tradeoffs by selecting appropriate AI models for each agent role.

514 31
Explore
a5c-ai/babysitter

verification-suite

Plan structure validation, phase completeness checks, reference integrity verification, and artifact existence confirmation. Provides the structured verification layer ensuring GSD artifacts are well-formed and complete.

514 31
Explore
a5c-ai/babysitter

state-management

STATE.md reading, writing, and field-level updates. Provides cross-session state persistence via .planning/STATE.md with structured fields for current task, completed phases, blockers, decisions, and quick tasks.

514 31
Explore
a5c-ai/babysitter

git-integration

Git commit patterns, formats, and conventions for GSD methodology. Provides atomic commits per task, structured commit messages, planning file commits, branch management, and milestone tag operations.

514 31
Explore
a5c-ai/babysitter

frontmatter-parsing

YAML frontmatter parsing and manipulation for .planning/ documents. Provides read, write, update, query, and validation operations on frontmatter blocks in GSD markdown artifacts.

514 31
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results