Resource Scheduler

SkillProductivity

Resource scheduling and assignment optimization skill for personnel and equipment allocation

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 Resource Scheduler skill

What this skill tells your AI

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

Overview

The Resource Scheduler skill provides comprehensive capabilities for optimizing resource scheduling and assignment. It supports skill-based assignment, shift scheduling, overtime optimization, and equipment allocation.

Capabilities

  • Skill-based assignment
  • Shift scheduling
  • Overtime optimization
  • Cross-training utilization
  • Equipment allocation
  • Maintenance window scheduling
  • Conflict resolution
  • Schedule publication

Used By Processes

  • CAP-002: Production Scheduling Optimization
  • CAP-001: Capacity Requirements Planning
  • TOC-002: Drum-Buffer-Rope Scheduling

Tools and Libraries

  • Workforce management systems
  • Scheduling optimization algorithms
  • HR systems integration
  • Communication platforms

Usage

skill: resource-scheduler
inputs:
  scheduling_horizon: 7  # days
  resources:
    - name: "John Smith"
      type: "operator"
      skills: ["assembly", "welding", "inspection"]
      shift_preference: "day"
      max_hours: 50
    - name: "Jane Doe"
      type: "operator"
      skills: ["assembly", "packaging"]
      shift_preference: "flexible"
      max_hours: 45
  requirements:
    - date: "2026-01-25"
      shift: "day"
      skill: "assembly"
      count: 3
    - date: "2026-01-25"
      shift: "day"
      skill: "welding"
      count: 2
  constraints:
    - "No consecutive night shifts"
    - "Minimum 8 hours between shifts"
    - "Maximum 10 hours per shift"
outputs:
  - schedule_assignments
  - coverage_report
  - overtime_forecast
  - skill_gaps
  - conflict_resolutions

Scheduling Objectives

ObjectivePriorityMetric
CoverageHigh% requirements filled
Skill MatchHighQualified for assignment
FairnessMediumBalanced distribution
CostMediumOvertime minimization
PreferenceLowEmployee satisfaction

Shift Patterns

PatternDescriptionUse Case
FixedSame schedule weeklyStable demand
RotatingShifts rotate24/7 operations
CompressedLonger days, fewer daysEmployee preference
FlexibleVariable start/endDemand variation
SplitTwo shifts per dayPeak periods

Skill Matrix

ResourceSkill 1Skill 2Skill 3
Operator AExpertCompetentTraining
Operator BTrainingExpertNone
Operator CCompetentTrainingExpert

Assignment Algorithm

1. Identify requirements
2. Match skills to requirements
3. Apply availability constraints
4. Optimize for objectives
5. Resolve conflicts
6. Publish schedule

Overtime Management

HoursRateThreshold
0-401.0xStandard
40-501.5xOvertime
50+2.0xDouble-time

Cross-Training Strategy

  1. Identify critical skills
  2. Assess current coverage
  3. Identify training candidates
  4. Develop training plan
  5. Track progress
  6. Update skill matrix

Integration Points

  • HR/payroll systems
  • Time and attendance
  • ERP systems
  • Communication platforms

Signals

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