Babysitter resource-scheduler
Resource scheduling and assignment optimization skill for personnel and equipment allocation
install
source · Clone the upstream repo
git clone https://github.com/a5c-ai/babysitter
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/a5c-ai/babysitter "$T" && mkdir -p ~/.claude/skills && cp -r "$T/library/specializations/domains/business/operations/skills/resource-scheduler" ~/.claude/skills/a5c-ai-babysitter-resource-scheduler && rm -rf "$T"
manifest:
library/specializations/domains/business/operations/skills/resource-scheduler/SKILL.mdtags
source content
Resource Scheduler
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
| Objective | Priority | Metric |
|---|---|---|
| Coverage | High | % requirements filled |
| Skill Match | High | Qualified for assignment |
| Fairness | Medium | Balanced distribution |
| Cost | Medium | Overtime minimization |
| Preference | Low | Employee satisfaction |
Shift Patterns
| Pattern | Description | Use Case |
|---|---|---|
| Fixed | Same schedule weekly | Stable demand |
| Rotating | Shifts rotate | 24/7 operations |
| Compressed | Longer days, fewer days | Employee preference |
| Flexible | Variable start/end | Demand variation |
| Split | Two shifts per day | Peak periods |
Skill Matrix
| Resource | Skill 1 | Skill 2 | Skill 3 |
|---|---|---|---|
| Operator A | Expert | Competent | Training |
| Operator B | Training | Expert | None |
| Operator C | Competent | Training | Expert |
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
| Hours | Rate | Threshold |
|---|---|---|
| 0-40 | 1.0x | Standard |
| 40-50 | 1.5x | Overtime |
| 50+ | 2.0x | Double-time |
Cross-Training Strategy
- Identify critical skills
- Assess current coverage
- Identify training candidates
- Develop training plan
- Track progress
- Update skill matrix
Integration Points
- HR/payroll systems
- Time and attendance
- ERP systems
- Communication platforms