Imported from jmagly/aiwg (agentic/code/plugins/sdlc/skills/project-timeline-simulator/SKILL.md). Install upstream with npx skills add jmagly/aiwg --skill project-timeline-simulator. Copyright stays with the author.

Project Timeline Simulator

Simulate project outcomes with variable modeling, risk assessment, and resource optimization scenarios.

Instructions

You are tasked with creating comprehensive project timeline simulations to optimize planning, resource allocation, and risk management. Follow this approach: $ARGUMENTS

1. Prerequisites Assessment

Critical Project Context Validation:

• Project Scope: What specific project are you simulating timelines for?
• Key Variables: What factors could significantly impact timeline outcomes?
• Resource Constraints: What team, budget, and time limitations apply?
• Success Criteria: How will you measure project success and timeline effectiveness?
• Risk Tolerance: What level of schedule risk is acceptable?

If context is unclear, guide systematically:

Missing Project Scope:
"What type of project needs timeline simulation?
- Software Development: Feature development, platform migration, system redesign
- Product Launch: New product development from concept to market
- Business Initiative: Process improvement, organizational change, market expansion
- Infrastructure Project: System upgrades, tool implementation, capacity expansion

Please specify project deliverables, stakeholders, and success criteria."

Missing Key Variables:
"What factors could significantly impact your project timeline?
- Resource Availability: Team capacity, skill availability, external dependencies
- Technical Complexity: Unknown requirements, integration challenges, performance needs
- External Dependencies: Vendor deliveries, regulatory approvals, partner coordination
- Market Dynamics: Customer feedback, competitive pressure, business priority changes"

2. Project Structure Modeling

Systematically map project components and dependencies:

Work Breakdown Structure (WBS) Analysis

Project Component Framework:

Phase-Based Structure:
- Discovery/Planning: Requirements gathering, design, architecture planning
- Development/Implementation: Core building, integration, testing phases
- Validation/Testing: Quality assurance, user acceptance, performance validation
- Deployment/Launch: Release preparation, rollout, go-live activities
- Stabilization/Optimization: Post-launch support, performance tuning, iteration

Feature-Based Structure:
- Core Features: Essential functionality for minimum viable product
- Enhanced Features: Additional capabilities for competitive advantage
- Integration Features: System connectivity and data synchronization
- Quality Features: Security, performance, reliability, and maintainability

Skill-Based Structure:
- Frontend Development: User interface and experience implementation
- Backend Development: Server logic, APIs, and data processing
- Infrastructure/DevOps: Deployment, monitoring, and operational setup
- Design/UX: User research, interface design, and usability testing
- Quality Assurance: Testing strategy, automation, and validation

Dependency Mapping Framework

Project Dependency Analysis:

Sequential Dependencies:
- Finish-to-Start: Task B cannot begin until Task A completes
- Start-to-Start: Task B cannot start until Task A has started
- Finish-to-Finish: Task B cannot finish until Task A finishes
- Start-to-Finish: Task B cannot finish until Task A starts

Resource Dependencies:
- Shared Resources: Team members working across multiple tasks
- Skill Dependencies: Specialized expertise required for specific tasks
- Tool Dependencies: Software, hardware, or platform availability
- Budget Dependencies: Funding approval and expenditure timing

External Dependencies:
- Vendor Deliveries: Third-party software, services, or hardware
- Regulatory Approvals: Compliance reviews and certification processes
- Stakeholder Decisions: Business approvals and priority setting
- Market Timing: Customer readiness and competitive positioning

3. Variable Modeling Framework

Systematically model factors affecting timeline outcomes:

Uncertainty Factor Analysis

Timeline Variable Categories:

Effort Estimation Variables:
- Task Complexity: Simple, moderate, complex, or unknown complexity
- Team Experience: Expert, experienced, moderate, or novice skill levels
- Requirements Clarity: Well-defined, partially defined, or evolving requirements
- Technology Maturity: Proven, established, emerging, or experimental technology

Resource Variables:
- Team Availability: Full-time, part-time, or shared allocation percentages
- Skill Availability: In-house expertise, contractors, or training requirements
- Infrastructure Readiness: Available, partially ready, or needs development
- Budget Flexibility: Fixed, constrained, or adjustable funding levels

External Variables:
- Stakeholder Responsiveness: Fast, normal, or slow decision and feedback cycles
- Market Stability: Stable, evolving, or rapidly changing requirements
- Regulatory Environment: Clear, evolving, or uncertain compliance landscape
- Competitive Pressure: Low, moderate, or high urgency for delivery

Variable Distribution Modeling

Probabilistic Timeline Estimation:

Three-Point Estimation:
- Optimistic Estimate: Best-case scenario with favorable conditions
- Most Likely Estimate: Expected scenario with normal conditions
- Pessimistic Estimate: Worst-case scenario with adverse conditions

Distribution Types:
- PERT Distribution: Beta distribution weighted toward most likely
- Triangular Distribution: Linear probability between min, mode, max
- Normal Distribution: Bell curve around mean with standard deviation
- Log-Normal Distribution: Right-skewed for tasks with uncertainty

Monte Carlo Simulation:
- Random sampling from variable distributions
- Thousands of simulation runs for statistical analysis
- Confidence intervals for timeline predictions
- Risk quantification and probability assessment

4. Scenario Generation Engine

Create comprehensive project timeline scenarios:

Scenario Development Framework

Multi-Dimensional Scenario Portfolio:

Baseline Scenarios (40% of simulations):
- Normal Resource Availability: Team at expected capacity and skills
- Standard Complexity: Requirements and technical challenges as anticipated
- Typical External Factors: Normal stakeholder responsiveness and market conditions
- Expected Dependencies: Third-party deliveries and approvals on schedule

Optimistic Scenarios (20% of simulations):
- Enhanced Resource Availability: Additional team members or improved productivity
- Reduced Complexity: Simpler requirements or technical solutions
- Favorable External Factors: Fast stakeholder decisions and stable market
- Accelerated Dependencies: Early vendor deliveries and quick approvals

Pessimistic Scenarios (25% of simulations):
- Constrained Resources: Team availability issues or skill gaps
- Increased Complexity: Scope creep or technical challenges
- Adverse External Factors: Slow decisions or changing market conditions
- Delayed Dependencies: Late vendor deliveries or approval delays

Disruption Scenarios (15% of simulations):
- Major Scope Changes: Significant requirement modifications mid-project
- Team Disruptions: Key team member departures or organizational changes
- Technology Disruptions: Platform changes or security requirements
- Market Disruptions: Competitive pressure or business priority shifts

Critical Path Analysis

• Identification of activities that directly impact project completion
• Float/slack analysis for non-critical activities
• Critical path vulnerability assessment under different scenarios
• Resource optimization for critical path acceleration

5. Risk Assessment and Impact Modeling

Comprehensive project risk evaluation:

Risk Identification Framework

Project Risk Categories:

Technical Risks:
- Requirements Risk: Unclear, changing, or conflicting requirements
- Technology Risk: Unproven technology or integration challenges
- Performance Risk: Scalability, reliability, or efficiency concerns
- Security Risk: Data protection and compliance requirements

Resource Risks:
- Team Risk: Availability, skills, or productivity challenges
- Budget Risk: Funding constraints or cost overruns
- Time Risk: Schedule pressure or competing priorities
- Vendor Risk: Third-party delivery or quality issues

Business Risks:
- Market Risk: Customer needs or competitive landscape changes
- Stakeholder Risk: Changing priorities or approval delays
- Regulatory Risk: Compliance requirements or policy changes
- Strategic Risk: Business model or technology direction shifts

Risk Impact Simulation

Risk Effect Modeling:

Probability Assessment:
- High Probability (70-90%): Likely to occur based on historical data
- Medium Probability (30-70%): Possible occurrence with mixed indicators
- Low Probability (5-30%): Unlikely but possible based on rare events
- Very Low Probability (<5%): Black swan events with major impact

Impact Assessment:
- Schedule Impact: Days or weeks of delay caused by risk realization
- Resource Impact: Additional team members or budget required
- Quality Impact: Feature cuts or technical debt accumulation
- Business Impact: Revenue delay or customer satisfaction reduction

Risk Mitigation Modeling:
- Prevention Strategies: Actions to reduce risk probability
- Mitigation Strategies: Plans to reduce risk impact if it occurs
- Contingency Plans: Alternative approaches when risks materialize
- Transfer Strategies: Insurance, contracts, or vendor risk sharing

6. Resource Optimization Simulation

Systematically optimize resource allocation across scenarios:

Resource Allocation Framework

Multi-Objective Resource Optimization:

Team Allocation Optimization:
- Skill matching for maximum productivity and quality
- Workload balancing to prevent burnout and bottlenecks
- Cross-training opportunities for risk reduction
- Contractor vs full-time employee optimization

Budget Allocation Optimization:
- Feature prioritization for maximum business value
- Infrastructure investment for scalability and reliability
- Tool and technology investment for productivity
- Risk mitigation investment for schedule protection

Timeline Optimization:
- Parallel work stream identification and coordination
- Critical path acceleration through resource concentration
- Non-critical path scheduling for resource smoothing
- Buffer allocation for uncertainty and risk management

Resource Constraint Modeling

• Team capacity limitations and productivity variations
• Budget restrictions and approval processes
• Tool and infrastructure availability constraints
• Skill development timelines and learning curves

7. Decision Point Integration

Connect simulation insights to project management decisions:

Adaptive Project Management

Simulation-Driven Decision Framework:

Milestone Decision Points:
- Go/No-Go Decisions: Continue, pivot, or cancel based on progress
- Resource Reallocation: Team or budget adjustments based on performance
- Scope Adjustments: Feature prioritization based on timeline pressure
- Risk Response: Mitigation strategy activation based on emerging risks

Early Warning Systems:
- Schedule Variance Triggers: When actual progress deviates from plan
- Resource Utilization Alerts: Team productivity or availability changes
- Risk Indicator Monitoring: Early signals of potential problems
- Quality Metric Tracking: Defect rates or technical debt accumulation

Adaptive Strategies:
- Agile Scope Management: Feature prioritization and MVP definition
- Resource Flexibility: Team scaling and skill augmentation options
- Timeline Buffer Management: Schedule contingency allocation and usage
- Quality Trade-off Management: Technical debt vs delivery speed decisions

Project Success Optimization

Success Metric Optimization:

Time-Based Success:
- On-Time Delivery: Probability of meeting original schedule
- Schedule Acceleration: Options for faster delivery with trade-offs
- Milestone Achievement: Interim goal completion likelihood
- Critical Path Protection: Schedule risk mitigation effectiveness

Quality-Based Success:
- Feature Completeness: Scope delivery against original requirements
- Technical Quality: Code quality, performance, and maintainability
- User Satisfaction: Usability and functionality meeting user needs
- Business Value: ROI and strategic objective achievement

Resource-Based Success:
- Budget Performance: Cost control and financial efficiency
- Team Satisfaction: Developer experience and retention
- Stakeholder Satisfaction: Communication and expectation management
- Knowledge Transfer: Capability building and learning objectives

8. Output Generation and Recommendations

Present simulation insights in actionable project management format:

## Project Timeline Simulation: [Project Name]

### Simulation Summary
- Scenarios Analyzed: [number and types of scenarios]
- Timeline Range: [minimum to maximum completion estimates]
- Success Probability: [likelihood of on-time, on-budget delivery]
- Key Risk Factors: [primary threats to project success]

### Timeline Predictions

| Scenario Type | Completion Probability | Duration Range | Key Assumptions |
|---------------|----------------------|----------------|-----------------|
| Optimistic | 90% | 12-14 weeks | Ideal conditions |
| Baseline | 70% | 16-20 weeks | Normal conditions |
| Pessimistic | 50% | 22-28 weeks | Adverse conditions |
| Worst Case | 10% | 30+ weeks | Multiple problems |

### Critical Success Factors
- Resource Availability: [team capacity and skill requirements]
- Dependency Management: [external coordination and timing]
- Risk Mitigation: [proactive risk prevention and response]
- Scope Management: [feature prioritization and change control]

### Recommended Strategy
- Primary Approach: [optimal resource allocation and timeline strategy]
- Contingency Plans: [backup strategies for different scenarios]
- Early Warning Indicators: [metrics to monitor for course correction]
- Decision Points: [key milestones for strategy adjustment]

### Resource Optimization
- Team Allocation: [optimal skill and capacity distribution]
- Budget Distribution: [investment prioritization across features and risk mitigation]
- Timeline Buffers: [schedule contingency allocation recommendations]
- Quality Investment: [testing and technical debt management strategy]

### Risk Management Plan
- High-Priority Risks: [most critical threats and mitigation strategies]
- Monitoring Strategy: [early detection and response systems]
- Contingency Resources: [backup team and budget allocation]
- Escalation Procedures: [decision triggers and stakeholder communication]

9. Continuous Project Learning

Establish ongoing simulation refinement and project improvement:

Performance Tracking

• Actual vs predicted timeline performance measurement
• Resource utilization efficiency and productivity assessment
• Risk realization frequency and impact validation
• Decision quality improvement over multiple projects

Methodology Enhancement

• Simulation accuracy improvement based on project outcomes
• Estimation technique refinement and calibration
• Risk model enhancement and validation
• Team capability and productivity modeling improvement

Usage Examples

# Software development project simulation
/project-timeline-simulator Simulate 6-month e-commerce platform development with 8-person team and Q4 launch deadline

# Product launch timeline modeling
/project-timeline-simulator Model mobile app launch timeline with user testing, app store approval, and marketing campaign coordination

# Infrastructure migration simulation
/project-timeline-simulator Simulate cloud migration project with legacy system dependencies and zero-downtime requirement

# Agile release planning
/project-timeline-simulator Model next quarter sprint planning with feature prioritization and team velocity uncertainty

Quality Indicators

• Green: Comprehensive scenarios, validated risk models, optimized resource allocation
• Yellow: Multiple scenarios, basic risk assessment, reasonable resource planning
• Red: Single timeline, minimal risk consideration, resource allocation not optimized

Common Pitfalls to Avoid

• Planning fallacy: Systematic underestimation of time and resources required
• Single-point estimates: Not modeling uncertainty and variability
• Resource optimism: Assuming 100% utilization and no productivity variation
• Risk blindness: Not identifying and planning for likely problems
• Scope creep ignorance: Not accounting for requirement changes and additions
• Static planning: Not adapting simulation based on actual project progress

Transform project planning from hopeful guessing into systematic, evidence-based timeline optimization through comprehensive simulation and scenario analysis.

References

• @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/vague-discretion.md — Timeline estimates must be bounded and measurable; avoid "flexible" or "as needed" schedule buffers
• @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/research-before-decision.md — Validate project scope and constraints before generating scenarios
• @$AIWG_ROOT/agentic/code/addons/aiwg-utils/skills/project-status/SKILL.md — Use to confirm current SDLC phase and existing planning artifacts before simulating
• @$AIWG_ROOT/agentic/code/frameworks/sdlc-complete/skills/project-health-check/SKILL.md — Health metrics (velocity, defect rate) feed into simulation variable modeling