project-timeline-simulator — Claude Code command
Runs several timeline scenarios for a project — baseline, optimistic, pessimistic and disruption — so you can size risk before work starts.
npx claude-code-templates@latest --command project-management/project-timeline-simulatorWhat project-timeline-simulator does
The command pulls its numbers from the repository itself. Contributor count comes from git shortlog -sn --since="90 days ago", and commit volume over the last 30 days stands in for velocity. Project type is either passed as an argument or inferred from the codebase.
From there it models team capacity, skill levels, outside dependencies and technical complexity. You get timeline ranges with confidence intervals, a critical path, risk-adjusted resource allocation, and Monte Carlo results as probability distributions. Early warning indicators and decision triggers come with them.
Only Read, Bash, Grep and Glob are allowed, so nothing in your tree gets rewritten. Arguments follow the shape [project-type] | --duration | --team-size | --risk-level. Without a RISKS.md or similar documentation in the repo, risk assessment leans on git history and code analysis alone.
What it helps with
- estimate realistic delivery dates before committing to them
- compare optimistic and pessimistic scenarios side by side
- map the critical path and spot dependency bottlenecks
- set timeline buffers and allocate the team across milestones
- catch early signals that a project is drifting off schedule
Example prompts for the agent
- Simulate the timeline for
[web-app]with--team-size 5and--risk-level high - Run project-timeline-simulator on this repo and show me the critical path
- Give me a Monte Carlo run over
--duration 6months with confidence intervals
How to install project-timeline-simulator
1claude-code-templates
npx claude-code-templates@latest --command project-management/project-timeline-simulator2Manually: put the files in place
.claude/commands/project-timeline-simulator.mdCall it with /project-timeline-simulator. For all projects use ~/.claude/commands/
Manually: put the files in place
~/.codex/prompts/project-timeline-simulator.mdCall it with /prompts:project-timeline-simulator. Codex marks this format deprecated in favour of skills
Manually: put the files in place
.github/prompts/project-timeline-simulator.prompt.mdManually: put the files in place
.gemini/commands/project-timeline-simulator.tomlGemini stores commands as TOML: the prompt text goes into the prompt field
Questions about project-timeline-simulator
How do I install project-timeline-simulator in Claude Code?
Run npx claude-code-templates@latest --command project-management/project-timeline-simulator. The command lands in .claude/commands/project-timeline-simulator.md.
What does project-timeline-simulator do?
It simulates project outcomes across multiple scenarios, weighs technical, resource and external risks, and suggests how to spread team and budget. Output includes timeline ranges with confidence intervals and Monte Carlo probability distributions.
What input does the simulation need?
It reads git history on its own — contributors over 90 days and commits over 30 days. Pass the project type as an argument, and point it at @RISKS.md or project docs for risk factors.
Source text
project-timeline-simulator.md · MIT
--- allowed-tools: Read, Bash, Grep, Glob argument-hint: "[project-type] | --duration | --team-size | --risk-level" description: Simulate project outcomes with variable modeling, risk assessment, and resource optimization --- # Project Timeline Simulator Simulate project outcomes with comprehensive variable modeling and risk assessment: **$ARGUMENTS** ## Current Project Context - Project type: Based on $ARGUMENTS or codebase analysis - Team capacity: !`git shortlog -sn --since="90 days ago" | wc -l` contributors - Velocity data: !`git log --oneline --since="30 days ago" | wc -l` commits/month - Risk indicators: @RISKS.md or project documentation ## Task Generate comprehensive project timeline simulations with multiple scenarios: **Simulation Framework**: 1. **Variable Modeling** - Team capacity, skill levels, external dependencies, technical complexity 2. **Scenario Generation** - Baseline, optimistic, pessimistic, and disruption scenarios 3. **Risk Assessment** - Technical, resource, business, and external risk factors 4. **Resource Optimization** - Team allocation, budget distribution, timeline buffers 5. **Decision Points** - Milestone gates, adaptation triggers, contingency activation **Output Deliverables**: - Timeline prediction ranges with confidence intervals - Critical path analysis and dependency mapping - Risk-adjusted resource allocation recommendations - Early warning indicators and decision triggers - Monte Carlo simulation results with probability distributions **Success Optimization**: Multi-objective optimization for time, quality, and resource efficiency.
© davila7 · MIT · davila7/claude-code-templates
