Menu

Individual skill

schedule-monte-carlo

0upvotes

Project completion as a distribution, not a date — Monte Carlo over the task graph. Use when a plan's finish date came from summing 'likely' estimates (it's wrong, mathematically), when leadership needs a commit date, or when you need to know which tasks actually control the timeline. Produces P10/P50/P90 completion, per-task criticality (how often each task sits on the critical path), and a real .xlsx — via the bundled zero-dependency simulator, deterministic with a seed.

skills/schedule-monte-carlo/SKILL.md

Read pinned source

Source commit f7c90bc09ee05dc25cf257bdb1826f2c2552c2cb

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
Yes
Repository scan complete
No
Skill scan complete
No
Observed behavior
Network or broad shell
Last checked
Nov 9, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
1,539
Repository last updated
Nov 10, 2026
License
MIT

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt

# Schedule Monte Carlo

Summing the "likely" estimates systematically understates the finish: parallel branches mean the *slowest* path wins each roll, and that maximum is always worse than the middle. This skill runs the actual simulation — thousands of schedule rolls over the dependency graph — and reports the date the way it behaves: as percentiles.

## Required Inputs

- **The task list with three-point estimates** — per task: optimistic / likely / pessimistic (any consistent unit) and dependencies. Honest pessimistics are the whole game: "what if the API vendor ghosts us for two weeks" belongs in that number.
- Simulation count and seed (optional; defaults 5,000 and a fixed seed — results are reproducible).

## Output Format

1. **The headline gap** — deterministic finish (sum-of-likelies) vs P50 vs P90, side by side. The deterministic-to-P50 gap is the lie the old plan told; show it first.
2. **The commitment guidance** — promise P50 internally, P90 externally; the space between is the honesty budget. Name the dates.
3. **Criticality table** — per task, the share of simulations where it sat on the critical path. The top 2-3 are where management attention belongs; a task at 0.9 criticality with a wide estimate range is the schedule.
Back to top