Automation & Integration AI

Process Mapper

Process Mapper is an ecommerce AI skill for Alireza Rezvani, built for teams working with Codex, Claude Code, OpenClaw. Use it to you are connecting recurring work…

Provider
Alireza Rezvani
Platforms
Codex · Claude Code · OpenClaw
View original link · GitHub

What this skill helps you do

A business process documentation tool for internal-operations leaders who need to map end-to-end workflows, identify bottlenecks, and quantify value-add ratios. Produces ASCII swim-lane diagrams by owner, a ranked bottleneck list with severity and root-cause hypotheses, and cycle-time analysis with value-add ratio classification (HEALTHY >25%, TYPICAL 10-25%, WASTE-HEAVY <10%). Applies Goldratt's Theory of Constraints deterministically — never recommends optimization of non-constraint stages. Covers procurement intake, employee onboarding, expense reimbursement, and more.

Install and get started

Copy the full instructions into your AI tool. Test one low-risk example before connecting real store data.

Original Skill instructions

You are a BizOps process-improvement lead. Capture each stage as JSON: name, owner, type (value-add|wait|rework), duration_p50/p90. Run process_documenter.py for ASCII swim-lane diagram by owner. Run cycle_time_analyzer.py for P50/P90 cycle time and value-add ratio. VA% >25%=HEALTHY, 10-25%=TYPICAL, <10%=WASTE-HEAVY. Run bottleneck_detector.py --profile <saas|services|manufacturing|healthcare> with rules: stage P50>2× value-add mean, wait-state>40% of total, rework>15%. Output ranked bottlenecks with severity, root-cause hypothesis, and action. Recommend single constraint-focused intervention per Goldratt — never optimize non-constraint stages. Include rework loops in the map. Label stages honestly — mis-labeling waiting as value-add is the most common failure.

Useful tasks

  • Documenting procurement intake, vendor/employee onboarding, or expense reimbursement processes
  • Diagnosing 'too slow' processes where nobody can name the bottleneck
  • Measuring value-add ratio to distinguish healthy processes from waste-heavy ones
  • Identifying cross-functional handoff failures with swim-lane diagrams
  • Applying Goldratt's Theory of Constraints to focus improvement on a single bottleneck

How to use it

  • Pick ONE process — Goldratt: the constraint is a single point, don't map everything at once
  • Label stages honestly — mis-labeling waiting as value-add is the most common data-quality failure
  • If you can't provide stage-level cycle-time data, instrument the process first, don't map it
  • Value-add ratio below 10% means WASTE-HEAVY — optimize the bottleneck, not a non-constraint stage
  • Adding people to a wait-bound process doesn't help — remove the handoff or batch instead

More skills for this workflow

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