# Plan Do Check Act

Iterative PDCA cycle for systematic experimentation and continuous improvement

- Repository: https://github.com/NeoLabHQ/context-engineering-kit (1797 stars)
- Category: Engineering
- License: GPL-3.0
- Last updated: 2026-08-26
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add NeoLabHQ/context-engineering-kit --skill plan-do-check-act -g -a claude-code -y`
Codex: `npx skills add NeoLabHQ/context-engineering-kit --skill plan-do-check-act -g -a codex -y`
Cursor: `npx skills add NeoLabHQ/context-engineering-kit --skill plan-do-check-act -g -a cursor -y`
Gemini CLI: `npx skills add NeoLabHQ/context-engineering-kit --skill plan-do-check-act -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add NeoLabHQ/context-engineering-kit`

## Description

Iterative PDCA cycle for systematic experimentation and continuous improvement

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Plan-Do-Check-Act (PDCA)

Apply PDCA cycle for continuous improvement through iterative problem-solving and process optimization.

## Description

Four-phase iterative cycle: Plan (identify and analyze), Do (implement changes), Check (measure results), Act (standardize or adjust). Enables systematic experimentation and improvement.

## Usage

`/plan-do-check-act [improvement_goal]`

## Variables

- GOAL: Improvement target or problem to address (default: prompt for input)
- CYCLE_NUMBER: Which PDCA iteration (default: 1)

## Steps

### Phase 1: PLAN

1. Define the problem or improvement goal
2. Analyze current state (baseline metrics)
3. Identify root causes (use `/why` or `/cause-and-effect`)
4. Develop hypothesis: "If we change X, Y will improve"
5. Design experiment: what to change, how to measure success
6. Set success criteria (measurable targets)

### Phase 2: DO

1. Implement the planned change (small scale first)
2. Document what was actually done
3. Record any deviations from plan
4. Collect data throughout implementation
5. Note unexpected observations

### Phase 3: CHECK

1. Measure results against success criteria
2. Compare to baseline (before vs. after)
3. Analyze data: did hypothesis hold?
4. Identify what worked and what didn't
5. Document learnings and insights

### Phase 4: ACT

1. **If successful**: Standardize the change
   - Update documentation
   - Train team
   - Create checklist/automation
   - Monitor for regression
2. **If unsuccessful**: Learn and adjust
   - Understand why it failed
   - Refine hypothesis
   - Start new PDCA cycle with adjusted plan
3. **If partially successful**:
   - Standardize what worked
   - Plan next cycle for remaining issues

## Examples

### Example 1: Reducing Build Time

The rest: https://github.com/NeoLabHQ/context-engineering-kit/blob/HEAD/antigravity/skills/plan-do-check-act/SKILL.md