# Analyse

Auto-selects best Kaizen method (Gemba Walk, Value Stream, or Muda) for target

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

## Description

Auto-selects best Kaizen method (Gemba Walk, Value Stream, or Muda) for target

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

# Smart Analysis

Intelligently select and apply the most appropriate Kaizen analysis technique based on what you're analyzing.

## Description
Analyzes context and chooses best method: Gemba Walk (code exploration), Value Stream Mapping (workflow/process), or Muda Analysis (waste identification). Guides you through the selected technique.

## Usage
`/analyse [target_description]`

Examples:
- `/analyse authentication implementation`
- `/analyse deployment workflow`
- `/analyse codebase for inefficiencies`

## Variables
- TARGET: What to analyze (default: prompt for input)
- METHOD: Override auto-selection (gemba, vsm, muda)

## Method Selection Logic

**Gemba Walk** → When analyzing:
- Code implementation (how feature actually works)
- Gap between documentation and reality
- Understanding unfamiliar codebase areas
- Actual vs. assumed architecture

**Value Stream Mapping** → When analyzing:
- Workflows and processes (CI/CD, deployment, development)
- Bottlenecks in multi-stage pipelines
- Handoffs between teams/systems
- Time spent in each process stage

**Muda (Waste Analysis)** → When analyzing:
- Code quality and efficiency
- Technical debt
- Over-engineering or duplication
- Resource utilization

## Steps
1. Understand what's being analyzed
2. Determine best method (or use specified method)
3. Explain why this method fits
4. Guide through the analysis
5. Present findings with actionable insights

---

## Method 1: Gemba Walk

"Go and see" the actual code to understand reality vs. assumptions.

### When to Use
- Understanding how feature actually works
- Code archaeology (legacy systems)
- Finding gaps between docs and implementation
- Exploring unfamiliar areas before changes

The rest: https://github.com/NeoLabHQ/context-engineering-kit/blob/HEAD/antigravity/skills/analyse/SKILL.md