Analyse
Pick the right Kaizen-style lens—Gemba Walk, Value Stream Mapping, or Muda—and run a guided analysis on code, pipelines, or waste without guessing which framework fits.
Overview
Analyse is an agent skill most often used in Operate (also Build, Ship) that auto-selects Gemba Walk, Value Stream Mapping, or Muda Analysis for your target.
Install
npx skills add https://github.com/neolabhq/context-engineering-kit --skill analyseWhat is this skill?
- Auto-selects among three methods: Gemba Walk, Value Stream Mapping, or Muda Analysis—or accepts METHOD override (gemba,
- Gemba Walk for implementation reality vs docs and unfamiliar code paths
- Value Stream Mapping for CI/CD, deployment, and multi-stage handoff bottlenecks
- Muda Analysis for duplication, over-engineering, technical debt, and utilization waste
- CLI-style entry: /analyse [target_description] with optional method override
- 3 Kaizen methods: Gemba Walk, Value Stream Mapping, Muda Analysis
Adoption & trust: 541 installs on skills.sh; 1.1k GitHub stars; 3/3 security scanners passed (skills.sh audits).
What problem does it solve?
You know something is wrong in code or workflow but do not know whether to explore implementation, map the pipeline, or hunt waste.
Who is it for?
Solo builders diagnosing unfamiliar features, slow CI/CD, or codebase bloat who want one entry command instead of three separate frameworks.
Skip if: One-off code generation, greenfield product brainstorming, or security audit checklists that require OWASP-style tooling rather than process analysis.
When should I use this skill?
/analyse [target_description] when analyzing code implementation, workflows, pipelines, inefficiencies, or gaps between docs and reality; optional METHOD override gemba, vsm, muda.
What do I get? / Deliverables
You get a guided Kaizen analysis on the chosen method with concrete observations you can turn into fixes, refactors, or process changes.
- Selected analysis method with rationale
- Guided Gemba, VSM, or Muda findings
- Actionable improvement themes
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Continuous improvement and waste removal sit naturally on Operate → iterate, even when the target is code or CI—the skill’s output is insight for the next fix cycle. Analyse optimizes how work actually flows and what to change next, which is iteration and refinement rather than greenfield implementation.
Where it fits
Run Gemba Walk on an authentication area to compare docs to the code path agents will extend.
Map the release pipeline to see which stage waits longest before you automate a handoff.
Run Muda on duplication and over-engineering before a refactor sprint.
How it compares
Method-selecting Kaizen guide—not a linter, test runner, or static security scanner.
Common Questions / FAQ
Who is analyse for?
Indie developers and small teams using agentic workflows who improve existing code and delivery paths and want Kaizen structure without mastering every variant upfront.
When should I use analyse?
In Operate iterate loops on debt and waste; in Build when exploring how authentication or a feature really works; in Ship when mapping deployment or CI bottlenecks—e.g. /analyse deployment workflow or /analyse codebase for inefficiencies.
Is analyse safe to install?
Check the Security Audits panel on this Prism page and your kit’s source; the skill guides analysis and may prompt agents to read repos or workflow configs you point at.
SKILL.md
READMESKILL.md - Analyse
# 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 ### Process 1. **Define scope**: What code area to explore 2. **State assumptions**: What you think it does 3. **Observe reality**: Read actual code 4. **Document findings**: - Entry points - Actual data flow - Surprises (differs from assumptions) - Hidden dependencies - Undocumented behavior 5. **Identify gaps**: Documentation vs. reality 6. **Recommend**: Update docs, refactor, or accept ### Example: Authentication System Gemba Walk ``` SCOPE: User authentication flow ASSUMPTIONS (Before): • JWT tokens stored in localStorage • Single sign-on via OAuth only • Session expires after 1 hour • Password reset via email link GEMBA OBSERVATIONS (Actual Code): Entry Point: /api/auth/login (routes/auth.ts:45) ├─> AuthService.authenticate() (services/auth.ts:120) ├─> UserRepository.findByEmail() (db/users.ts:67) ├─> bcrypt.compare() (services/auth.ts:145) └─> TokenService.generate() (services/token.ts:34) Actual Flow: 1. Login credentials → POST /api/auth/login 2. Password hashed with bcrypt (10 rounds) 3. JWT generated with 24hr expiry (NOT 1 hour!) 4. Token stored in httpOnly cookie (NOT localStorage) 5. Refresh token in separate cookie (15 days) 6. Session data in Redis (30 days TTL) SURPRISES: ✗ OAuth not implemented (commented out code found) ✗ Password reset is manual (admin intervention) ✗ Three different session storage mechanisms: - Redis for session data - Database for "remember me" - Cookies for tokens ✗ Legacy endpoint /auth/legacy still active (no auth!) ✗ Admin users bypass rate limiting (security issue) GAPS: • Documentation says OAuth, code doesn't have it • Session expiry inconsistent (docs: 1hr, code: 24hr) • Legacy endpoint not documented (security risk) • No mention of "remember me" in docs RECOMMENDATIONS: 1. HIGH: Secure or remove /auth/legacy endpoint 2. HIGH: Document actual session expiry (24hr) 3. MEDIUM: Clean up or implement OAuth 4. MEDIUM: Consolidate session storage (choose one) 5. LOW: Add rate limiting for admin users ``` ### Example: CI/CD Pipeline Gemba Walk ``` SCOPE: Build and deployment pipel