A self-evolving Software Development Life Cycle (SDLC) enforcement system for AI coding agents. Makes Claude plan before coding, test before shipping, and ask when uncertain. Measures itself getting better over time.
Requires Claude Code (Anthropic's CLI for Claude).
Run from your terminal or from inside Claude Code (! prefix):
npx agentic-sdlc-wizard initThen start (or restart) Claude Code — type /exit then claude to reload hooks. Setup auto-invokes on first prompt — Claude reads the wizard doc, scans your project, and generates bespoke CLAUDE.md, SDLC.md, TESTING.md, and ARCHITECTURE.md. No manual commands needed.
Alternative install methods
From GitHub (no npm needed):
npx github:BaseInfinity/agentic-ai-sdlc-wizard initManual: Download CLAUDE_CODE_SDLC_WIZARD.md to your project and tell Claude Run the SDLC wizard setup.
Health check & updates
npx agentic-sdlc-wizard check # Human-readable
npx agentic-sdlc-wizard check --json # Machine-readable (CI-friendly)Reports MATCH / CUSTOMIZED / MISSING / DRIFT for every installed file. Exits non-zero on MISSING or DRIFT — use in CI to catch setup regressions.
Check for content updates: Tell Claude Check if the SDLC wizard has updates — it reads CHANGELOG.md, shows what's new, and offers to apply changes.
You want Claude Code to follow engineering discipline automatically:
- Plan before coding (not guess-and-check)
- Write tests first (TDD enforced via hooks)
- State confidence (LOW = ask user, don't guess)
- Track work visibly (TaskCreate)
- Self-review before presenting
- Prove it's better (use native features unless you prove custom wins)
The wizard auto-detects your stack (package.json, test framework, deployment targets) and generates bespoke hooks + skills + docs. CI validates the generated assets; cross-stack setup-path E2E is on the roadmap.
Five layers working together:
Layer 5: SELF-IMPROVEMENT
Weekly/monthly workflows detect changes, test them
statistically, create PRs. Baselines evolve organically.
Layer 4: STATISTICAL VALIDATION
E2E scoring with 95% CI (5 trials, t-distribution).
SDP normalizes for model quality. CUSUM catches drift.
Layer 3: SCORING ENGINE
7 criteria, 10/11 points. Claude evaluates Claude.
Before/after wizard A/B comparison in CI.
Layer 2: ENFORCEMENT
Hooks fire every interaction (~100 tokens).
PreToolUse reminds Claude to write tests first.
Layer 1: PHILOSOPHY
The wizard document. KISS. TDD. Confidence levels.
Copy it, run setup, get a bespoke SDLC.
| Capability | What It Does |
|---|---|
| E2E scoring in CI | Every PR gets an automated SDLC compliance score (0-10) — measures whether Claude actually planned, tested, and reviewed |
| Before/after A/B testing | Compares wizard changes against a baseline with 95% confidence intervals to prove improvements aren't noise |
| SDP normalization | Separates "the model had a bad day" from "our SDLC broke" by cross-referencing external benchmarks |
| CUSUM drift detection | Catches gradual quality decay over time — borrowed from manufacturing quality control |
| Pre-tool TDD hooks | Before source edits, a hook reminds Claude to write tests first. CI scoring checks whether it actually followed TDD |
| Self-evolving loop | Weekly/monthly external research + local CI shepherd loop — you approve, the system gets better |
Think Iron Man: Jarvis is nothing without Tony Stark. Tony Stark is still Tony Stark. But together? They make Iron Man. This SDLC is your suit - you build it over time, improve it for your needs, and it makes you both better.
The dream: Mold an ever-evolving SDLC to your needs. Replace my components with native Claude Code features as they ship — and one day, delete this repo entirely because Claude Code has them all built in. That's the goal.
WIZARD FILE (CLAUDE_CODE_SDLC_WIZARD.md)
- Setup guide, used once
- Lives on GitHub, fetched when needed
|
| generates
v
GENERATED FILES (in your repo)
- .claude/hooks/*.sh
- .claude/skills/*/SKILL.md
- .claude/settings.json
- CLAUDE.md, SDLC.md, TESTING.md, ARCHITECTURE.md
|
| validated by
v
CI/CD PIPELINE
- E2E: simulate SDLC task -> score 0-10
- Before/after: main vs PR wizard
- Statistical: 5x trials, 95% CI
- Model-aware: SDP adjusts for external conditions
| Cadence | Source | Action |
|---|---|---|
| Weekly | Claude Code releases | PR with analysis + E2E test |
| Weekly | Community (Reddit, HN) | Issue digest |
| Monthly | Deep research, papers | Trend report |
Every update: regression tested -> AI reviewed -> human approved.
Like evaluating scientific method adherence - we measure process compliance:
| Criterion | Points | Type |
|---|---|---|
| TodoWrite/TaskCreate | 1 | Deterministic |
| Confidence stated | 1 | Deterministic |
| Plan mode | 2 | AI-judge |
| TDD RED | 2 | Deterministic |
| TDD GREEN | 2 | AI-judge |
| Self-review | 1 | AI-judge |
| Clean code | 1 | AI-judge |
40% deterministic + 60% AI-judged. 5 trials handle variance.
| Metric | Meaning |
|---|---|
| Raw | Actual score (Layer 2: SDLC compliance) |
| SDP | Adjusted for model conditions |
| Robustness | How well SDLC holds up vs model changes |
- Robustness < 1.0 = SDLC is resilient (good!)
- Robustness > 1.0 = SDLC is sensitive (investigate)
Tests aren't just validation - they're the foundation everything else builds on.
- Tests >= App Code - Critique tests as hard (or harder) than implementation
- Tests prove correctness - Without them, you're just hoping
- Tests enable fearless change - Refactor confidently
| Plugin | Purpose | Scope |
|---|---|---|
claude-md-management |
Required - CLAUDE.md maintenance | CLAUDE.md only |
claude-code-setup |
Recommends automations | Recommendations |
code-review |
Local self-review and PR review (optional) | Local + PRs |
Don't reinvent the wheel. Use native/built-in features UNLESS you prove your custom version is better. If you can't prove it, delete yours.
- Test the native solution — measure quality, speed, reliability
- Test your custom solution — same scenario, same metrics
- Compare side-by-side
- Native >= custom? Use native. Delete yours.
- Custom > native? Keep yours. Document WHY. Re-evaluate when native improves.
This applies to everything: native commands vs custom skills, framework utilities vs hand-rolled code, library functions vs custom implementations.
This isn't the only Claude Code SDLC tool. Here's an honest comparison:
| Aspect | SDLC Wizard | everything-claude-code | claude-sdlc |
|---|---|---|---|
| Focus | SDLC enforcement + measurement | Agent performance optimization | Plugin marketplace |
| Hooks | 3 (SDLC, TDD, instructions) | 12+ (dev blocker, prettier, etc.) | Webhook watcher |
| Skills | 4 (/sdlc, /setup, /update, /feedback) | 80+ domain-specific | 13 slash commands |
| Evaluation | 95% CI, CUSUM, SDP, Tier 1/2 | Configuration testing | skilltest framework |
| CI Shepherd | Local CI fix loop | No | No |
| Auto-updates | Weekly CC + community scan | No | No |
| Install | npx agentic-sdlc-wizard init |
npm install | npm install |
| Philosophy | Lightweight, prove-it-or-delete | Scale and optimization | Documentation-first |
Our unique strengths: Statistical rigor (CUSUM + 95% CI), SDP scoring (model quality vs SDLC compliance), CI shepherd loop, Prove-It A/B pipeline, comprehensive automated test suite, dogfooding enforcement.
Where others are stronger: everything-claude-code has broader language/framework coverage. claude-sdlc has webhook-driven automation. Both have npm distribution.
The spirit: Open source — we learn from each other. See COMPETITIVE_AUDIT.md for details.
| Document | What It Covers |
|---|---|
| ARCHITECTURE.md | System design, 5-layer diagram, data flows, file structure |
| CI_CD.md | All 4 workflows, E2E scoring, tier system, SDP, integrity checks |
| SDLC.md | Version tracking, enforcement rules, SDLC configuration |
| TESTING.md | Testing philosophy, test diamond, TDD approach |
| CHANGELOG.md | Version history, what changed and when |
| CONTRIBUTING.md | How to contribute, evaluation methodology |
PRs welcome. See CONTRIBUTING.md for evaluation methodology and testing.