Build with AI like an engineering team — not like a chat session.

Vibe Coding Production Kit (VCP) is a production-minded operating system and zero-runtime-dependency CLI for AI-assisted software development. It turns vague “vibe coding” into a repeatable engineering lifecycle built around specifications, architecture, bounded tasks, repository-native agent rules, readiness gates, security, verification evidence, independent review, safe updates, and recovery.

It is model-agnostic and works with tools such as Codex, Claude Code, Cursor, GitHub Copilot, and other coding agents.

Arabic documentation: README.ar.md

Run the published npm package directly — no global install required:

npx vibe-coding-production init . --agent all --stack auto --yesOr target another repository:

npx vibe-coding-production init ./my-app --agent claude --stack auto --yesPreview without writing:

npx vibe-coding-production init . --agent all --stack auto --dry-runThe executable is also available as vcp when installed or invoked through npm package tooling.

If you intentionally want to run the repository version instead of the published npm package:

npx --yes github:MoeEyani/Vibe-Coding-Production-Kit init . --agent all --stack auto --yesThe CLI requires Node.js 22+, has no runtime dependencies, and auto-detects TypeScript, Python, and Go only when repository evidence supports that decision.

New here? Follow the end-to-end 10-minute Quickstart.

Most vibe-coding workflows optimize for getting the first demo working. VCP optimizes for the 100th feature, the second developer, production incidents, security reviews, migrations, refactors, upgrades, and years of maintenance.

init

↓

task

↓

ready --stage plan

↓

context --mode plan

↓

plan

↓

ready --stage implement

↓

context --mode implement

↓

implement

↓

verify

↓

independent review

↓

doctor

↓

release / observe

When a newer VCP version is available:

update --check

↓

update --dry-run

↓

resolve conflicts if any

↓

update

↓

doctor

vcp init now creates .vcp/manifest.json and persistent baseline snapshots. Once a repository is initialized, VCP refuses to replace that lifecycle state with init --force; upgrades go through the update engine.

Check version state:

vcp update . --check

vcp update . --check --jsonPreview the full migration plan without writing project files:

vcp update . --dry-runApply after reviewing the plan:

vcp update .Recover the newest safe recovery point:

vcp rollback .Detach or re-track one VCP-managed file without deleting local content:

vcp manage ignore AGENTS.md

vcp manage track AGENTS.mdThe update engine uses:

- persistent baseline hashes and snapshots;

- managed,- generated, and- preserveownership policies;

- bounded three-way merge for independent edits;

- explicit CONFLICTinstead of guessing on overlaps;

- versioned migration declarations for renames/removals;

- lifecycle locking before planning and mutation;

- path traversal and symlink protections;

- transaction state, backups, post-apply verification, and automatic rollback;

- conservative rollback semantics instead of pretending partial historical backups are complete snapshots.

See docs/UPDATES.md for the full contract and docs/CLI.md for commands/options.

The read-only doctor checks whether the engineering system is actually configured—not merely copied:

npx vibe-coding-production doctor .It reports concrete PASS / WARN / FAIL findings for agent instructions, unresolved verification commands, source-of-truth documents, untouched templates, CI, plan/review workflow, manifest compatibility, baseline integrity, and interrupted update transactions.

Use --json for automation or --strict to make warnings non-zero. See docs/DOCTOR.md.

npx vibe-coding-production task accept-invite --title "Accept invitation"The generator creates docs/tasks/accept-invite.md with source-of-truth links, acceptance criteria, scope boundaries, security/privacy questions, failure modes, observability, tests, rollout/recovery, implementation planning, review checks, and the verification commands actually configured in AGENTS.md.

See docs/TASK-PACKS.md.

vcp ready accept-invite --stage plan

vcp ready accept-invite --stage implementThe planning gate requires a real outcome, resolvable Source of Truth, concrete acceptance criteria, and explicit scope. The implementation gate additionally requires resolved architecture/data/integration boundaries, domain invariants, security/privacy, failure modes, observability, testing, rollout/recovery, and a concrete implementation plan.

vcp context accept-invite --mode planUse --mode implement, review, security, or release as the task progresses. Add only affected implementation files with repeatable --include flags. Context packs reject repository escapes and enforce a size budget by default.

Preview exactly what would execute:

vcp verify accept-inviteExecution requires explicit consent and an implementation-ready task:

vcp verify accept-invite --run \

--output .vcp/evidence/accept-invite.jsonCommands run sequentially and stop after the first failure. Evidence records command, status, exit code, signal, timeout state, and duration, while raw stdout/stderr is deliberately not persisted by default.

See docs/VERIFICATION-EVIDENCE.md.

Start with examples/reference-saas-invite/ to see the workflow as concrete engineering artifacts instead of blank templates.

It models a security-sensitive multi-tenant invitation vertical slice with completed product/domain/architecture/data artifacts, ADR, threat model, test strategy, bounded task, layered code, and negative-path tests for authorization, tenant boundaries, token hashing, expiry, replay, and email binding.

cd examples/reference-saas-invite

npm test

npm run checkThe example explicitly documents what remains unproven for real production infrastructure instead of calling a demo “production-ready.”

Do not ask AI to build your project. Build a system that makes it difficult for AI to build your project incorrectly.

The human owns intent, trade-offs, architecture, risk acceptance, and final decisions. AI helps research, plan, implement, test, review, document, and automate — inside explicit constraints.

Idea

-> Product brief

-> PRD + acceptance criteria

-> User flows

-> Domain model

-> Architecture + ADRs

-> Data model

-> Threat model

-> Test strategy

-> Epics / stories / bounded tasks

-> Readiness gate

-> Plan before code

-> Bounded implementation

-> Verification evidence

-> Independent review

-> CI gates

-> Release + observability

-> Safe VCP lifecycle updates

-> Learn and update the source of truth

- AGENTS.md— repository-wide rules for coding agents.

- Product templates — product brief, PRD, user flows, acceptance criteria.

- Architecture templates — domain model, system design, data model, ADRs.

- Security template — threat modeling before implementation.

- Test strategy — unit/integration/contract/E2E decision framework.

- Delivery system — Definition of Ready, Definition of Done, task/release checklists.

- vcp task— bounded repository-native task contracts.

- vcp ready— separate plan/implementation readiness gates.

- vcp context— bounded phase-specific AI context packs.

- vcp verify— explicit execution and verification evidence.

- vcp doctor— repository/system health audit without a misleading magic score.

- vcp update— lifecycle-aware safe updates with merge/migrations/recovery.

- Agent prompts — discovery, planning, implementation, review, security, refactoring, release review.

- GitHub hygiene — issue templates, PR template, contributing guide, security policy, validation workflow.

- English README plus an Arabic guide.

- docs/product/PRODUCT-BRIEF.md

- docs/product/PRD.md

- docs/product/USER-FLOWS.md

- docs/architecture/DOMAIN.md

- docs/architecture/ARCHITECTURE.md

- docs/architecture/DATA-MODEL.md

- docs/security/THREAT-MODEL.md

- docs/testing/TEST-STRATEGY.md

Then customize AGENTS.md with real repository commands for install, format, lint, typecheck, unit/integration tests, build, and E2E.

flowchart LR

A[Select task] --> B[Read Source of Truth]

B --> C[Readiness: plan]

C --> D[Build plan context]

D --> E[Plan without editing]

E --> F[Readiness: implement]

F --> G[Implement bounded scope]

G --> H[Verification evidence]

H --> I[Self-review diff]

I --> J[Independent review]

J --> K{Quality gates pass?}

K -- No --> G

K -- Yes --> L[Merge / release / observe]

.

├── AGENTS.md

├── README.md

├── README.ar.md

├── CONTRIBUTING.md

├── SECURITY.md

├── bin/

├── lib/

├── docs/

│ ├── 00-START-HERE.md

│ ├── QUICKSTART.md

│ ├── CLI.md

│ ├── UPDATES.md

│ ├── product/

│ ├── architecture/

│ ├── security/

│ ├── testing/

│ └── delivery/

├── prompts/

├── examples/

├── scripts/

└── .github/

- Specs before implementation.

- Architecture decisions are recorded, not buried in chat history.

- No large unbounded agent tasks.

- External input is validated at trust boundaries.

- Authorization is server-side and resource-specific.

- Schema changes use reviewed migrations and rollback thinking.

- Tests are added with behavior, not postponed to the end.

- The builder is not the only reviewer.

- CI is the mechanical source of truth when CI is available.

- Production must be observable and recoverable.

- Lifecycle upgrades are planned and reversible; templates are not blindly recopied.

A good agent task normally has:

- one primary outcome;

- a narrow set of affected modules;

- explicit acceptance criteria;

- known tests;

- no unrelated refactor;

- a diff small enough for a human to understand.

If a task requires a long explanation of “and while you're there…”, split it.

The kit intentionally avoids locking you into one AI vendor. Keep universal rules in AGENTS.md, and add tool-specific instruction files only when they provide real value.

Do not duplicate conflicting rules across multiple agent configuration files. Prefer one source of truth and thin adapters.

- CLI bootstrap with evidence-based TypeScript/Python/Go profiles

- Context-aware task pack generator

- Two-stage task readiness gate

- Phase-specific bounded context packs

- Safe verification evidence workflow

- Read-only doctoraudit

- Worked reference vertical slice

- Versioned lifecycle state and safe vcp update

- Three-way merge, migrations, locking, backup, rollback, and manage ignore/track

- Mobile stack profiles

- Monorepo-aware stack/CI profiles

- Security profiles for common application classes

- Git-aware review/release automation

- Prompt evaluation suite for coding agents

- Architecture fitness-function examples

- Extensible community profile/plugin system

See CONTRIBUTING.md if you want to help.

MIT — use it in personal, commercial, and open-source projects.