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Empowers Google Antigravity, Cursor, Copilot & Claude with 54 specialized agents, 69+ skills, Semantic AST Memory, and MCP native tools โ zero external API keys required.","maintainers":[{"name":"aswini_behera","email":"aswinibehera666@gmail.com"}],"readme":"# ๐ญ Agent-Kit (V3.6) โ The Hybrid AI Arsenal\n\n> \n> \n\n## The Ultimate MCP Server that supercharges Google Antigravity, Cursor, Claude Desktop, and Windsurf\n\n> _You are a CTO with 54 autonomous AI employees acting as a native extension to your IDE._\n\n[](https://www.npmjs.com/package/@ab_aswini/agent-kit-p1) [](https://github.com/Ab-aswini/Agent-kit-P1) [](https://www.npmjs.com/package/@ab_aswini/agent-kit-p1) [](LICENSE) [](https://github.com/Ab-aswini/Agent-kit-P1)\n\n```text\nโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ\nโ โ\nโ โก npx @ab_aswini/agent-kit-p1 init โ\nโ โ\nโ โณ That's it. Your 54-agent AI company is now deployed. โ\nโ โ\nโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ\n```\n\n## ๐ Table of Contents\n\n| # | Section | What You'll Learn |\n| :-: | :------------------------------------------------------------- | :---------------------------------------------------- |\n| 1 | [๐งฉ What Is Agent-Kit?](#-what-is-agent-kit) | The big picture โ why this exists |\n| 2 | [๐ก The Problem We Solve](#-the-problem-we-solve) | The pain point and how we fix it |\n| 3 | [๐๏ธ How It Works โ Architecture](#๏ธ-how-it-works--architecture) | The governance model, layers, and control flow |\n| 4 | [๐ฅ Meet Your Team โ 54 Agents](#-meet-your-team--54-agents) | Every department, every agent, every role |\n| 5 | [๐จ UI&UX Intelligence Engine](#-uiux-intelligence-engine) | The built-in design brain with 18 domains & 16 stacks |\n| 6 | [๐ฆ The Iron Well Protocol](#-the-iron-well-protocol) | How governance actually works step-by-step |\n| 7 | [โก Install & Setup](#-install--setup) | Every way to install + first steps |\n| 8 | [๐ฏ Company Archetypes](#-company-archetypes) | Choose your team size from 14 to 54 agents |\n| 9 | [โ๏ธ Tech Stack](#๏ธ-tech-stack) | What's under the hood |\n| 10 | [๐ก๏ธ Security & Privacy](#๏ธ-security--privacy) | How safety is enforced at every layer |\n| 11 | [๐ข Deployment Pipeline](#-deployment-pipeline) | From your IDE to NPM to the end user |\n| 12 | [๐บ๏ธ Roadmap](#๏ธ-roadmap) | What's coming next |\n| 13 | [๐ค Contributing](#-contributing) | How to add agents, skills, or datasets |\n| 14 | [๐ License](#-license) | MIT โ fully open |\n\n---\n\n## ๐งฉ What Is Agent-Kit?\n\n**Agent-Kit is an NPM package that turns any project directory into an AI-powered software company.**\n\nWhen you run `npx @ab_aswini/agent-kit-p1 init`, it creates a **zero-footprint** global store and drops a single `.agentkit` pointer file in your project. The global store contains:\n\n```text\nyour-project/\nโโโ .agent-os/ โ The AI Operating System\nโ โโโ agents/ โ 54 AI agent definitions (.md files)\nโ โ โโโ tier-1/ โ Executive council (CTS, SFS, SP, RC)\nโ โ โโโ engineering/ โ Backend, Frontend, Database, Mobile, Game\nโ โ โโโ qa/ โ Testing, coverage, regression\nโ โ โโโ security/ โ Threat modeling, pen testing\nโ โ โโโ product/ โ PRDs, UX research, README architect\nโ โ โโโ devops/ โ CI/CD, Docker, monitoring\nโ โ โโโ intelligence/ โ Legacy archaeology, research\nโ โ โโโ marketing-growth/ โ SEO/GEO, brand authority\nโ โ โโโ meta/ โ Memory, loops, permissions\nโ โ\nโ โโโ skills/ โ 69+ reusable skill modules\nโ โ โโโ clean-code/ โ Code quality standards\nโ โ โโโ api-patterns/ โ REST/GraphQL conventions\nโ โ โโโ database-design/ โ Schema, migration patterns\nโ โ โโโ page-cro/ โ Conversion Rate Optimization\nโ โ โโโ schema-markup/ โ SEO JSON-LD implementation\nโ โ โโโ testing-patterns/ โ TDD, pyramid, coverage\nโ โ โโโ ... 63 more (Including 25 Advanced Marketing Skills)\nโ โ\nโ โโโ .shared/\nโ โ โโโ UI&UX/ โ Design intelligence engine\nโ โ โโโ data/ โ 18 domain CSVs (styles, colors, etc.)\nโ โ โ โโโ stacks/ โ 16 framework-specific CSVs\nโ โ โโโ scripts/ โ BM25 search engine + design generator\nโ โ\nโ โโโ workflows/ โ 19 pre-built SOPs (create, debug, deploy...)\nโ โโโ rules/ โ Universal rules, Socratic Gate, GEMINI config\nโ โโโ templates/ โ 12 company archetype configurations\nโ โโโ hub-logic.md โ Central intelligence hub\nโ โโโ manifest.json โ Master registry of all 54 agents\nโ\nโโโ scripts/ โ Automation scripts\nโ โโโ checklist.py โ 360ยฐ project health audit\nโ โโโ spawn_agent.py โ Generate system prompts for any agent\nโ โโโ security_chaos_test.py โ Simulated attack testing\nโ โโโ sync_api_contracts.py โ Backend-frontend contract alignment\nโ\nโโโ memory/ โ Persistent context across sessions\nโ โโโ global/ โ Architecture, decisions, conventions\nโ โโโ backend/ โ Backend-specific context\nโ โโโ frontend/ โ Frontend-specific context\nโ โโโ product/ โ Product-specific context\nโ\nโโโ bin/cli.js โ CLI entry point\n```\n\n**Every `.md` file is an agent definition** โ a detailed protocol document that tells your AI IDE (whether you use **Google Antigravity**, **Cursor**, **VS Code + GitHub Copilot**, **Windsurf**, or **Claude Desktop**) exactly how to behave for a specific role. When you tell your AI assistant to \"read the backend specialist agent\", it loads that agent's rules, boundaries, skills, and decision frameworks.\n\n**๐ V3.6 Features: Native MCP Server + Self-Test + Multi-Model**\nAgent-Kit now runs natively as a **Model Context Protocol (MCP)** server with **6 tools**: `list_agents`, `get_agent_prompt`, `query_ui_ux_engine`, `run_memory_sync`, `run_checklist`, and `run_security_chaos`. It also ships with a `self-test` command to run all diagnostics, supports `AGENT_KIT_MODEL` env var for multi-model routing, and logs all agent actions.\n\n> [!IMPORTANT]\n> **The Supportive Office Philosophy**: Agent-Kit does **not** require external LLM APIs (no OpenAI/Anthropic keys needed). It acts as a **Supportive Office** for your IDE's native AI (Copilot, Gemini, Claude). You provide the built-in IDE LLM; Agent-Kit provides the company structure, the rules, the memory, and the tools so the LLM can complete the work smarter.\n\n---\n\n## ๐ก The Problem We Solve\n\nBuilding production software requires coordinated expertise across many domains:\n\n```mermaid\n%%{init: {'theme': 'default'}}%%\n\nflowchart LR\n subgraph NEED[\"What Production Software Needs\"]\n direction TB\n A[\"๐๏ธ Architecture\"]\n B[\"๐ง Backend APIs\"]\n C[\"๐จ Frontend UI\"]\n D[\"๐๏ธ Database Design\"]\n E[\"๐งช Testing & QA\"]\n F[\"๐ก๏ธ Security Audit\"]\n G[\"๐ฏ Product Strategy\"]\n H[\"๐ DevOps & CI/CD\"]\n I[\"๐ฑ Mobile Development\"]\n J[\"๐ข SEO & Marketing\"]\n end\n\n subgraph WITHOUT[\"Without Agent-Kit\"]\n direction TB\n X[\"๐ฐ One dev doing everything\"]\n Y[\"๐ธ Hire 10+ specialists\"]\n Z[\"๐ Gaps in coverage\"]\n end\n\n subgraph WITH[\"With Agent-Kit\"]\n direction TB\n W[\"๐ญ 54 AI specialists\"]\n V[\"๐ก๏ธ Governed by Iron Well\"]\n U[\"โก Zero hiring cost\"]\n end\n\n NEED --> WITHOUT\n NEED --> WITH\n\n style X fill:#EF4444,stroke:#DC2626,color:#fff,stroke-width:2px\n style Y fill:#EF4444,stroke:#DC2626,color:#fff,stroke-width:2px\n style Z fill:#EF4444,stroke:#DC2626,color:#fff,stroke-width:2px\n style W fill:#10B981,stroke:#047857,color:#fff,stroke-width:2px\n style V fill:#10B981,stroke:#047857,color:#fff,stroke-width:2px\n style U fill:#10B981,stroke:#047857,color:#fff,stroke-width:2px\n```\n\n**The typical solo developer** writes code, tests improperly, skips security audits, struggles with UX, and deploys with crossed fingers.\n\n**Agent-Kit gives you a full company:**\n\n| Role | Agent | What It Actually Does |\n| :------------------ | :--------- | :----------------------------------------------------------------- |\n| CTO | CTS-001 | Reviews every decision, enforces architecture, has merge authority |\n| Lead Developer | SFS-001 | Orchestrates multi-file tasks, routes work to specialists |\n| Strategist | SP-001 | Creates milestone plans before any code is written |\n| Risk Officer | RC-001 | Flags compliance issues, evaluates trade-offs |\n| 10 Backend Devs | BE-001โ010 | API design, auth, microservices, caching, queues |\n| 9 Frontend Devs | FE-001โ009 | Components, state management, animations, a11y, asset architecture |\n| 5 DB Engineers | DB-001โ005 | Schema design, migrations, query optimization |\n| 6 QA Engineers | QA-001โ006 | Unit tests, integration, E2E, regression |\n| Security Specialist | SEC-001 | OWASP compliance, vulnerability scanning |\n| 6 DevOps Engineers | DO-001โ006 | Docker, CI/CD, monitoring, deployment |\n| Product Manager | PM-001 | PRDs, user stories, acceptance criteria |\n| UX Researcher | PM-002 | Usability analysis, design patterns |\n| README Architect | RA-001 | Documentation generation (that's me!) |\n| SEO+AEO Specialist | MKT-001 | SERAPH: Technical SEO, schema markup, AEO, search submission |\n| Intel Agent | INTEL-001 | Legacy code analysis, deep research |\n| 4 Meta Agents | MM-001โ004 | Memory management, loop detection, permissions |\n\n---\n\n## ๐๏ธ How It Works โ Architecture\n\n### The Governance Model\n\nAgent-Kit uses a **military-style chain of command** called the **Iron Well Protocol**. No agent can go rogue โ every action flows through approval gates.\n\n```mermaid\n%%{init: {'theme': 'default'}}%%\n\ngraph TD\n subgraph HUMAN[\"๐งโ๐ป YOU โ THE OWNER\"]\n H((\"๐ค Developer\"))\n end\n\n subgraph EXECUTIVE[\"๐๏ธ TIER 1 โ EXECUTIVE COUNCIL\"]\n SFS[\"๐ฏ SFS-001 (Orchestrator)\"]\n CTS[\"๐ CTS-001 (Supervisor)\"]\n SP[\"๐ SP-001 (Planner)\"]\n RC[\"โ๏ธ RC-001 (Risk & Compliance)\"]\n end\n\n subgraph DEPARTMENTS[\"โก TIER 2 โ 9 SPECIALIZED DEPARTMENTS\"]\n direction LR\n ENG[\"๐ง Engineering (26)\"]\n QA[\"๐งช QA (6)\"]\n SEC[\"๐ก๏ธ Security (1)\"]\n PROD[\"๐ฆ Product (5)\"]\n DX[\"๐ DevOps (6)\"]\n INTEL[\"๐ Intel (1)\"]\n MKT[\"๐ข Marketing (1)\"]\n end\n\n subgraph META[\"๐ง TIER 3 โ META-MANAGEMENT\"]\n MM[\"๐ง Memory + Loops + Permissions\"]\n end\n\n subgraph INTELLIGENCE[\"๐จ SHARED INTELLIGENCE LAYER\"]\n UX[\"๐จ UI&UX Engine\"]\n end\n\n H -->|\"๐ You give a task\"| SFS\n SFS -->|\"๐ฆ Socratic Gate:
3 strategic questions\"| H\n H -->|\"โ
You answer\"| SFS\n SFS -->|\"๐ Creates plan\"| SP\n SP -->|\"๐ milestones.md\"| SFS\n SFS -->|\"๐ค Delegates to specialists\"| DEPARTMENTS\n DEPARTMENTS -->|\"๐งช Submit for review\"| QA\n QA -->|\"โ๏ธ Approval\"| CTS\n CTS -->|\"๐ Final delivery\"| H\n\n META -.->|\"๐ Context sync\"| DEPARTMENTS\n INTELLIGENCE -.->|\"๐จ Design data\"| DEPARTMENTS\n\n style H fill:#10B981,stroke:#047857,stroke-width:3px,color:#fff\n style SFS fill:#7C3AED,stroke:#5B21B6,stroke-width:2px,color:#fff\n style CTS fill:#7C3AED,stroke:#5B21B6,stroke-width:2px,color:#fff\n style SP fill:#8B5CF6,stroke:#6D28D9,stroke-width:2px,color:#fff\n style RC fill:#8B5CF6,stroke:#6D28D9,stroke-width:2px,color:#fff\n style ENG fill:#2563EB,stroke:#1D4ED8,stroke-width:2px,color:#fff\n style QA fill:#06B6D4,stroke:#0891B2,stroke-width:2px,color:#fff\n style SEC fill:#EF4444,stroke:#DC2626,stroke-width:2px,color:#fff\n style PROD fill:#F59E0B,stroke:#D97706,stroke-width:2px,color:#000\n style DX fill:#EC4899,stroke:#DB2777,stroke-width:2px,color:#fff\n style INTEL fill:#14B8A6,stroke:#0D9488,stroke-width:2px,color:#fff\n style MKT fill:#F97316,stroke:#EA580C,stroke-width:2px,color:#fff\n style MM fill:#6366F1,stroke:#4F46E5,stroke-width:2px,color:#fff\n style UX fill:#F59E0B,stroke:#D97706,stroke-width:3px,color:#000\n```\n\n### The Anti-Hallucination Protocol (The 4 Core Constraints)\n\nTo ensure Agent-Kit operates with zero hallucinations and grounded intelligence, all 54 agents rigidly adhere to the **4 Core Constraints** (enforced globally in `universal-rules.agent.md`):\n\n1. **RAG (Retrieval-Augmented Generation)**: Dynamic connection to project docs, databases, and APIs.\n2. **Source Grounding**: Every answer must be tied to a documented source. Absolute rule: \"If no reliable source exists, I don't have enough information to answer.\"\n3. **Confidence Thresholds**: If confidence is low, agents abstain and ask clarifying questions instead of guessing.\n4. **Post-Response Validation**: Self-correction checks for factual errors, rule violations, format issues, and safety before returning the final plan or code.\n\n### The Four Layers\n\nEvery component in Agent-Kit lives in one of four layers:\n\n```mermaid\n%%{init: {'theme': 'default'}}%%\n\ngraph TD\n subgraph L4[\"๐ฅ๏ธ LAYER 4 โ INTERFACE (How You Interact)\"]\n CLI[\"โจ๏ธ CLI Commands\"]\n IDE[\"๐ป AI IDE (Cursor / Windsurf)\"]\n NPX[\"๐ฆ NPX/NPM\"]\n end\n\n subgraph L3[\"๐๏ธ LAYER 3 โ ORCHESTRATION (How Agents Coordinate)\"]\n GATE[\"๐ฆ Socratic Gate\"]\n PHASE[\"โก 2-Phase Engine\"]\n GOV[\"๐ Tiered Authority\"]\n WF[\"๐ 19 Workflows\"]\n end\n\n subgraph L2[\"๐ง LAYER 2 โ INTELLIGENCE (How Agents Think)\"]\n BM25[\"๐ BM25 Search Engine\"]\n DSG[\"๐จ Design System Generator\"]\n REASON[\"๐ก Reasoning Engine\"]\n SPAWN[\"๐ค Agent Spawner\"]\n end\n\n subgraph L1[\"๐พ LAYER 1 โ DATA (What Agents Know)\"]\n AGENTS[\"๐ 54 Agent Protocols\"]\n SKILLS[\"๐งฉ 69+ Skill Modules\"]\n CSV[\"๐ 34 CSV Datasets\"]\n MEM[\"๐ง Memory Hubs\"]\n end\n\n L4 --> L3\n L3 --> L2\n L2 --> L1\n\n style CLI fill:#7C3AED,stroke:#5B21B6,stroke-width:2px,color:#fff\n style IDE fill:#8B5CF6,stroke:#6D28D9,stroke-width:2px,color:#fff\n style NPX fill:#A78BFA,stroke:#7C3AED,stroke-width:2px,color:#fff\n style GATE fill:#EF4444,stroke:#DC2626,stroke-width:2px,color:#fff\n style PHASE fill:#EC4899,stroke:#DB2777,stroke-width:2px,color:#fff\n style GOV fill:#F43F5E,stroke:#E11D48,stroke-width:2px,color:#fff\n style WF fill:#FB7185,stroke:#F43F5E,stroke-width:2px,color:#fff\n style BM25 fill:#F59E0B,stroke:#D97706,stroke-width:2px,color:#000\n style DSG fill:#F97316,stroke:#EA580C,stroke-width:2px,color:#fff\n style REASON fill:#FBBF24,stroke:#F59E0B,stroke-width:2px,color:#000\n style SPAWN fill:#FCD34D,stroke:#FBBF24,stroke-width:2px,color:#000\n style AGENTS fill:#10B981,stroke:#047857,stroke-width:2px,color:#fff\n style SKILLS fill:#06B6D4,stroke:#0891B2,stroke-width:2px,color:#fff\n style CSV fill:#14B8A6,stroke:#0D9488,stroke-width:2px,color:#fff\n style MEM fill:#2DD4BF,stroke:#14B8A6,stroke-width:2px,color:#000\n```\n\n---\n\n## ๐ฅ Meet Your Team โ 54 Agents\n\n### Executive Council (Tier 1)\n\nThese four agents govern everything. They are loaded first, always active, and have the highest authority.\n\n| Agent | ID | Authority | Core Responsibility |\n| :--------------------------------- | :------ | :-------- | :--------------------------------------------------------------------------------------------- |\n| ๐ **Chief Technical Supervisor** | CTS-001 | Highest | Architecture authority, merge control, final approval on all deployments and DB changes |\n| ๐ฏ **Senior Full Stack Developer** | SFS-001 | High | Primary orchestrator โ routes all tasks, activates the Socratic Gate, delegates to departments |\n| ๐ **Strategy Planner** | SP-001 | High | Creates milestone plans, defines task breakdowns, manages the 4-phase planning methodology |\n| โ๏ธ **Risk & Compliance** | RC-001 | High | Evaluates risks, flags compliance issues, assesses cost/benefit trade-offs |\n\n### Engineering Department (26 Agents)\n\n| Sub-Division | Agents | ID Range | What They Build |\n| :-------------- | :----: | :--------- | :------------------------------------------------------------------------------------------------------------------------ |\n| ๐ง **Backend** | 10 | BE-001โ010 | REST/GraphQL APIs, authentication (JWT, OAuth), microservices, caching, message queues, middleware |\n| ๐จ **Frontend** | 9 | FE-001โ009 | React/Next.js/Vue components, state management, routing, responsive design, animations, accessibility, asset architecture |\n| ๐๏ธ **Database** | 5 | DB-001โ005 | Schema design, Prisma/TypeORM migrations, query optimization, indexing, data modeling |\n| ๐ฑ **Mobile** | 1 | MOB-001 | React Native, Flutter, platform-native iOS/Android |\n| ๐ฎ **Game** | 1 | GAME-001 | Game mechanics, physics engines, cross-platform game development |\n\n### Support Departments\n\n| Department | Lead | Agents | Focus |\n| :----------------------- | :-------- | :----: | :----------------------------------------------------------------------------------------------- |\n| ๐งช **QA & Verification** | QA-001 | 6 | Unit tests (Jest, Pytest), integration tests, E2E (Playwright), regression, code coverage audits |\n| ๐ก๏ธ **Security** | SEC-001 | 1 | OWASP Top 10 scanning, dependency auditing, threat modeling, shift-left security practices |\n| ๐ฆ **Product & Docs** | PM-001 | 5 | PRDs, user stories, acceptance criteria, UX research, README generation |\n| ๐ **DevOps** | DO-001 | 6 | Docker containerization, CI/CD pipelines, cloud deployment, monitoring, infrastructure-as-code |\n| ๐ **Intelligence** | INTEL-001 | 1 | Legacy codebase archaeology, deep technical research, knowledge extraction |\n| ๐ข **Marketing** | MKT-001 | 1 | SERAPH: Technical SEO, schema markup, AEO, search engine submission |\n| ๐ง **Meta-Management** | MM-001 | 4 | Memory file management, infinite loop detection, permission boundary enforcement |\n\n---\n\n## ๐จ UI&UX Intelligence Engine\n\nThe **UI&UX Engine** is Agent-Kit's built-in design brain. It's a Python-powered intelligence layer that gives every agent instant access to **600,000+ data points** of structured design knowledge.\n\n### How It Works\n\nWhen any agent needs design guidance (colors, typography, layout, component patterns, accessibility, dark mode), it queries the UI&UX Engine:\n\n```mermaid\n%%{init: {'theme': 'default'}}%%\n\nflowchart TD\n Q[\"๐ Agent asks: SaaS dashboard...\"] --> DD[\"๐งญ Domain Detector\"]\n DD --> BM[\"โก BM25 Search Engine\"]\n BM --> D1[\"๐ 18 Domain CSVs\"]\n BM --> D2[\"๐ฆ 16 Stack CSVs\"]\n D1 --> DSG[\"๐จ Design System Generator\"]\n D2 --> DSG\n DSG --> OUT[\"โ
Complete Design System Output\"]\n\n style Q fill:#7C3AED,stroke:#5B21B6,stroke-width:2px,color:#fff\n style DD fill:#2563EB,stroke:#1D4ED8,stroke-width:2px,color:#fff\n style BM fill:#06B6D4,stroke:#0891B2,stroke-width:2px,color:#fff\n style D1 fill:#EC4899,stroke:#DB2777,stroke-width:2px,color:#fff\n style D2 fill:#F97316,stroke:#EA580C,stroke-width:2px,color:#fff\n style DSG fill:#F59E0B,stroke:#D97706,stroke-width:3px,color:#000\n style OUT fill:#10B981,stroke:#047857,stroke-width:3px,color:#fff\n```\n\n### The 18 Search Domains\n\nEvery design question maps to one or more of these knowledge bases:\n\n> ### 18 Search Domains\n>\n> 1. ๐ญ **Styles** (1,000+) - CSS patterns, layout systems, spacing scales, shadows, borders\n> 2. ๐จ **Colors** (1,200+) - Color palettes, contrast ratios, semantic color systems, brand guidelines\n> 3. ๐ค **Typography** (800+) - Font stacks, type scales, line heights, responsive typography\n> 4. ๐ **Landing Pages** (2,400+) - Hero sections, CTAs, social proof patterns, conversion layouts\n> 5. ๐๏ธ **Products** (1,500+) - Product cards, galleries, filtering patterns, cart UX\n> 6. ๐ **Charts** (400+) - Data visualization, chart types, color coding for data\n> 7. โจ **Icons** (2,000+) - Icon systems, sizing conventions, accessibility for icons\n> 8. ๐งฉ **UX Guidelines** (700+) - Interaction patterns, micro-interactions, user flow best practices\n> 9. ๐ **Web Interfaces** (500+) - Navigation, sidebars, modals, toast notifications\n> 10. โ๏ธ **React Performance** (800+) - Memoization, lazy loading, virtual lists, bundle optimization\n> 11. ๐ฌ **Prompts** (1,800+) - AI prompt templates for design decisions\n> 12. ๐ก **UI Reasoning** (1,200+) - Why certain designs work โ backed by data\n> 13. ๐ฌ **Animations** (500+) - Transition curves, duration guidelines, motion principles\n> 14. โฟ **Accessibility** (600+) - WCAG 2.1, ARIA patterns, screen reader support\n> 15. ๐ **Dark Mode** (400+) - Dark theme strategies, color inversion rules, contrast in dark\n> 16. ๐ค **AI Patterns** (400+) - AI-native UI components, chat interfaces, loading states\n> 17. ๐ **Forms** (500+) - Form validation UX, multi-step wizards, input patterns\n> 18. โ ๏ธ **Error States** (400+) - Error messages, empty states, fallback UI, retry patterns\n\n### The 16 Framework Stacks\n\nFramework-specific guidance with 15-column schema including **2026-ready columns:**\n\n> ### 16 Framework Stacks & Data Schema\n>\n> **Stack Includes:** โ๏ธ React, โฒ Next.js, ๐ Vue, ๐ Nuxt, ๐ฅ Svelte, ๐
ฐ๏ธ Angular, ๐ Astro, ๐ฟ Remix, ๐ฆ Tauri, ๐ Flutter, ๐ SwiftUI, ๐ฑ React Native, ๐ค Jetpack Compose, ๐งฉ shadcn, ๐ Tailwind, ๐ Nuxt UI\n>\n> **Columns Include:** `Component_Name`, `Category`, `Use_Case`, `Code_Example`, `Accessibility_Score`, `Dark_Mode_Strategy`, `AI_Integration_Level`, `Privacy_Tier`, `Agent_Readiness`, `Performance_Budget`\n>\n> [!NOTE]\n> **2026 Columns Explained:**\n>\n> - `Dark_Mode_Strategy` โ How to implement dark mode for each component\n> - `AI_Integration_Level` โ How AI-ready the component is (chat, voice, generative)\n> - `Privacy_Tier` โ GDPR/CCPA/HIPAA compliance tier\n> - `Agent_Readiness` โ Whether the component works with AI agent workflows\n> - `Performance_Budget` โ Max acceptable load time / bundle size\n\n---\n\n## ๐ฆ The Iron Well Protocol\n\nThis is the governance system that prevents chaos. Every complex task goes through this exact flow:\n\n```mermaid\n%%{init: {'theme': 'default'}}%%\n\nsequenceDiagram\n autonumber\n actor Dev as ๐งโ๐ป You (Developer)\n participant SFS as ๐ฏ SFS-001
Orchestrator\n participant GATE as ๐ฆ Socratic Gate\n participant SP as ๐ SP-001
Planner\n participant ENG as ๐ง Engineering
Agent(s)\n participant UX as ๐จ UI&UX Engine\n participant QA as ๐งช QA Agent(s)\n participant CTS as ๐ CTS-001
Supervisor\n\n Dev->>SFS: \"Build a user dashboard with real-time analytics\"\n\n Note over SFS,GATE: PHASE 0 โ SOCRATIC GATE (Mandatory)\n SFS->>Dev: Question 1: What data sources feed the dashboard?\n Dev->>SFS: PostgreSQL + WebSocket events\n SFS->>Dev: Question 2: Who are the users โ admins or end users?\n Dev->>SFS: Admin users only, internal tool\n SFS->>Dev: Question 3: Any compliance constraints?\n Dev->>SFS: SOC 2 โ no PII displayed\n\n Note over SFS,SP: PHASE 1 โ PLANNING (No Code Allowed)\n SFS->>SP: Create milestone plan\n SP-->>SFS: milestones.md with task breakdown\n SFS->>Dev: Here is the plan โ approve?\n Dev->>SFS: โ
Approved with one change\n SFS->>SP: Update plan\n SP-->>SFS: Updated milestones.md\n\n Note over SFS,QA: PHASE 2 โ EXECUTION (Code Allowed)\n SFS->>ENG: Execute: Build dashboard API\n ENG->>UX: Need design system for admin dashboard\n UX-->>ENG: Color palette + typography + component patterns\n ENG->>ENG: Implementing API + frontend + tests\n ENG->>QA: Ready for review\n\n Note over QA,CTS: VERIFICATION\n QA->>QA: Run checklist.py audit\n QA-->>CTS: All checks passed โ
\n CTS->>Dev: ๐ Dashboard delivered โ ready for deployment\n```\n\n### What the Socratic Gate Actually Does\n\nThe Socratic Gate is **not optional**. For any complex request (build, create, implement, refactor), the AI must ask **at least 3 strategic questions** before writing a single line of code.\n\n| Question Type | Purpose | Example |\n| :-------------- | :----------------------------- | :-------------------------------------------------------------- |\n| **Scope** | Prevent scope creep | \"Should this dashboard also handle reporting export?\" |\n| **Users** | Clarify audience | \"Is this for technical admins or business stakeholders?\" |\n| **Constraints** | Surface hidden requirements | \"Any regulatory compliance? GDPR? SOC 2?\" |\n| **Trade-offs** | Explore alternatives | \"Real-time via WebSockets or polling every 30s?\" |\n| **Edge Cases** | Prevent bugs before they exist | \"What happens when the data source is temporarily unavailable?\" |\n\n> [!TIP]\n> **Why this matters:** Most AI coding tools just start building. Agent-Kit forces clarity first. The result: fewer rewrites, no misunderstandings, and production-quality output from the start.\n\n---\n\n## โก Install & Setup\n\n### Method 1: Quick Start (Recommended)\n\nThe fastest way โ one command, zero configuration:\n\n```bash\nnpx @ab_aswini/agent-kit-p1 init\n```\n\nThis scaffolds the complete agent system into a **zero-footprint global store** โ only a `.agentkit` pointer file touches your project. All 54 agents, 42+ skills, 19 workflows, and the UI&UX engine are deployed.\n\nThis is the core of the V3.6 **Hybrid Arsenal** philosophy. Agent-Kit does not try to be an LLM IDE; instead, it is the ultimate super-weapon _for_ your IDE.\n\nBy running the MCP server, you give Cursor/Claude access to Agent-Kit's powerful internal Python tools:\n\n- `list_agents` / `get_agent_prompt` โ Query and generate system prompts for any of 54 agents\n- `run_checklist` โ Cursor can natively trigger `checklist.py` to ensure your project complies with Iron Well architecture standards\n- `run_security_chaos` โ Cursor can trigger the Security Chaos Monkey to scan for exposed secrets and risky patterns\n- `query_ui_ux_engine` โ Cursor can query the internal BM25 search engine to pull complete, enterprise-grade Design Systems\n- `run_memory_sync` โ Auto-generate `architecture.md`, `api-contracts.md`, `dependencies.md`\n\n**The Workflow:**\nYou tell Cursor: _\"Audit my project using Agent-Kit.\"_\nCursor hits our MCP server โ Agent-Kit runs the Python audit on your local files โ Cursor reads the output and fixes the code for you.\n\n### Method 2: Dev Dependency\n\n```bash\nnpm install --save-dev @ab_aswini/agent-kit-p1\n\n```\n\nThen add a setup script:\n\n```json\n{\n \"scripts\": {\n \"setup:agents\": \"agent-kit init\",\n \"health\": \"agent-kit doctor\"\n }\n}\n```\n\n### Method 3: Interactive Mode (Choose Your Team)\n\nDon't need all 54 agents? Pick a company archetype:\n\n```bash\nnpx @ab_aswini/agent-kit-p1 init --interactive\n```\n\nThis walks you through an interactive menu to select your project type (SaaS, Mobile, E-commerce, etc.) and deploys only the agents you need.\n\n### Method 4: Add to package.json\n\n```bash\nnpm install --save-dev @ab_aswini/agent-kit-p1\n```\n\nThen add a setup script:\n\n```json\n{\n \"scripts\": {\n \"setup:agents\": \"agent-kit init\",\n \"health\": \"agent-kit doctor\"\n }\n}\n```\n\n### ๐ Method 5: Native MCP Server (Google Antigravity / Cursor / Claude)\n\nAgent-Kit can run as a **Model Context Protocol (MCP)** server, securely attaching all 54 agents directly to your IDE.\n\n**For Google Antigravity & Cursor:** Add this to your MCP Settings:\n\n- Name: `Agent-Kit`\n- Type: `command`\n- Command: `npx @ab_aswini/agent-kit-p1 mcp`\n\n**For Claude Desktop:** Add to your `claude_desktop_config.json`:\n\n```json\n{\n \"mcpServers\": {\n \"agent-kit\": {\n \"command\": \"npx\",\n \"args\": [\"@ab_aswini/agent-kit-p1\", \"mcp\"]\n }\n }\n}\n```\n\n_Tools exposed natively to your AI:_ `list_agents`, `get_agent_prompt`, `query_ui_ux_engine`, `run_memory_sync`, `run_checklist`, `run_security_chaos`.\n\n### ๐ฉบ Health Check\n\nAfter installation, verify everything is in place:\n\n```bash\nnpx @ab_aswini/agent-kit-p1 doctor\n```\n\nThis validates: agent files exist, directory structure is correct, manifest is consistent, and skills are properly linked.\n\n### ๐ฌ First Steps After Install\n\n| Step | Command / Action | What Happens |\n| :--: | :----------------------------------------------------------------------------------- | :--------------------------------------------------------------------- |\n| 1 | Open project in **Google Antigravity / Cursor / Windsurf** | Your AI IDE is ready |\n| 2 | Tell your AI: _\"Read `.agent-os/agents/tier-1/chief-technical-supervisor.agent.md`\"_ | CTS-001 activates as your technical authority |\n| 3 | Run `python scripts/checklist.py` | Validates full project health |\n| 4 | Run `python scripts/spawn_agent.py BE-001` | Generates a ready-to-paste system prompt for Backend Agent 001 |\n| 5 | Start building | Tell your AI what to build โ the Socratic Gate activates automatically |\n\n### ๐ Full CLI Reference\n\n| Command | Description |\n| :--------------------------------------------------- | :-------------------------------------------------------------------------------------------------------------- |\n| `agent-kit init` | Deploy all 54 agents, skills, workflows, and UI&UX engine |\n| `agent-kit init -i` / `agent-kit init --interactive` | Interactive archetype selection (choose your team size) |\n| `agent-kit doctor` | Validate system health and flag missing components |\n| `agent-kit clean` | Remove legacy zero-footprint migration artifacts |\n| `agent-kit chat` | Launch the interactive Command-Trigger REPL |\n| `agent-kit run \"prompt\"` | **[V3.5]** Execute a task via the orchestration engine with action logging |\n| `agent-kit sync` | **[V3]** Run a one-shot Semantic Memory Sync โ updates `architecture.md`, `api-contracts.md`, `dependencies.md` |\n| `agent-kit sync --watch` | **[V3]** Watch mode โ auto-re-syncs agent memory every 5s when project files change |\n| `agent-kit self-test` | **[V3.5]** Run all 3 diagnostics (memory sync + security chaos + health check) with unified report |\n| `agent-kit mcp` | **[V3]** Start the Model Context Protocol (MCP) server for native Cursor / Claude Desktop integration |\n\n### ๐ฌ Command-Trigger REPL (Slash Commands)\n\nRun `npx @ab_aswini/agent-kit-p1 chat` to open an interactive session. You can type natural language or use slash commands to instantly route context to specialized agents:\n\n| Command | Agent Triggered | Core Responsibility |\n| :---------- | :-------------- | :------------------------------------------------------------------------------------------------- |\n| `/help` | _System_ | List available commands |\n| `/fix` | QA-001 | Analyzes errors/code for logical flaws and proposes precise fixes |\n| `/test` | QA-001 | Writes comprehensive, edge-case resilient unit/integration tests |\n| `/refactor` | BE-001 | Optimizes code for efficiency, readability, and SOLID principles |\n| `/plan` | SP-001 | Decomposes a request into a granular, step-by-step milestone plan |\n| `/seo` | MKT-001 | **[V3.5]** Triggers SERAPH SEO+AEO agent for technical SEO, schema markup, and search optimization |\n| _(default)_ | SFS-001 | Standard orchestrator routing for general inquiries |\n\n> [!IMPORTANT]\n> **Requirements:** Node.js 16+ and npm 7+. Python 3.8+ is needed for the UI&UX engine and audit scripts.\n\n---\n\n## ๐ฏ Company Archetypes\n\nWhen you run `agent-kit init --interactive`, you choose from **12 pre-configured company archetypes**. Each archetype deploys a curated subset of agents, skills, and departments tailored to your project type.\n\n```mermaid\n%%{init: {'theme': 'default'}}%%\n\nflowchart TD\n START((\"๐๏ธ Choose Your Company\")) --> S[\"๐ SaaS Startup (44)\"]\n START --> M[\"๐ฑ Mobile App (26)\"]\n START --> EC[\"๐ E-commerce (45)\"]\n START --> P[\"๐ผ๏ธ Portfolio (14)\"]\n START --> D[\"๐ Dashboard (29)\"]\n START --> B[\"๐ Blog / CMS (21)\"]\n START --> ED[\"๐ EdTech (32)\"]\n START --> HC[\"๐ฅ Healthcare (40)\"]\n START --> MP[\"๐ช Marketplace (47)\"]\n START --> AI[\"๐ค AI / ChatBot (30)\"]\n START --> G[\"๐ฎ Gaming (23)\"]\n START --> API[\"โ๏ธ API-First (33)\"]\n\n style START fill:#7C3AED,stroke:#5B21B6,stroke-width:3px,color:#fff\n style S fill:#2563EB,stroke:#1D4ED8,stroke-width:2px,color:#fff\n style M fill:#EC4899,stroke:#DB2777,stroke-width:2px,color:#fff\n style EC fill:#F97316,stroke:#EA580C,stroke-width:2px,color:#fff\n style P fill:#10B981,stroke:#047857,stroke-width:2px,color:#fff\n style D fill:#06B6D4,stroke:#0891B2,stroke-width:2px,color:#fff\n style B fill:#14B8A6,stroke:#0D9488,stroke-width:2px,color:#fff\n style ED fill:#8B5CF6,stroke:#7C3AED,stroke-width:2px,color:#fff\n style HC fill:#EF4444,stroke:#DC2626,stroke-width:2px,color:#fff\n style MP fill:#F59E0B,stroke:#D97706,stroke-width:2px,color:#000\n style AI fill:#6366F1,stroke:#4F46E5,stroke-width:2px,color:#fff\n style G fill:#84CC16,stroke:#65A30D,stroke-width:2px,color:#000\n style API fill:#FBBF24,stroke:#F59E0B,stroke-width:2px,color:#000\n```\n\n### What Each Archetype Includes\n\n> ### The 12 Pre-Configured Archetypes\n>\n> - ๐ **SaaS Startup** (44 Agents) โ Engineering (full), Security, QA, Product, DevOps, Meta\n> - ๐ฑ **Mobile App** (26 Agents) โ Engineering (mobile + backend), QA, Product, Meta\n> - ๐ **E-commerce** (45 Agents) โ Engineering (full), Security, QA, Product, DevOps, Marketing, Meta\n> - ๐ผ๏ธ **Portfolio** (14 Agents) โ Engineering (frontend), Product, Meta\n> - ๐ **Dashboard** (29 Agents) โ Engineering (backend + frontend + DB), QA, Meta\n> - ๐ **Blog / CMS** (21 Agents) โ Engineering (frontend + backend), Product, Marketing, Meta\n> - ๐ **EdTech** (32 Agents) โ Engineering (full), QA, Product, Meta\n> - ๐ฅ **Healthcare** (40 Agents) โ Engineering (full), Security, QA, Product, DevOps, Meta\n> - ๐ช **Marketplace** (47 Agents) โ Engineering (full), Security, QA, Product, DevOps, Marketing, Meta\n> - ๐ค **AI / ChatBot** (30 Agents) โ Engineering (backend + frontend), Intelligence, QA, Meta\n> - ๐ฎ **Gaming** (23 Agents) โ Engineering (game + frontend), QA, Meta\n> - โ๏ธ **API-First** (33 Agents) โ Engineering (backend + DB), Security, QA, DevOps, Meta [!TIP]\n> **Start small, scale up.** You can always run `agent-kit init` later to upgrade to the full 54-agent fleet. The CLI is additive โ it won't overwrite existing agents.\n\n---\n\n## โ๏ธ Tech Stack\n\n| Layer | Technology | Purpose |\n| :---------------------: | :------------------------------ | :------------------------------------------------------------------------------------- |\n| ๐ฆ **Distribution** | NPM / NPX | One-command installation, versioning, global installs |\n| โจ๏ธ **CLI** | Node.js + fs-extra + picocolors | Init scaffolding, doctor validation, interactive archetype menu |\n| ๐๏ธ **Agent Protocols** | Markdown (.md) + JSON manifests | Agent definitions with identity, rules, boundaries, anti-patterns |\n| ๐ **Search Engine** | Python + custom BM25 | Full-text search over 34 CSV datasets with tokenization and IDF weighting |\n| ๐จ **Design Generator** | Python + CSV + JSON | Multi-domain aggregation โ automated design system output |\n| ๐ **Auth Reference** | FastAPI + Bcrypt + JWT | Production-ready authentication template for backend agents |\n| โ๏ธ **Audit Engine** | `checklist.py` (Python) | Priority-ordered health validation: Security โ Lint โ Schema โ Tests โ UX โ SEO |\n| ๐ง **Memory System** | Structured Markdown | Persistent project context: architecture.md, decisions.md, conventions.md, risk-log.md |\n| ๐ **Workflows** | Markdown SOPs | 19 pre-built standard operating procedures with step-by-step execution |\n\n---\n\n## ๐ก๏ธ Security & Privacy\n\nAgent-Kit enforces security through **seven distinct mechanisms**:\n\n| # | Mechanism | How It Works |\n| :-: | :----------------------------- | :------------------------------------------------------------------------------------------------------------------------------------ |\n| 1 | ๐ฆ **Socratic Gate** | Forces 3+ strategic questions before any complex task โ prevents the AI from acting on misunderstood requirements |\n| 2 | ๐ **Tiered Authority (RBAC)** | 4-tier access control: Owner โ Executive โ Department โ Meta. No agent can exceed its tier permissions |\n| 3 | ๐ก๏ธ **Iron Well 2-Phase** | Phase 1 = planning only (no code). Phase 2 = execution only (plan must be approved first). No mixing. |\n| 4 | ๐ **Privacy Columns** | Every CSV dataset includes `Privacy_Tier` (GDPR, CCPA, HIPAA levels), consent-before-track patterns, and data minimization guidelines |\n| 5 | ๐ **SEC-001 Agent** | Dedicated security specialist that performs threat modeling, dependency auditing, and OWASP Top 10 scanning |\n| 6 | ๐ **Chaos Testing** | `security_chaos_test.py` simulates real-world attack vectors against your codebase to find vulnerabilities proactively |\n| 7 | ๐ก **API Contract Sync** | `sync_api_contracts.py` ensures backend API responses match what the frontend expects โ preventing integration bugs at deploy time |\n\n### CTS-001 Approval Checklist\n\nBefore any code reaches production, CTS-001 verifies:\n\n```text\nโ
Code follows project conventions\nโ
No security vulnerabilities introduced\nโ
Performance impact is acceptable\nโ
Tests are adequate (unit + integration)\nโ
Documentation is updated\nโ
Memory files are current\nโ
No permission boundaries violated\n```\n\n---\n\n## ๐ข Deployment Pipeline\n\nFrom your IDE to your end user's project:\n\n```mermaid\n%%{init: {'theme': 'default'}}%%\n\nflowchart LR\n DEV[\"๐งโ๐ป Developer\"] -->|\"git push\"| GH[\"๐ GitHub Repo\"]\n GH -->|\"CI triggers\"| LINT[\"๐ Lint & Type Check\"]\n LINT -->|\"pass\"| TEST[\"๐งช Component Tests\"]\n TEST -->|\"pass\"| AUDIT[\"โ๏ธ checklist.py Audit\"]\n AUDIT -->|\"โ
all pass\"| VSN[\"๐ Version Bump\"]\n VSN --> PUB[\"๐ฆ npm publish\"]\n PUB --> USER[\"๐ End User (npx init)\"]\n\n AUDIT -->|\"โ fail\"| DEV\n\n style DEV fill:#6366F1,color:#fff,stroke:#4F46E5,stroke-width:2px\n style GH fill:#7C3AED,color:#fff,stroke:#5B21B6,stroke-width:2px\n style LINT fill:#2563EB,color:#fff,stroke:#1D4ED8,stroke-width:2px\n style TEST fill:#06B6D4,color:#fff,stroke:#0891B2,stroke-width:2px\n style AUDIT fill:#F59E0B,color:#000,stroke:#D97706,stroke-width:2px\n style VSN fill:#EC4899,color:#fff,stroke:#DB2777,stroke-width:2px\n style PUB fill:#10B981,color:#fff,stroke:#047857,stroke-width:3px\n style USER fill:#7C3AED,color:#fff,stroke:#5B21B6,stroke-width:3px\n```\n\n---\n\n## ๐บ๏ธ Roadmap\n\n| Initiative | Status | Description |\n| :----------------------- | :--------: | :---------------------------------------------------------------------------------------------------- |\n| ๐ช **Agent Marketplace** | ๐ Planned | Community-contributed agent templates, skills, and CSV datasets |\n| ๐ **Multi-LLM Router** | ๐ Planned | Assign different AI models to different agents (GPT for planning, Claude for code, Gemini for design) |\n| ๐ **Live Dashboard** | ๐ Planned | Web-based fleet monitoring through the orchestrator |\n\n---\n\n## ๐ง The Agent-Kit Architecture (V3.6+)\n\n> [!IMPORTANT]\n> **The Hybrid Arsenal Pivot**\n> Agent-Kit V3.6 introduces four distinct intelligence pillars designed to **augment** your existing IDE AI (like **Google Antigravity**, Cursor, Copilot, or Windsurf), rather than compete with them.\n\n1. **Pillar 1: Native MCP Server** โ Agent-Kit integrates directly into your AI IDE as an active tool server with 6 tools.\n2. **Pillar 2: The Hybrid Arsenal** โ Provides active validation (`checklist.py`), security chaos testing, and UI generation scripts that your IDE AI can trigger autonomously.\n3. **Pillar 3: Semantic Project Memory** โ Live AST-aware codebase scanning that updates agent ground-truth over time (`architecture.md`, `api-contracts.md`, etc.).\n4. **Pillar 4: Self-Test Loop** โ `self-test` command runs all 3 diagnostics and produces a unified health report, enabling the system to audit itself.\n\n---\n\n## ๐ค Contributing\n\nAgent-Kit is fully modular โ every agent, skill, and dataset is an independent file. Contributing is straightforward.\n\n### Add a New Agent\n\n1. Create `your-agent.agent.md` in `.agent-os/agents//`\n2. Follow the standard template:\n - **Identity** โ Agent ID, tier, role description\n - **Protocol** โ Step-by-step operational procedure\n - **Boundaries** โ What files it can read/write\n - **Anti-Patterns** โ Common mistakes to avoid\n3. Register in `manifest.json` under the appropriate department\n4. Submit a PR with a description of the agent's purpose\n\n### Add a New Skill\n\n1. Create `.agent-os/skills/your-skill/SKILL.md`\n2. Add YAML frontmatter with `name` and `description`\n3. Include helper scripts in `scripts/` and examples in `examples/` if applicable\n\n### Add a New CSV Dataset\n\n1. Add your CSV file:\n - **Domain CSVs** โ `.agent-os/.shared/UI&UX/data/your-domain.csv`\n - **Stack CSVs** โ `.agent-os/.shared/UI&UX/data/stacks/your-stack.csv`\n2. Register it in `scripts/core.py` โ `CSV_CONFIG` or `STACK_CONFIG`\n3. Add detection keywords to `detect_domain()` so the BM25 engine can auto-route queries\n\n### Workflow\n\n```text\nFork โ Branch โ Implement โ Test โ PR โ Review โ Merge\n```\n\n---\n\n## ๐ License\n\nThis project is licensed under the **MIT License** โ see [LICENSE](LICENSE) for details.\n\n---\n\n> ### ๐ญ Built for solo developers who think like companies\n>\n> **54 agents ยท 42+ skills ยท 19 workflows ยท 18 design domains ยท 16 framework stacks**\n>\n> **Iron Well v2.0 governance ยท BM25 search ยท Socratic Gate ยท 12 company archetypes**\n>\n> [](https://www.npmjs.com/package/@ab_aswini/agent-kit-p1) [](https://github.com/Ab-aswini/Agent-kit-P1) [](https://github.com/Ab-aswini/Agent-kit-P1/issues)\n>\n> โญ **If Agent-Kit helps your workflow, star this repo โ it helps others find it.**\n","readmeFilename":"README.md"}