enterprise-ai-saas

name	enterprise-ai-saas
description	This skill scaffolds and builds a production-ready, enterprise-grade AI SaaS website with authentication (Supabase Auth + JWT + RBAC), subscription payments (Stripe), AI chat (MiniMax M2.7 via EdgeOne AI Gateway with streaming), admin dashboard, and a 5-layer security architecture — all deployed to EdgeOne Pages using Edge Functions, Cloud Functions, KV Storage, and Middleware. It should be used when the user wants to build a full-stack AI SaaS platform from scratch — e.g. "build an AI SaaS", "create an AI assistant platform", "scaffold a SaaS with login and payment", "帮我搭一个 AI SaaS", "做一个带登录支付的 AI 平台", "搭建企业级 AI 工具站", "create a subscription-based AI tool", "build a full-stack SaaS with admin dashboard". Do NOT trigger when the user already has a running project and only wants to add a single function/API (use edgeone-pages-dev). Do NOT trigger for pure deployment of an existing project (use edgeone-pages-deploy). Do NOT trigger for simple static sites, portfolios, or landing pages without SaaS features.
metadata	{"author":"enterprise-ai-saas","version":"1.0.0"}

Enterprise AI SaaS Scaffolding Skill

Build a complete, enterprise-grade AI SaaS platform on EdgeOne Pages — from zero to production with one command.

Generated websites include: user authentication, subscription payments, AI chat with streaming, admin dashboard, and multi-layer security — all leveraging EdgeOne's full-stack capabilities.

When to use this skill

• User wants to start a new AI SaaS (AI assistant, AI tool, AI chatbot platform, etc.)
• User wants a full-stack platform with login + payment + AI + admin dashboard
• User mentions enterprise features like security, RBAC, rate limiting, audit logging
• User wants to build on EdgeOne Pages with Edge Functions, KV, and Cloud Functions

Do NOT use for:

• Adding a single API/function to an existing project → use edgeone-pages-dev
• Deploying an already-built project → use edgeone-pages-deploy
• Simple static sites, blogs, portfolios, or landing pages without SaaS features
• Non-SaaS e-commerce sites (use a dedicated e-commerce skill)

How to use this skill (for the coding agent)

Follow the Main Flow below top-to-bottom. Load references/*.md only when the flow tells you to — do NOT preload everything. This skill uses progressive disclosure to minimize context usage.

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⛔ Critical Rules (never skip)

1. ALWAYS ask the user about their Prompt FIRST (Step 1). This is the mandatory entry gate.
2. Never fabricate the user's product. If info is missing and the user has no Prompt, run the built-in questionnaire in references/user-prompt-intake.md.
3. Generate all code from scratch — this skill does NOT depend on any external template repository. All project files are generated directly by the agent following the patterns in references/.
4. TypeScript everywhere. Never generate plain JavaScript files. All .ts / .tsx only.
5. Never commit secrets. Ensure .env.local, .edgeone/.token, and any API key files are in .gitignore.
6. Security is not optional. Always implement at least the base security layer (rate limiting + input validation + CORS) regardless of the user's security.level choice.
7. DO NOT deploy inside this skill. Deployment belongs to edgeone-pages-deploy. In Step 8, verify the deploy skill is available and hand off.
8. Test before handoff. Always run npm run build successfully before proceeding to Step 8.
9. Confirm destructive operations (removing modules, changing config) before executing.
10. Install edgeone-pages-skills at the start — this is a competition requirement. Run npx skills add TencentEdgeOne/edgeone-pages-skills during project scaffold.

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Main Flow

Step 1 — Gate Question: does the user have a Prompt?

This is mandatory and happens FIRST. Ask the user:

开始之前先问一下：你有没有自己准备好的产品描述 / Prompt？

• 有 — 贴进来，我会据此定位品牌 / 功能 / 配色 / 安全等级
• 没有 — 我会用内置问答引导你，问几个关键问题
• 完全默认 — 直接按默认规格（AI 助手平台，深蓝主题，中英双语，企业级安全）落地

Branch:

• User provides a Prompt → read references/user-prompt-intake.md § "Prompt 解析" and extract a Spec
• User chooses questionnaire → read references/user-prompt-intake.md § "内置问答" and run through questions
• User chooses default → use default Spec from references/user-prompt-intake.md § "默认规格"

Output: a Spec object. Show it to the user and confirm before proceeding.

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Step 2 — Spec Confirmation

Display the full Spec to the user in a JSON code block. Validate dependency rules:

• features.payment = true ⟹ features.auth = true
• features.aiChat = true ⟹ features.auth = true
• features.adminDashboard = true ⟹ features.auth = true
• security.level = "enterprise" ⟹ all security features enabled

Ask for final confirmation. Proceed only after the user says go.

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Step 3 — Project Scaffold

Read references/project-scaffold.md and follow it to:

1. Create the project directory
2. Initialize package.json with all dependencies
3. Generate the complete directory structure (see architecture in references/architecture-overview.md)
4. Install edgeone-pages-skills: npx skills add TencentEdgeOne/edgeone-pages-skills
5. Install dependencies: npm install
6. Verify directory structure matches expected layout

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Step 4 — Core Features Implementation

Implement features based on the Spec, loading references as needed:

Feature	Condition	Reference
Authentication (Supabase + JWT + RBAC)	features.auth = true	references/auth-system.md
Subscription Payments (Stripe)	features.payment = true	references/payment-stripe.md
AI Chat (MiniMax M2.7 via EdgeOne AI Gateway)	features.aiChat = true	references/ai-integration.md
Admin Dashboard	features.adminDashboard = true	references/admin-dashboard.md
UI Design System	Always	references/ui-design-system.md
Database Schema	features.auth = true	references/database-schema.md

Implementation order: Auth → Database → Payment → AI → Admin → UI polish.

Report progress after each module. If a module fails to build, diagnose and fix before moving on.

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Step 5 — Security Hardening

Read references/security-hardening.md and implement the security layers based on security.level:

Layer	Level: basic	Level: enterprise
Rate Limiting (Edge Function + KV)	✅ IP-based	✅ IP + User + Endpoint
CORS + CSP Headers	✅ Basic	✅ Strict whitelist
Input Validation (Zod)	✅ API inputs	✅ All inputs + file uploads
JWT Verification (Edge)	✅ Token check	✅ Token + Role + Expiry
Stripe Webhook Signature	✅ Basic verify	✅ Verify + Idempotency
Supabase RLS	✅ Row-level	✅ Row-level + Column-level
Audit Logging	❌	✅ All mutations logged
CSRF Protection	❌	✅ Double-submit cookie

Also read references/edge-kv-patterns.md for EdgeOne-specific implementation patterns.

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Step 6 — Environment Variables

Read references/deployment-handoff.md § "Environment Variables" and:

1. Generate .env.example with all required keys (no real values)
2. Create .env.local from .env.example
3. Based on enabled features, produce a filtered env list
4. Guide the user to obtain each key from the respective dashboards:
   • Supabase: Project URL, Anon Key, Service Role Key
   • Stripe: Secret Key, Webhook Secret, Price IDs
   • MiniMax: API Key (via EdgeOne AI Gateway)
   • EdgeOne: AI Gateway Key, Gateway Name
5. Write collected values into .env.local

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Step 7 — Local Verification

Run build and local dev:

npm run build          # Must succeed with zero errors
npm run dev            # Start on http://localhost:3000

Ask the user to verify:

• Homepage renders with correct branding
• Login / Register works (if Supabase env configured)
• Pricing page shows subscription plans
• AI chat produces streaming responses (if MiniMax key configured)
• Admin dashboard accessible only to admin role
• Rate limiting returns 429 after threshold
• Mobile layout renders correctly

If something breaks, diagnose:

• Missing env var → check .env.local
• Build error → fix TypeScript/import issues
• Supabase error → check schema initialization
• AI error → verify EdgeOne AI Gateway configuration

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Step 8 — Deployment Handoff

8.1 Pre-check: is edgeone-pages-deploy installed?

Check if the deploy skill exists:

• macOS/Linux: ~/.codebuddy/skills/edgeone-pages-deploy/
• Or check via the IDE's skill management

8.2 If installed — tell the user:

✅ 项目已就绪，本地验证通过。

直接告诉我 "部署到 EdgeOne Pages"，我会加载 edgeone-pages-deploy skill 完成上线。

8.3 If not installed — guide installation:

⚠️ 检测到 deploy skill 未安装。运行以下命令安装：

npx skills add TencentEdgeOne/edgeone-pages-skills

安装完成后告诉我，我来继续部署流程。

DO NOT execute deployment commands inside this skill.

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Routing

Step	When to load	Reference
Step 1 — User intent + Spec extraction	Always (first step)	references/user-prompt-intake.md
Step 3 — Project structure + dependencies	After Spec confirmed	references/project-scaffold.md
Step 3 — Architecture decisions	After Spec confirmed	references/architecture-overview.md
Step 4 — Authentication	features.auth = true	references/auth-system.md
Step 4 — Payments	features.payment = true	references/payment-stripe.md
Step 4 — AI integration	features.aiChat = true	references/ai-integration.md
Step 4 — Admin dashboard	features.adminDashboard = true	references/admin-dashboard.md
Step 4 — UI components	Always	references/ui-design-system.md
Step 4 — Database schema	features.auth = true	references/database-schema.md
Step 5 — Security implementation	Always	references/security-hardening.md
Step 5 — Edge + KV patterns	Always	references/edge-kv-patterns.md
Step 8 — Build verification + deploy handoff	After all features done	references/deployment-handoff.md

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Generated Website Pages

The skill produces a complete website with these routes:

Route	Description	Auth Required
/	Marketing landing page (Hero, Features, Pricing, Testimonials, CTA)	No
/login	Login page (Email + OAuth)	No
/register	Registration page	No
/pricing	Subscription plans (Free / Pro / Enterprise)	No
/dashboard	User dashboard (AI workspace + usage stats)	Yes
/dashboard/chat	AI chat interface (streaming responses)	Yes
/dashboard/settings	User profile and preferences	Yes
/admin	Admin overview (requires admin role)	Yes (admin)
/admin/users	User management	Yes (admin)
/admin/analytics	Usage analytics and metrics	Yes (admin)
/admin/settings	System configuration	Yes (admin)

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Tech Stack

• Frontend: Next.js 14 (App Router) + TypeScript + Tailwind CSS + shadcn/ui + Motion (Framer Motion)
• Backend: EdgeOne Cloud Functions (Node.js) + Edge Functions (V8)
• Storage: EdgeOne KV (sessions, cache, rate limiting) + Supabase (PostgreSQL)
• Payments: Stripe Subscriptions + Webhooks
• AI: MiniMax M2.7 via EdgeOne AI Gateway (streaming SSE)
• Auth: Supabase Auth + JWT + RBAC Middleware
• Deploy: EdgeOne Pages

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Quick Reference

Install this skill:

npx skills add enterprise-ai-saas-skill

Trigger phrases:

• "build an AI SaaS on EdgeOne Pages"
• "scaffold an enterprise AI platform"
• "帮我搭一个带登录支付的 AI SaaS"
• "create a full-stack AI assistant platform"
• "做一个企业级 AI 工具站部署到 EdgeOne Pages"

Hand-off to deploy: user says "deploy to EdgeOne Pages" / "部署到 EdgeOne Pages"