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WaspReactPrismaTypeScriptClaude

Wasp × Claude Prompt Engineering

Stop fighting Claude hallucinations. Generate Wasp-aware prompts that produce code your team can actually ship.

Try Wasp + Claude Prompts Free
Model-agnostic prompts
Stack-aware constraints
Production-ready output
The Problem

AI ignores Wasp DSL, writes manual auth code, and skips the declarative operations syntax. Claude can hallucinate API signatures and produce overly verbose implementations.

The Solution

AI Prompt Architect Prompts enforce Wasp .wasp file declarations, auto-generated CRUD, and proper auth/operations patterns. It provides Claude with constraints and examples that reduce hallucination and enforce concise output.

How It Works

Three steps to production-quality Wasp code

⚙️
STEP 1

Define Your Wasp Stack

Specify your Wasp + React project structure, dependencies, and conventions.

🧠
STEP 2

Generate Claude-Optimised Prompts

Get prompts formatted specifically for Claude, with Wasp constraints that eliminate hallucinations.

🚀
STEP 3

Ship Production Code

Paste the prompt into Claude and get code that follows Wasp best practices — tested patterns, not hallucinations.

Frequently Asked Questions

Does it work with Claude?
Yes. AI Prompt Architect generates prompts optimised for Claude, including context formatting and constraint syntax that Claude responds best to.
Can it handle Wasp projects?
Absolutely. Prompts include Wasp-specific conventions, API patterns, and best practices to eliminate common hallucinations.
Is there a free tier?
Yes — generate up to 5 prompts per day for free. Pro tier unlocks unlimited generations, team sharing, and advanced templates.

Technical Deep Dive

How does AI Prompt Architect handle React Server Components vs Client Components?
Prompts include explicit "use client" / "use server" boundary annotations, ensuring AI-generated code correctly separates server-side data fetching from interactive client logic. The constraint engine enforces proper import boundaries.
Can it generate prompts for React 19 concurrent features?
Yes — prompts encode useTransition, useDeferredValue, and Suspense boundary patterns. The system constrains AI output to avoid deprecated lifecycle methods and ensures proper concurrent-safe state updates.
How does AI Prompt Architect optimise prompts for Claude?
It structures prompts with Claude's XML tag format, explicit constraint blocks, and few-shot examples that reduce hallucination. The system leverages Claude's strength with long context by including full schema definitions.
Real Generated Output

Production-Ready Project Structure

Every generated prompt includes a complete directory tree tailored to your Wasp + React + Prisma + TypeScript + Claude stack

project-structure.tree — AI Prompt Architect
├── .github/
│   ├── workflows/
│   │   ├── ci.yml
│   │   ├── deploy-staging.yml
│   │   └── deploy-production.yml
│   ├── CODEOWNERS
│   └── pull_request_template.md
├── .husky/
│   ├── pre-commit
│   └── commit-msg
├── docker/
│   ├── Dockerfile
│   ├── Dockerfile.dev
│   ├── docker-compose.yml
│   ├── docker-compose.dev.yml
│   └── nginx.conf
├── docs/
│   ├── architecture/
│   │   ├── ADR-001-framework-selection.md
│   │   ├── ADR-002-database-strategy.md
│   │   ├── ADR-003-auth-approach.md
│   │   └── system-diagram.mermaid
│   ├── api/
│   │   └── openapi.yaml
│   └── runbook.md
├── prisma/
│   ├── schema.prisma
│   ├── seed.ts
│   └── migrations/
│       └── 001_initial_schema/
│           └── migration.sql
├── src/
│   ├── app/
│   │   ├── layout.tsx
│   │   ├── page.tsx
│   │   ├── loading.tsx
│   │   ├── error.tsx
│   │   ├── not-found.tsx
│   │   ├── (auth)/
│   │   │   ├── login/page.tsx
│   │   │   ├── signup/page.tsx
│   │   │   └── layout.tsx
│   │   ├── (dashboard)/
│   │   │   ├── layout.tsx
│   │   │   ├── overview/page.tsx
│   │   │   ├── projects/
│   │   │   │   ├── page.tsx
│   │   │   │   └── [id]/page.tsx
│   │   │   ├── settings/page.tsx
│   │   │   └── billing/page.tsx
│   │   └── api/
│   │       ├── auth/[...nextauth]/route.ts
│   │       ├── webhooks/stripe/route.ts
│   │       ├── trpc/[trpc]/route.ts
│   │       └── health/route.ts
│   ├── components/
│   │   ├── ui/
│   │   │   ├── Button.tsx
│   │   │   ├── Input.tsx
│   │   │   ├── Modal.tsx
│   │   │   ├── Toast.tsx
│   │   │   ├── Skeleton.tsx
│   │   │   └── index.ts
│   │   ├── layouts/
│   │   │   ├── AppShell.tsx
│   │   │   ├── Sidebar.tsx
│   │   │   ├── Header.tsx
│   │   │   └── Footer.tsx
│   │   └── features/
│   │       ├── auth/
│   │       │   ├── LoginForm.tsx
│   │       │   ├── SignupForm.tsx
│   │       │   └── AuthGuard.tsx
│   │       └── projects/
│   │           ├── ProjectCard.tsx
│   │           ├── ProjectList.tsx
│   │           └── CreateProjectModal.tsx
│   ├── server/
│   │   ├── trpc/
│   │   │   ├── router.ts
│   │   │   ├── context.ts
│   │   │   └── procedures/
│   │   │       ├── user.ts
│   │   │       ├── project.ts
│   │   │       └── billing.ts
│   │   ├── db/
│   │   │   ├── client.ts
│   │   │   └── queries/
│   │   │       ├── users.ts
│   │   │       └── projects.ts
│   │   └── services/
│   │       ├── auth.service.ts
│   │       ├── email.service.ts
│   │       ├── stripe.service.ts
│   │       └── analytics.service.ts
│   ├── lib/
│   │   ├── utils.ts
│   │   ├── constants.ts
│   │   ├── validators.ts
│   │   └── hooks/
│   │       ├── useAuth.ts
│   │       ├── useDebounce.ts
│   │       └── useMediaQuery.ts
│   ├── styles/
│   │   ├── globals.css
│   │   └── tokens.css
│   └── types/
│       ├── index.ts
│       ├── api.ts
│       └── database.ts
├── tests/
│   ├── unit/
│   │   └── services/
│   │       └── auth.test.ts
│   ├── integration/
│   │   └── api/
│   │       └── users.test.ts
│   └── e2e/
│       ├── auth.spec.ts
│       └── projects.spec.ts
├── .env.example
├── .eslintrc.cjs
├── .prettierrc
├── .gitignore
├── next.config.ts
├── tailwind.config.ts
├── tsconfig.json
├── vitest.config.ts
├── playwright.config.ts
└── package.json

Start Building with Wasp

Free tier includes unlimited prompt generation. No credit card required.

Try Wasp + Claude Prompts Free

3 well-crafted few-shot examples (150 tokens) outperform a 600-token verbose instruction block, saving 75% on input cost.Brown et al., 'Language Models are Few-Shot Learne…