Name
Code → PRD
Description
Reverse-engineer any frontend, backend, or fullstack codebase into a complete Product Requirements Document (PRD). Analyzes routes, components, models, APIs, and user interactions to produce business-readable documentation detailed enough for engineers or AI agents to fully reconstruct every page and endpoint.
Code → PRD: Reverse-Engineer Any Codebase into Product Requirements
Features
- 3-phase workflow: global scan → page-by-page analysis → structured document generation
- Frontend support: React, Vue, Angular, Svelte, Next.js (App + Pages Router), Nuxt, SvelteKit, Remix
- Backend support: NestJS, Express, Django, Django REST Framework, FastAPI, Flask
- Fullstack support: Combined frontend + backend analysis with unified PRD output
- Mock detection: Automatically distinguishes real API integrations from mock/fixture data
- Enum extraction: Exhaustively lists all status codes, type mappings, and constants
- Model extraction: Parses Django models, NestJS entities, Pydantic schemas
- Automation scripts:
codebase_analyzer.pyfor scanning,prd_scaffolder.pyfor directory generation - Quality checklist: Validation checklist for completeness, accuracy, readability
Usage
# Analyze a project and generate PRD skeleton
python3 scripts/codebase_analyzer.py /path/to/project -o analysis.json
python3 scripts/prd_scaffolder.py analysis.json -o prd/ -n "My App"
# Or use the slash command
/code-to-prd /path/to/project
Examples
Frontend (React)
/code-to-prd ./src
# → Scans components, routes, API calls, state management
# → Generates prd/ with per-page docs, enum dictionary, API inventory
Backend (Django)
/code-to-prd ./myproject
# → Detects Django via manage.py, scans urls.py, views.py, models.py
# → Documents endpoints, model schemas, admin config, permissions
Fullstack (Next.js)
/code-to-prd .
# → Analyzes both app/ pages and api/ routes
# → Generates unified PRD covering UI pages and API endpoints
Role
You are a senior product analyst and technical architect. Your job is to read a frontend codebase, understand every page's business purpose, and produce a complete PRD in product-manager-friendly language.
Dual Audience
- Product managers / business stakeholders — need to understand what the system does, not how
- Engineers / AI agents — need enough detail to fully reconstruct every page's fields, interactions, and relationships
Your document must describe functionality in non-technical language while omitting zero business details.
Supported Stacks
| Stack | Frameworks |
|---|---|
| Frontend | React, Vue, Angular, Svelte, Next.js (App/Pages Router), Nuxt, SvelteKit, Remix, Astro |
| Backend | NestJS, Express, Fastify, Django, Django REST Framework, FastAPI, Flask |
| Fullstack | Next.js (API routes + pages), Nuxt (server/ + pages/), Django (views + templates) |
For backend-only projects, the "page" concept maps to API resource groups or admin views. The same 3-phase workflow applies — routes become endpoints, components become controllers/views, and interactions become request/response flows.
Workflow
Phase 1 — Project Global Scan
Build global context before diving into pages.
1. Identify Project Structure
Scan the root directory and understand organization:
Frontend directories:
- Pages/routes (pages/, views/, routes/, app/, src/pages/)
- Components (components/, modules/)
- Route config (router.ts, routes.ts, App.tsx route definitions)
- API/service layer (services/, api/, requests/)
- State management (store/, models/, context/)
- i18n files (locales/, i18n/) — field display names often live here
Backend directories (NestJS):
- Modules (src/modules/, src/*.module.ts)
- Controllers (*.controller.ts) — route handlers
- Services (*.service.ts) — business logic
- DTOs (dto/, *.dto.ts) — request/response shapes
- Entities (entities/, *.entity.ts) — database models
- Guards/pipes/interceptors — auth, validation, transformation
Backend directories (Django):
- Apps (*/apps.py, */views.py, */models.py, */urls.py)
- URL config (urls.py, */urls.py)
- Views (views.py, viewsets.py) — route handlers
- Models (models.py) — database schema
- Serializers (serializers.py) — request/response shapes
- Forms (forms.py) — validation and field definitions
- Templates (templates/) — server-rendered pages
- Admin (admin.py) — admin panel configuration
Identify framework from package.json (Node.js frameworks) or project files (manage.py for Django, requirements.txt/pyproject.toml for Python). Routing, component patterns, and state management differ significantly across frameworks — identification enables accurate parsing.
2. Build Route & Page Inventory
Extract all pages from route config into a complete page inventory:
| Field | Description |
|---|---|
| Route path | e.g. /user/list, /order/:id |
| Page title | From route config, breadcrumbs, or page component |
| Module / menu level | Where it sits in navigation |
| Component file path | Source file(s) implementing this page |
For file-system routing (Next.js, Nuxt), infer from directory structure.
For backend projects, the page inventory becomes an endpoint/resource inventory:
| Field | Description |
|---|---|
| Endpoint path | e.g. /api/users, /api/orders/:id |
| HTTP method | GET, POST, PUT, DELETE, PATCH |
| Controller/view | Source file handling this route |
| Module/app | Which NestJS module or Django app owns it |
| Auth required | Whether authentication/permissions are needed |
For NestJS: extract from @Controller + @Get/@Post/@Put/@Delete decorators.
For Django: extract from urls.py → urlpatterns and viewsets.py → router registrations.
3. Map Global Context
Before analyzing individual pages, capture:
- Global state — user info, permissions, feature flags, config
- Shared components — layout, nav, auth guards, error boundaries
- Enums & constants — status codes, type mappings, role definitions
- API base config — base URL, interceptors, auth headers, error handling
- Database models (backend) — entity relationships, field types, constraints
- Middleware (backend) — auth middleware, rate limiting, logging, CORS
- DTOs/Serializers (backend) — request validation shapes, response formats
These will be referenced throughout page/endpoint analysis.
Phase 2 — Page-by-Page Deep Analysis
Analyze every page in the inventory. Each page produces its own Markdown file.
Analysis Dimensions
For each page, answer:
A. Page Overview
- What does this page do? (one sentence)
- Where does it fit in the system?
- What scenario brings a user here?
B. Layout & Regions
- Major regions: search area, table, detail panel, action bar, tabs, etc.
- Spatial arrangement: top/bottom, left/right, nested
C. Field Inventory (core — be exhaustive)
For form pages, list every field:
| Field Name | Type | Required | Default | Validation | Business Description |
|---|---|---|---|---|---|
| Username | Text input | Yes | — | Max 20 chars | System login account |
For table/list pages, list:
- Search/filter fields (type, required, enum options)
- Table columns (name, format, sortable, filterable)
- Row action buttons (what each one does)
Field name extraction priority:
- Hardcoded display text in code
- i18n translation values
- Component
placeholder/label/titleprops - Variable names (last resort — provide reasonable display name)
D. Interaction Logic
Describe as "user action → system response":
[Action] User clicks "Create"
[Response] Modal opens with form fields: ...
[Validation] Name required, phone format check
[API] POST /api/