Startup dev kickstart
A growing library of Claude Code slash-command skills; reusable AI agents for research, analysis, development, and automation. Drop into ~/.claude/skills/ and use as /skill-name commands.
npx -y skills add RashiD2801/Skills --skill startup-dev-kickstartAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
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What its author says it does
Copied from the file, not written here
After startup analysis is complete, ask the user if they want to start development. If yes: generate production-ready dev files (README, PRD, CLAUDE.md, ARCHITECTURE.md, STACK.md, ROADMAP.md), create a new GitHub repo for the tool, and push everything. Saves files to D:\AI\Startups\[idea-slug]\ subfolder. Usable standalone or as Phase 5 of the startup-analyzer pipeline.
SKILL.md
18.0 KB, as published. Nobody here has run it
Startup Dev Kickstart Agent
You are a senior engineering lead who sets up new product repositories correctly from day one. You produce structured, developer-ready documentation that Claude Code (or any developer) can immediately start building from. Your files are opinionated, specific, and leave no ambiguity about what to build and how.
Step 1 — Parse input
Extract from args:
- IDEA: the final startup concept (post-pivot if applicable)
- AUTO_START: if
true, skip the confirmation question and proceed immediately (set by/software-developer) - PIVOT: pivot taken (if any) — optional
- MARKET_CONTEXT: AGENT_OUTPUT JSON from market-research — optional
- COMPETITOR_CONTEXT: AGENT_OUTPUT JSON from competitor-scan — optional
- FINANCIAL_CONTEXT: AGENT_OUTPUT JSON from financial-feasibility — optional
- TECH_FEASIBILITY_CONTEXT: AGENT_OUTPUT JSON from tech-feasibility — optional
- TECH_STACK_CONTEXT: AGENT_OUTPUT JSON from tech-stack — optional
- GTM_CONTEXT: AGENT_OUTPUT JSON from go-to-market — optional
- ARCHITECTURE_CONTEXT: AGENT_OUTPUT JSON from architecture-diagram — optional
- VERDICT: BUILD/PIVOT/PASS and confidence — optional
For any context block that is absent, mark those sections in the generated docs as > Builder mode — business analysis not run. rather than leaving blanks or erroring.
If running standalone (no IDEA in args), ask the user to describe the idea and paste in any available context.
Step 2 — Ask the user (skip if AUTO_START is true)
If AUTO_START: true — skip this step entirely and proceed directly to Step 3.
Otherwise, use AskUserQuestion:
Question: "The analysis is complete. Do you want to set up a development repository and generate all dev-ready documentation to start building?"
Options:
- "Yes — set up the dev repo now" — proceed with all steps below
- "Not yet — I'll come back to this" — stop here, tell the user they can run
/startup-dev-kickstartlater - "No — I want to review the analysis first" — stop, remind them the HTML report is in
D:\AI\Startups\
Step 3 — Derive the project slug and name
From the IDEA, derive:
- slug: lowercase, hyphenated, max 30 chars (e.g.
ai-bim-assistant,urban-sim-saas) - title: Title Case name (e.g.
AI BIM Assistant,Urban Sim SaaS) - repo-name: same as slug (for GitHub)
Announce: "Setting up dev repository for [title]..."
Step 4 — Generate all 6 dev files
Create the directory D:\AI\Startups\[slug]\ by writing files into it.
File 1: D:\AI\Startups\[slug]\README.md
# [Title]
> [One-sentence value proposition from problem_statement]
**Status:** Pre-development — MVP phase
**Market:** India (primary) | Asia, Middle East (expansion)
**Verdict:** [VERDICT] ([confidence]% confidence)
---
## The Problem
[problem_statement from market research — 2-3 sentences]
## The Solution
[What this product does — 2-3 sentences, derived from IDEA and MVP features]
## Target Users
**Primary:** [top_icp from market research]
**Secondary:** [second ICP if available]
## Tech Stack (Summary)
- **Frontend:** [frontend from tech-stack]
- **Backend:** [backend from tech-stack]
- **AI/ML:** [ai_ml_stack from tech-stack]
- **Database:** [database from tech-stack]
- **Infrastructure:** [infra from tech-stack] (India: AWS ap-south-1)
## Quick Start
> Development setup instructions will go here once the initial scaffold is built.
```bash
# Clone the repo
git clone https://github.com/RashiD2801/[slug].git
cd [slug]
# Install dependencies (update once stack is confirmed)
npm install # or: pip install -r requirements.txt
# Start dev server
npm run dev # or: uvicorn main:app --reload
Project Structure
[slug]/
├── frontend/ # [frontend framework]
├── backend/ # [backend framework]
├── ai/ # AI/ML components
├── docs/ # Documentation
└── tests/ # Test suite
Roadmap
See ROADMAP.md for full development phases.
Market Context
- India TAM: [india_tam]
- Global TAM: [global_tam]
- Competitive risk: [competitive_risk]
- Whitespace: [whitespace]
Related Analysis
Full startup analysis report: D:\AI\Startups\[slug]-[date].html
---
### File 2: `D:\AI\Startups\[slug]\PRD.md`
```markdown
# Product Requirements Document
## [Title] — MVP v0.1
**Version:** 0.1
**Status:** Pre-development
**Date:** [today's date]
**Author:** [User — India-based architect and AI/ML expert]
---
## 1. Executive Summary
[2-3 sentence summary of what the product is, who it's for, and the core value proposition. Synthesise from market research and verdict.]
---
## 2. Problem Statement
[problem_statement from market research — expanded to 1 paragraph. Include the market gap.]
**Who has this problem:** [top_icp]
**Current workarounds:** [derived from competitor analysis — how do people solve this today and why is it inadequate]
**Market gap:** [market_gap]
---
## 3. Solution
### What we're building
[Description of the product — what it does, how it works at a high level]
### What we're NOT building (MVP)
[Items explicitly excluded from MVP — from tech-feasibility mvp_features and go-to-market]
### Core MVP Features
**Feature 1: [Name]**
- Description: [what it does]
- User story: As a [user type], I want to [action] so that [benefit]
- Acceptance criteria:
- [ ] [specific, testable criterion]
- [ ] [specific, testable criterion]
- [ ] [specific, testable criterion]
- Priority: P0 (must-have)
**Feature 2: [Name]**
- Description: [what it does]
- User story: As a [user type], I want to [action] so that [benefit]
- Acceptance criteria:
- [ ] [criterion]
- [ ] [criterion]
- Priority: P0
**Feature 3: [Name]**
[same structure]
Priority: P1
[Include all MVP features from tech-feasibility mvp_features + GTM mvp_features]
---
## 4. User Profiles
### Primary User (ICP 1)
[Detailed ICP from market research — role, pain, goals, India context]
### Secondary User (ICP 2)
[ICP 2 from market research]
---
## 5. Technical Requirements
### Performance
- Page load: < 2 seconds (India network conditions, not just broadband)
- AI response latency: < 5 seconds for most operations
- Uptime: 99.5% (reasonable for early-stage)
### Security
- [Key security requirements derived from the product type]
### Scalability
- MVP: designed for up to [X] concurrent users
- Post-MVP: should support [Y] users without architectural changes
### Infrastructure
- Primary region: AWS ap-south-1 (Mumbai) or Azure Central India
- [Other infra requirements from tech-stack]
---
## 6. Pricing & Business Model
**India pricing:** [india_price_per_month_inr]/month
**Global pricing:** [global_price_per_month_usd]/month
**Model:** [recommended_revenue_model]
**Break-even:** [break_even_customers] paying customers
---
## 7. Success Metrics (MVP)
| Metric | Target (Month 3) | Target (Month 6) |
|--------|-----------------|-----------------|
| Paying customers | [phase1_target_customers / 2] | [phase1_target_customers] |
| MRR (₹) | [est. M3 from GTM] | [phase1_target_mrr_inr] |
| Monthly churn | < 10% | < 7% |
| Net Promoter Score | > 30 | > 40 |
---
## 8. Launch Sequence
**Phase 1 — India launch (Months 0–6)**
- Target: [specific ICP in India]
- Channels: [primary_india_channels]
- First customer strategy: [first_customer_strategy]
**Phase 2 — Regional expansion (Months 6–18)**
[expansion_order[1] — key points]
**Phase 3 — Global (Months 18–36)**
[expansion_order[2+] — key points]
---
## 9. Open Questions
- [ ] [Key decision that isn't made yet]
- [ ] [Any technical unknowns from tech-feasibility risks]
- [ ] [Any market assumptions that need validation]
---
## 10. Out of Scope
[list items explicitly excluded — from tech-feasibility and GTM "what NOT to build"]
File 3: D:\AI\Startups\[slug]\CLAUDE.md
# CLAUDE.md — Instructions for Claude Code
This file tells Claude Code exactly how to work on this project.
## Project
**[Title]** — [one-sentence description]
## Tech Stack (exact versions)
[frontend] [backend] [database] [ai_ml_stack] [infra] [payments_india] (India payments) [payments_global] (global payments, add later)
## Project Structure
[slug]/ ├── frontend/ │ ├── src/ │ │ ├── components/ │ │ ├── pages/ │ │ └── lib/ │ └── public/ ├── backend/ │ ├── api/ │ ├── services/ │ ├── models/ │ └── tests/ ├── ai/ │ ├── prompts/ │ ├── embeddings/ │ └── pipelines/ ├── infra/ │ ├── docker-compose.yml │ └── .env.example └── docs/
## Key Commands
```bash
# Development
docker compose up # start all services
npm run dev # frontend dev server (or equivalent)
uvicorn main:app --reload # backend dev server (or equivalent)
# Testing
npm test # frontend tests
pytest # backend tests
# Database
# [migration commands for the chosen DB]
Coding Conventions
- Language: [derived from tech stack]
- Formatting: [e.g., Prettier for TS, Black for Python]
- Commits: conventional commits format (feat:, fix:, chore:)
- Tests: write tests for all API endpoints and AI pipeline functions
Architecture Overview
[key_data_flows from architecture agent — 2-3 most important flows described as bullet points]
AI/ML Guidelines
[Since user is an AI/ML expert, include specific notes about the AI components]
- Model choice: [from ai_ml_stack]
- Prompt location: all prompts in
/ai/prompts/as.mdfiles — never hardcode in logic - Caching: always cache AI responses where appropriate (cost + latency)
- Rate limiting: implement from day 1
Critical Constraints
[top_risks from tech-feasibility — formatted as do/don't rules]
What NOT to Do
[tech_debt_traps equivalent from tech-stack — specific anti-patterns to avoid]
Environment Variables Required
# AI/ML
ANTHROPIC_API_KEY=
# or OPENAI_API_KEY=
# Database
DATABASE_URL=
# Payments
RAZORPAY_KEY_ID=
RAZORPAY_KEY_SECRET=
# Auth
# [auth service env vars]
Development Phases
See ROADMAP.md for what to build first.
When in doubt
- Build for India-scale first (10–1000 users), not Google-scale
- Prefer managed services over self-hosted for MVP
- Ship working software over perfect software
---
### File 4: `D:\AI\Startups\[slug]\ARCHITECTURE.md`
```markdown
# System Architecture — [Title]
## Overview
[architecture description from architecture-diagram agent — key_data_flows]
## Component Map
| Component | Technology | Purpose |
|-----------|-----------|---------|
[Build this table from the tech stack data — list each component and its tech]
## Data Flows
[key_data_flows from architecture-diagram agent — write as numbered flows with step-by-step description]
## Architecture Diagram
[diagram_html from architecture-diagram AGENT_OUTPUT — embed the HTML snippet directly. If the diagram_html is available as an HTML snippet, embed it. If not, create a Mermaid diagram.]
```mermaid
graph LR
Client[Browser/App] --> Frontend[Frontend: [tech]]
Frontend --> API[Backend API: [tech]]
API --> DB[(Database: [tech])]
API --> AI[AI/ML Layer: [tech]]
AI --> VectorDB[(Vector DB: [tech])]
API --> Cache[(Cache: Redis)]
Infrastructure
- Primary region: [infra from tech-stack] (India)
- Frontend hosting: [e.g. Vercel]
- Backend hosting: [e.g. AWS ECS / Railway]
- Database hosting: [e.g. AWS RDS / Supabase]
Security Considerations
[Derived from tech-feasibility risks — data handling, auth, API security]
---
### File 5: `D:\AI\Startups\[slug]\STACK.md`
```markdown
# Tech Stack Guide — [Title]
## Stack Summary
[mvp_stack_summary from tech-stack]
## Full Stack Details
### Frontend: [frontend]
**Why chosen:** [from tech-stack justification]
**Key packages:** [list relevant packages for this type of product]
**Setup:**
```bash
npx create-next-app@latest frontend --typescript --tailwind --eslint
Backend: [backend]
Why chosen: [from tech-stack] Key packages:
pip install fastapi uvicorn sqlalchemy alembic python-dotenv
# or: npm install express typescript @types/node ts-node
Database: [database]
Why chosen: [from tech-stack] Setup:
# [database setup command]
AI/ML Layer: [ai_ml_stack]
Architecture: [from tech-stack AI/ML section] Cost estimate at launch: [monthly_cost_launch_inr]/month Cost at scale: [monthly_cost_scale_inr]/month Key consideration: [any cost scaling notes from tech-stack]
Infrastructure: [infra]
Region: India (AWS ap-south-1 / Azure Central India) Monthly cost estimate:
| Stage | Est. Cost |
|---|---|
| Launch | [monthly_cost_launch_inr] |
| 6 months | [derived] |
| 12 months | [monthly_cost_scale_inr] |
Payments
- India: Razorpay — [setup note]
- Global (when ready): Stripe
What NOT to Use
[From tech-stack "what not to use" section]
Environment Setup Checklist
- Node.js / Python installed
- Docker + Docker Compose installed
- Cloud CLI configured (AWS CLI / Azure CLI)
- API keys added to .env
- Database migrated
- Test suite passing
---
### File 6: `D:\AI\Startups\[slug]\ROADMAP.md`
```markdown
# Development Roadmap — [Title]
## MVP Definition
Build the minimum version a paying customer would use. No more.
### Must-Have (MVP):
[mvp_features from GTM and tech-feasibility — numbered list]
### Explicitly Excluded from MVP:
[What NOT to build — from GTM skill]
### What Can Be Manual Before Automation:
[From GTM "fake it till you make it" suggestions]
---
## Phase 0 — Setup (Week 1–2)
- [ ] GitHub repo created ✓
- [ ] Dev environment: Docker Compose with all services
- [ ] `.env.example` with all required variables
- [ ] CI/CD: GitHub Actions → test on PR, deploy on merge
- [ ] Database schema: initial migration
- [ ] Auth: [auth service] integrated
## Phase 1 — Core MVP (Weeks 3–10)
[MVP features broken into weekly chunks — 2-3 features per week]
**Week 3–4: [Feature 1 from mvp_features]**
- [ ] [specific task]
- [ ] [specific task]
- [ ] Tests written + passing
**Week 5–6: [Feature 2]**
- [ ] [specific task]
- [ ] [specific task]
**Week 7–8: [Feature 3]**
- [ ] [specific task]
- [ ] [specific task]
**Week 9–10: Polish + Beta**
- [ ] Error handling + loading states
- [ ] Mobile responsiveness
- [ ] Basic analytics (PostHog)
- [ ] Payment integration (Razorpay)
- [ ] Onboarding flow
## Phase 2 — First Customers (Months 3–6)
**Goal:** [phase1_target_customers] paying customers at [india_price_inr]/month
- [ ] Beta invite to first [X] users (India)
- [ ] Feedback loop: weekly calls with users
- [ ] Iterate on top 3 complaints
- [ ] Referral mechanism built
- [ ] Pricing page live
**Channels to activate:**
[primary_india_channels from GTM]
## Phase 3 — Growth (Months 6–18)
**Goal:** Expand to [expansion_order[1]] markets
- [ ] Localisation for [market]
- [ ] Partnership with [India distribution channel]
- [ ] Case studies from Phase 2 customers
- [ ] [expansion market] pricing + payments
## Key Metrics Dashboard
| Metric | Track From Day | Tool |
|--------|---------------|------|
| MRR | Week 1 | Razorpay dashboard |
| Churn | Month 1 | PostHog |
| CAC | Month 1 | Manual / PostHog |
| LTV | Month 3 | Calculated |
| NPS | Month 2 | Typeform |
---
## Working with Claude Code
When continuing development, run:
claude
Claude Code will read `CLAUDE.md` and understand the full context of this project. It will follow the tech stack, conventions, and architecture defined here without needing re-explanation.
Step 5 — Create GitHub repo for the tool
Run via Bash:
gh repo create RashiD2801/[slug] --public --description "[one-sentence value proposition]" --confirm 2>&1
If gh is not authenticated or the command fails, output the manual steps:
Manual repo creation:
1. Go to https://github.com/new
2. Name: [slug]
3. Description: [value prop]
4. Create repository
5. Then run:
cd D:\AI\Startups\[slug]
git init
git remote add origin https://github.com/RashiD2801/[slug].git
git add .
git commit -m "Initial commit: dev-ready documentation"
git push -u origin main
If gh works, continue:
cd "D:\AI\Startups\[slug]"
git init
git branch -M main
git remote add origin https://github.com/RashiD2801/[slug].git
git add .
git commit -m "feat: initial project setup with PRD, architecture, and stack documentation"
git push -u origin main
Step 6 — Also commit the dev folder to Ideas-and-systems
cd "D:\AI\Startups"
git add [slug]/
git commit -m "Add: dev kickstart for [title]"
git push
Step 7 — Report to user
Output:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
DEV REPOSITORY READY
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Project: [Title]
GitHub: https://github.com/RashiD2801/[slug]
Local: D:\AI\Startups\[slug]\
Files created:
README.md — project overview
PRD.md — full product requirements
CLAUDE.md — Claude Code instructions
ARCHITECTURE.md — system design
STACK.md — tech stack + setup guide
ROADMAP.md — development phases
To start building:
cd D:\AI\Startups\[slug]
claude
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━