build-and-deploy — community build-and-deploy, langchain-retrieval-agent, community, ide skills, Claude Code, Cursor, Windsurf

v1.0.0
GitHub

About this Skill

Perfect for LangChain Agents needing streamlined deployment to Vercel with vector store integration. LangChain.js agent with retrieval tool powered by LangGraph, Supabase vector store, and the Vercel AI SDK

rebyteai-template rebyteai-template
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Updated: 3/5/2026

Agent Capability Analysis

The build-and-deploy skill by rebyteai-template is an open-source community AI agent skill for Claude Code and other IDE workflows, helping agents execute tasks with better context, repeatability, and domain-specific guidance.

Ideal Agent Persona

Perfect for LangChain Agents needing streamlined deployment to Vercel with vector store integration.

Core Value

Empowers agents to deploy LangChain retrieval tools powered by LangGraph, Supabase vector store, and the Vercel AI SDK, ensuring seamless integration and efficient deployment using `vercel build --prod` and `vercel deploy --prebuilt --prod` commands.

Capabilities Granted for build-and-deploy

Deploying LangChain retrieval agents to Vercel for production environments
Configuring environment variables for secure deployment
Integrating Supabase vector store for efficient data retrieval

! Prerequisites & Limits

  • Requires Vercel account and project setup
  • Must use `vercel build --prod` and `vercel deploy --prebuilt --prod` for successful deployment
  • Git author permission issues may arise in VM environments if not using recommended commands
Labs Demo

Browser Sandbox Environment

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Experience this Agent in a zero-setup browser environment powered by WebContainers. No installation required.

Boot Container Sandbox

build-and-deploy

Install build-and-deploy, an AI agent skill for AI agent workflows and automation. Works with Claude Code, Cursor, and Windsurf with one-command setup.

SKILL.md
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Build and Deploy LangChain Retrieval Agent

CRITICAL: For Vercel, you MUST use vercel build --prod then vercel deploy --prebuilt --prod. Do NOT use vercel --prod or vercel deploy --prod directly - these will fail due to Git author permission issues in VM environments.

Workflow

1. Setup Environment Variables

Read .env.example to see all required variables:

bash
1cat .env.example

Create .env by reading values from current environment:

For each variable in .env.example, read the value from the current environment and write to .env. Example approach:

bash
1# Read .env.example and create .env with values from current environment 2while IFS= read -r line || [[ -n "$line" ]]; do 3 # Skip comments and empty lines 4 [[ "$line" =~ ^#.*$ || -z "$line" ]] && continue 5 # Extract variable name (before = sign) 6 var_name=$(echo "$line" | cut -d'=' -f1) 7 # Get value from environment 8 var_value="${!var_name}" 9 # Write to .env 10 echo "${var_name}=${var_value}" >> .env 11done < .env.example

Or manually inspect .env.example and create .env with the required values from environment variables.

2. Install Dependencies

bash
1yarn install

3. Setup Supabase Vector Store

Get the database connection URL from Supabase Dashboard:

  • Go to Settings → Database → Connection string → URI
  • Copy the URI and add it to .env as SUPABASE_DB_URL
bash
1yarn setup-db

This creates the pgvector extension, documents table, and match_documents function in your Supabase project.

4. Build

bash
1yarn build

5. Deploy

Vercel:

All vercel CLI commands require -t <token> or --token <token> for authentication.

bash
1# Pull project settings (also links project, creates .vercel/project.json) 2vercel pull --yes -t $VERCEL_TOKEN 3 4# Push env vars to Vercel (first time only) 5# Must add to each environment separately 6while IFS='=' read -r key value; do 7 [[ "$key" =~ ^#.*$ || -z "$key" || -z "$value" ]] && continue 8 for env in production preview development; do 9 printf '%s' "$value" | vercel env add "$key" $env -t $VERCEL_TOKEN 10 done 11done < .env 12 13# Build locally for production 14vercel build --prod -t $VERCEL_TOKEN 15 16# Deploy prebuilt 17vercel deploy --prebuilt --prod --yes -t $VERCEL_TOKEN

Netlify:

bash
1# Import all env vars from .env (first time only) 2netlify env:import .env 3 4# Deploy 5netlify deploy --prod

Critical Notes

  • VERCEL PREBUILT MODE IS MANDATORY: Always use vercel build --prod followed by vercel deploy --prebuilt --prod. Never use vercel --prod or vercel deploy --prod without --prebuilt flag.
  • Supabase Required: Need a Supabase project (free tier works)
  • Vector Store Setup: Run yarn setup-db to create tables automatically
  • Environment Variables: All values come from current environment - inspect .env.example for required variables
  • OpenAI for Embeddings: OPENAI_API_KEY is always required for vector embeddings
  • No Dev Server: Never run yarn dev in VM environment

FAQ & Installation Steps

These questions and steps mirror the structured data on this page for better search understanding.

? Frequently Asked Questions

What is build-and-deploy?

Perfect for LangChain Agents needing streamlined deployment to Vercel with vector store integration. LangChain.js agent with retrieval tool powered by LangGraph, Supabase vector store, and the Vercel AI SDK

How do I install build-and-deploy?

Run the command: npx killer-skills add rebyteai-template/langchain-retrieval-agent. It works with Cursor, Windsurf, VS Code, Claude Code, and 19+ other IDEs.

What are the use cases for build-and-deploy?

Key use cases include: Deploying LangChain retrieval agents to Vercel for production environments, Configuring environment variables for secure deployment, Integrating Supabase vector store for efficient data retrieval.

Which IDEs are compatible with build-and-deploy?

This skill is compatible with Cursor, Windsurf, VS Code, Trae, Claude Code, OpenClaw, Aider, Codex, OpenCode, Goose, Cline, Roo Code, Kiro, Augment Code, Continue, GitHub Copilot, Sourcegraph Cody, and Amazon Q Developer. Use the Killer-Skills CLI for universal one-command installation.

Are there any limitations for build-and-deploy?

Requires Vercel account and project setup. Must use `vercel build --prod` and `vercel deploy --prebuilt --prod` for successful deployment. Git author permission issues may arise in VM environments if not using recommended commands.

How To Install

  1. 1. Open your terminal

    Open the terminal or command line in your project directory.

  2. 2. Run the install command

    Run: npx killer-skills add rebyteai-template/langchain-retrieval-agent. The CLI will automatically detect your IDE or AI agent and configure the skill.

  3. 3. Start using the skill

    The skill is now active. Your AI agent can use build-and-deploy immediately in the current project.

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