Deploy Vercel integrations to Vercel, Fly.io, and Cloud Run platforms. Use when deploying Vercel-powered applications to production, configuring platform-specific secrets, or setting up deployment pipelines. Trigger with phrases like "deploy vercel", "vercel Vercel", "vercel production deploy", "vercel Cloud Run", "vercel Fly.io".
Installation
Details
Usage
After installing, this skill will be available to your AI coding assistant.
Verify installation:
skills listSkill Instructions
name: vercel-deploy-integration description: | Deploy Vercel integrations to Vercel, Fly.io, and Cloud Run platforms. Use when deploying Vercel-powered applications to production, configuring platform-specific secrets, or setting up deployment pipelines. Trigger with phrases like "deploy vercel", "vercel Vercel", "vercel production deploy", "vercel Cloud Run", "vercel Fly.io". allowed-tools: Read, Write, Edit, Bash(vercel:), Bash(fly:), Bash(gcloud:*) version: 1.0.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io
Vercel Deploy Integration
Prerequisites
- Vercel API keys for production environment
- Platform CLI installed (vercel, fly, or gcloud)
- Application code ready for deployment
- Environment variables documented
Instructions
Step 1: Choose Deployment Platform
Select the platform that best fits your infrastructure needs and follow the platform-specific guide below.
Step 2: Configure Secrets
Store Vercel API keys securely using the platform's secrets management.
Step 3: Deploy Application
Use the platform CLI to deploy your application with Vercel integration.
Step 4: Verify Health
Test the health check endpoint to confirm Vercel connectivity.
Output
- Application deployed to production
- Vercel secrets securely configured
- Health check endpoint functional
- Environment-specific configuration in place
Error Handling
See {baseDir}/references/errors.md for comprehensive error handling.
Examples
See {baseDir}/references/examples.md for detailed examples.
Resources
More by jeremylongshore
View allOauth Callback Handler - Auto-activating skill for API Integration. Triggers on: oauth callback handler, oauth callback handler Part of the API Integration skill category.
Rabbitmq Queue Setup - Auto-activating skill for Backend Development. Triggers on: rabbitmq queue setup, rabbitmq queue setup Part of the Backend Development skill category.
evaluating-machine-learning-models: This skill allows Claude to evaluate machine learning models using a comprehensive suite of metrics. It should be used when the user requests model performance analysis, validation, or testing. Claude can use this skill to assess model accuracy, precision, recall, F1-score, and other relevant metrics. Trigger this skill when the user mentions "evaluate model", "model performance", "testing metrics", "validation results", or requests a comprehensive "model evaluation".
building-neural-networks: This skill allows Claude to construct and configure neural network architectures using the neural-network-builder plugin. It should be used when the user requests the creation of a new neural network, modification of an existing one, or assistance with defining the layers, parameters, and training process. The skill is triggered by requests involving terms like "build a neural network," "define network architecture," "configure layers," or specific mentions of neural network types (e.g., "CNN," "RNN," "transformer").
