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Planetscale

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BagelHole
planetscale

Operate MySQL-compatible databases on PlanetScale with branching workflows, safe migrations, and production rollouts.

Overview

PublisherBagelHole
RepositoryDevOps-Security-Agent-Skills
Skill nameplanetscale
Stars
1.1K
Forks
161
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by BagelHole on GitHub. Read the source before you install it.

Installation

Install the Planetscale AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/BagelHole/DevOps-Security-Agent-Skills/tree/main/infrastructure/databases/planetscale
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/BagelHole/DevOps-Security-Agent-Skills.git /tmp/DevOps-Security-Agent-Skills
mkdir -p .claude/skills
cp -r /tmp/DevOps-Security-Agent-Skills/infrastructure/databases/planetscale .claude/skills/planetscale
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Planetscale in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Planetscale on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Planetscale is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

PlanetScale

Use PlanetScale for serverless MySQL-compatible databases with non-blocking schema change workflows built on Vitess.

When to Use

  • You need a managed MySQL-compatible database with zero-downtime migrations.
  • Your team wants Git-like branching for schema development.
  • You are building a serverless or edge application that benefits from connection pooling.
  • You need horizontal sharding without managing Vitess directly.

Prerequisites

  • A PlanetScale account (free tier available).
  • The pscale CLI installed locally.
  • Node.js 18+ if using Prisma or other ORM integrations.

Install the pscale CLI

bash
# macOS
brew install planetscale/tap/pscale

# Linux (deb)
curl -fsSL https://github.com/planetscale/cli/releases/latest/download/pscale_linux_amd64.deb -o pscale.deb
sudo dpkg -i pscale.deb

# Verify installation
pscale version

# Authenticate
pscale auth login

Create and Manage Databases

bash
# Create a new database
pscale database create my-app --region us-east

# List databases
pscale database list

# Show database info
pscale database show my-app

# Delete a database (destructive)
pscale database delete my-app

Branching Workflow

PlanetScale branches work like Git branches for your database schema. The main branch is the production branch by default.

bash
# Create a development branch from main
pscale branch create my-app add-users-table

# List all branches
pscale branch list my-app

# Open a shell on the branch to apply schema changes
pscale shell my-app add-users-table

Apply Schema Changes on a Branch

sql
-- Inside the pscale shell on the development branch
CREATE TABLE users (
  id         BIGINT       NOT NULL AUTO_INCREMENT PRIMARY KEY,
  email      VARCHAR(255) NOT NULL,
  name       VARCHAR(255) NOT NULL,
  created_at TIMESTAMP    DEFAULT CURRENT_TIMESTAMP,
  updated_at TIMESTAMP    DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
  UNIQUE KEY idx_users_email (email)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

CREATE TABLE orders (
  id         BIGINT    NOT NULL AUTO_INCREMENT PRIMARY KEY,
  user_id    BIGINT    NOT NULL,
  total      DECIMAL(10,2) NOT NULL DEFAULT 0.00,
  status     ENUM('pending','paid','shipped','cancelled') DEFAULT 'pending',
  created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
  KEY idx_orders_user_id (user_id),
  KEY idx_orders_status (status)
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;

PlanetScale does not enforce foreign keys at the database level. Use application-level constraints or Vitess-level routing rules instead.

Deploy Requests

Deploy requests are the pull-request equivalent for database schemas. They show a diff, run linting, and merge non-blocking into production.

bash
# Create a deploy request from branch to main
pscale deploy-request create my-app add-users-table

# List open deploy requests
pscale deploy-request list my-app

# Show diff for a deploy request
pscale deploy-request diff my-app 1

# Deploy (merge) the request
pscale deploy-request deploy my-app 1

# Close without deploying
pscale deploy-request close my-app 1

# Delete the branch after successful deploy
pscale branch delete my-app add-users-table

Connection Strings and Proxying

bash
# Create a password (connection credential) for a branch
pscale password create my-app main production-creds

# Output includes host, username, and password for the connection string:
# mysql://USERNAME:PASSWORD@HOST/my-app?sslmode=verify_identity

# Proxy a branch to localhost for local development (no password needed)
pscale connect my-app add-users-table --port 3306

Environment Variable Pattern

bash
# .env (local development using pscale connect)
DATABASE_URL="mysql://root@127.0.0.1:3306/my-app"

# .env.production (using PlanetScale connection string)
DATABASE_URL="mysql://USERNAME:PASSWORD@us-east.connect.psdb.cloud/my-app?sslaccept=strict"

Prisma Integration

prisma
// prisma/schema.prisma
datasource db {
  provider     = "mysql"
  url          = env("DATABASE_URL")
  relationMode = "prisma"   // required — PlanetScale does not support foreign keys
}

model User {
  id        Int      @id @default(autoincrement())
  email     String   @unique
  name      String
  orders    Order[]
  createdAt DateTime @default(now())
  updatedAt DateTime @updatedAt
}

model Order {
  id        Int      @id @default(autoincrement())
  userId    Int
  total     Decimal  @db.Decimal(10, 2)
  status    String   @default("pending")
  user      User     @relation(fields: [userId], references: [id])
  createdAt DateTime @default(now())

  @@index([userId])
  @@index([status])
}
bash
# Push schema changes to the PlanetScale branch
npx prisma db push

# Generate the Prisma client
npx prisma generate

Vitess Features and Query Insights

bash
# Open the query insights dashboard
pscale shell my-app main

# Inside the shell, check running queries
SHOW PROCESSLIST;

# Examine query statistics (PlanetScale Insights tab in the web UI)
# Or use the API:
pscale api organizations/my-org/databases/my-app/branches/main/query-statistics

Useful Vitess-Aware Queries

sql
-- Check table sizes
SELECT table_name,
       ROUND(data_length / 1024 / 1024, 2) AS data_mb,
       ROUND(index_length / 1024 / 1024, 2) AS index_mb,
       table_rows
FROM information_schema.tables
WHERE table_schema = 'my-app'
ORDER BY data_length DESC;

-- Show index usage
SHOW INDEX FROM users;

-- Explain a query plan
EXPLAIN SELECT * FROM orders WHERE user_id = 42 AND status = 'paid';

Docker Setup for Local Development

Use a plain MySQL 8 container to mirror PlanetScale locally when you are offline or want fast iteration without the CLI proxy.

yaml
# docker-compose.yml
version: "3.9"

services:
  mysql:
    image: mysql:8.0
    restart: unless-stopped
    ports:
      - "3306:3306"
    environment:
      MYSQL_ROOT_PASSWORD: rootpass
      MYSQL_DATABASE: my-app
      MYSQL_USER: myapp
      MYSQL_PASSWORD: secret
    volumes:
      - mysql_data:/var/lib/mysql
      - ./init.sql:/docker-entrypoint-initdb.d/init.sql
    command: >
      --default-authentication-plugin=mysql_native_password
      --character-set-server=utf8mb4
      --collation-server=utf8mb4_unicode_ci

volumes:
  mysql_data:
bash
docker compose up -d
mysql -h 127.0.0.1 -u myapp -psecret my-app

Production Best Practices

  • Keep every schema change backward compatible; deploy the schema first, then the application code.
  • Use deploy request reviews as a gate; require at least one approval before merging.
  • Enable connection pooling (@planetscale/database driver or Prisma Data Proxy) for serverless workloads.
  • Monitor query insights weekly and add indexes for queries exceeding 100 ms.
  • Set branch promotion rules so only specific team members can deploy to main.
  • Use read-only regions to reduce latency for geographically distributed reads.

Troubleshooting

SymptomLikely CauseFix
Access denied on pscale connectCLI not authenticatedRun pscale auth login
Deploy request shows "schema conflict"Concurrent branch changes to the same tableRebase: delete branch, recreate from current main, reapply changes
foreign key constraint errorPlanetScale does not support foreign keysUse relationMode = "prisma" or remove FK definitions
High latency on readsNo index on queried columnAdd index via a new branch and deploy request
max connections exceededConnection pooling not enabledUse @planetscale/database serverless driver or PgBouncer-style proxy
pscale connect hangsFirewall blocking outbound TLSAllow outbound 443 to *.psdb.cloud

Related Skills

Frequently asked questions

What does the Planetscale AI skill do?

Operate MySQL-compatible databases on PlanetScale with branching workflows, safe migrations, and production rollouts.

Why use Planetscale on TypingMind?

Because you install it once and use it with any model. Planetscale is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Planetscale in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/BagelHole/DevOps-Security-Agent-Skills/tree/main/infrastructure/databases/planetscale. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Planetscale?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Planetscale?

As many as you like. As long as a model supports skills, you can use Planetscale with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Planetscale AI skill free?

Yes. It is published on GitHub by BagelHole under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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