Planetscale Pscale Cli Automation

Organization

planetscale

planetscale-pscale-cli-automation

Use the PlanetScale CLI (pscale) from automated agents with --format json, auth check, pscale sql, and per-command --force. Run before other PlanetScale skills when driving pscale directly. Use when the user asks to automate pscale, run CLI commands headless, or verify pscale auth from an agent.

Overview

Publisher	planetscale
Repository	`skills`
Skill name	`planetscale-pscale-cli-automation`
Stars	136
Forks	6
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

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 planetscale on GitHub. Read the source before you install it.

Installation

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

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/planetscale/skills/tree/main/planetscale-pscale-cli-automation
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.

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/planetscale/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/planetscale-pscale-cli-automation .claude/skills/planetscale-pscale-cli-automation

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Planetscale Pscale Cli Automation 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 Pscale Cli Automation 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 Pscale Cli Automation 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 CLI automation

Purpose

Teach agents how to invoke pscale non-interactively. This skill covers CLI conventions only. Operational workflows (inventory, safety review, schema recommendations) use the other skills in this repo — start with ../planetscale-safe-orchestrator/SKILL.md for a full assessment.

Two AGENTS.md files (do not confuse them)

Document	Where	Purpose
CLI agent guide	Shipped with `pscale` (`AGENTS.md` in the CLI repo, or `pscale agent-guide`)	How to call `pscale`: auth, `--format json`, flag placement, `pscale sql`
Project agent guide	Your application repository's `AGENTS.md`	Which org, database, branch, engine, prod branch, MCP scope, approval rules

Do not edit project AGENTS.md without operator approval (see ../planetscale-mcp-agent-operating-model/SKILL.md).

Bootstrap (always start here)

bash
pscale agent-guide --format json
pscale auth check --format json

If auth check returns "status": "action_required", follow issues and next_steps in the JSON. For login, the human may need to approve in the browser; use pscale auth login --format json.

Conventions

Always pass --format json for automation.
Put --org <org> on resource subcommands (database, branch, sql, api, …) — not on root pscale.
Put positional arguments before flags (pscale sql mydb main --org bb …).
Use pscale sql, not pscale shell (shell requires a TTY).
Default SQL role is reader; pass --role admin (or writer/readwriter) for writes. Match pscale shell semantics for --role and --replica.
--force is per subcommand only (e.g. database delete … --force, pscale sql … --force). There is no global --force or PSCALE_FORCE.
--format json alone never skips confirmations — add --force on the destructive subcommand after explicit user approval.

Typical workflow

bash
pscale auth check --format json
pscale org list --format json
pscale database list --org <org> --format json
pscale branch list <database> --org <org> --format json
pscale sql <database> <branch> --org <org> --format json --query "SELECT 1"

MySQL uses @primary by default (same as pscale shell); pass --keyspace only for multi-keyspace databases.

MCP vs CLI

MCP clients — use the hosted PlanetScale MCP server (see pscale agent-guide --format json for the current URL).
Shell scripts and coding agents — use pscale with --format json as above.

When this skill is not enough

Install the full PlanetScale skills pack (if not already):

sh
git clone https://github.com/planetscale/skills.git && cd skills && script/setup
# or: npx skills add planetscale/skills -g -y

Then run sub-skills or ../planetscale-safe-orchestrator/SKILL.md for database operations beyond basic CLI invocation.

Current conventions source of truth

Prefer live output over memorized flag syntax:

bash
pscale agent-guide --format json

The embedded guide field contains the full CLI agent guide shipped with your pscale binary.

Frequently asked questions

What does the Planetscale Pscale Cli Automation AI skill do?

Why use Planetscale Pscale Cli Automation on TypingMind?

Because you install it once and use it with any model. Planetscale Pscale Cli Automation 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 Pscale Cli Automation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/planetscale/skills/tree/main/planetscale-pscale-cli-automation. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Planetscale Pscale Cli Automation?

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 Pscale Cli Automation?

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

Is the Planetscale Pscale Cli Automation AI skill free?

Yes. It is published on GitHub by planetscale 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

PlanetScale CLI automation

Purpose

Two AGENTS.md files (do not confuse them)

Bootstrap (always start here)

Conventions

Typical workflow

MCP vs CLI

When this skill is not enough

Current conventions source of truth

Frequently asked questions

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