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Vault

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GadaaLabs
vault

Use when starting feature work that needs isolation from the current workspace, or before executing implementation plans — creates isolated git worktrees with smart directory selection and safety verification

Overview

PublisherGadaaLabs
Repositoryclaude-code-on-steroids
Skill namevault
Stars
67
Forks
10
Bundled files
Instructions only
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 GadaaLabs on GitHub. Read the source before you install it.

Installation

Install the Vault 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.
  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/GadaaLabs/claude-code-on-steroids.git /tmp/claude-code-on-steroids
mkdir -p .claude/skills
cp -r /tmp/claude-code-on-steroids/skills/vault .claude/skills/vault
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Vault 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 Vault 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 Vault 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.

Using Git Worktrees

Overview

VAULTA vault is a sealed, isolated chamber — what happens inside cannot contaminate what's outside. When invoked: creates an isolated git worktree so implementation work is completely separated from the main branch — parallel agents cannot corrupt each other's state, and breaking changes stay contained until verified.

Core principle: Systematic directory selection + safety verification = reliable isolation.

Announce at start: "Running VAULT to set up an isolated workspace."


Directory Selection Process

Follow this priority order:

1. Check Existing Directories

bash
ls -d .worktrees 2>/dev/null     # Preferred (hidden)
ls -d worktrees 2>/dev/null      # Alternative

If found: use that directory. If both exist, .worktrees/ wins.

2. Check CLAUDE.md

bash
grep -i "worktree.*director" CLAUDE.md 2>/dev/null

If a preference is specified: use it without asking.

3. Ask the User

If no directory exists and no CLAUDE.md preference:

No worktree directory found. Where should I create worktrees?

1. .worktrees/ (project-local, hidden)
2. ~/.config/superpowers/worktrees/<project-name>/ (global)

Which would you prefer?

Safety Verification

For Project-Local Directories (.worktrees/ or worktrees/)

MUST verify the directory is gitignored before creating the worktree:

bash
git check-ignore -q .worktrees 2>/dev/null || git check-ignore -q worktrees 2>/dev/null

If NOT ignored — fix immediately:

  1. Add the line to .gitignore
  2. Commit the change
  3. Then proceed with worktree creation

Why critical: Prevents accidentally committing worktree contents to the repository.

For Global Directory (~/.config/superpowers/worktrees/)

No .gitignore verification needed — it's outside the project entirely.


Creation Steps

1. Detect Project Name

bash
project=$(basename "$(git rev-parse --show-toplevel)")

2. Create the Worktree

bash
git worktree add "$path" -b "$BRANCH_NAME"
cd "$path"

3. Run Project Setup (auto-detect)

bash
if [ -f package.json ];      then npm install; fi
if [ -f Cargo.toml ];        then cargo build; fi
if [ -f requirements.txt ];  then pip install -r requirements.txt; fi
if [ -f pyproject.toml ];    then poetry install; fi
if [ -f go.mod ];            then go mod download; fi

4. Verify Clean Baseline

bash
# Use the project's test command
npm test / cargo test / pytest / go test ./...
  • Tests fail → report failures, ask whether to proceed or investigate
  • Tests pass → report ready

5. Report Location

Worktree ready at <full-path>
Tests passing (<N> tests, 0 failures)
Ready to implement <feature-name>

Quick Reference

SituationAction
.worktrees/ existsUse it (verify ignored)
worktrees/ existsUse it (verify ignored)
Both existUse .worktrees/
Neither existsCheck CLAUDE.md → ask user
Directory not gitignoredAdd to .gitignore + commit first
Tests fail at baselineReport failures + ask before proceeding
No package.json / Cargo.tomlSkip dependency install

Red Flags

Never:

  • Create a project-local worktree without verifying it is gitignored
  • Skip baseline test verification
  • Proceed with failing tests without asking
  • Assume directory location when ambiguous
  • Skip the CLAUDE.md check

Always:

  • Priority order: existing directory > CLAUDE.md preference > ask user
  • Verify gitignore for project-local directories
  • Auto-detect and run project setup
  • Confirm clean test baseline before handing off

Integration

Called by:

  • architect — required when design is approved and implementation follows
  • phantom — required before executing any plan tasks
  • exodus — required before executing any plan tasks

Pairs with:

  • seal — cleans up the worktree after work is complete

Frequently asked questions

What does the Vault AI skill do?

Use when starting feature work that needs isolation from the current workspace, or before executing implementation plans — creates isolated git worktrees with smart directory selection and safety verification

Why use Vault on TypingMind?

Because you install it once and use it with any model. Vault 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 Vault in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/GadaaLabs/claude-code-on-steroids/tree/main/skills/vault. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Vault?

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 Vault?

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

Is the Vault AI skill free?

It is published on GitHub by GadaaLabs. Check the repository for licensing terms. 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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