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Octopus

Manage all your projects from one repo using AI coding assistants. Open Octopus in Cursor or Claude Code, and run skills (commit, deploy, start dev server, etc.) against any registered project — without copying config into each one.

"commit and push MyApp"
"deploy Backend"
"start react for Dashboard"

The agent resolves the project path, reads cached context, and runs everything in the right directory.

Why

  • One hub — keep your AI assistant rules and skills in one place, use them everywhere.
  • Token-efficient — project summaries are cached locally so the agent doesn't re-explore repos every session.
  • Shareable — all personal data lives in local/ (gitignored). The skills and rules are safe to share publicly.

Quick start

1. Clone

git clone https://github.com/your-username/Octopus.git
cd Octopus

2. Create your local config

mkdir -p local/maps
cp examples/repos.json local/repos.json
cp examples/preferences.json local/preferences.json

Edit local/repos.json with your actual project paths:

{
  "lastActive": "my-app",
  "projects": {
    "my-app": {
      "path": "/Users/you/Code/my-app",
      "added": "2025-01-01"
    }
  }
}

3. Open in your AI editor

Cursor: Open this folder. Rules in .cursor/rules/ and skills in skills/ are picked up automatically.

Claude Code: Open this folder. Instructions in CLAUDE.md are picked up automatically. Tell it to read the skills in skills/ on first use.

4. Start using it

"add project MyApp"          → registers a project
"map project MyApp"          → generates a cached summary
"commit and push MyApp"      → stages, commits, pushes
"deploy MyApp"               → builds and deploys
"start MyApp"                → starts the dev server
"start docker for MyApp"     → docker compose up

If you skip the project name, Octopus uses the last active project.

Repo structure

Octopus/
├── CLAUDE.md                    # Claude Code instructions (auto-loaded)
├── .cursor/rules/
│   └── octopus-core.mdc        # Cursor rules (auto-loaded)
├── skills/
│   ├── add-project.md          # Register a project
│   ├── map-project.md          # Cache a project summary
│   ├── commit-push.md          # Git commit and push
│   ├── deploy.md               # Build and deploy (Firebase/Vercel/Netlify)
│   ├── dev-server.md           # Start dev server
│   └── docker.md               # Docker Compose
├── examples/
│   ├── repos.json              # Example project registry
│   └── preferences.json        # Example preferences
└── local/                      # ← gitignored, your personal data
    ├── repos.json              # Your project registry
    ├── preferences.json        # Your response style preferences
    └── maps/
        └── MyProject.md        # Cached project summaries

Skills reference

Skill Trigger phrases What it does
add-project "add project", "register project", "use octopus" Finds a repo on disk, saves its path, auto-generates a summary
map-project "map project", "summarize project" Creates a cached summary so the agent has instant context
commit-push "commit", "push", "commit and push" Builds, stages, commits with auto-generated message, pushes
deploy "deploy", "ship", "publish" Builds and deploys (auto-detects Firebase/Vercel/Netlify)
dev-server "start", "dev", "run" Starts the dev server (auto-detects npm start/dev/docker)
docker "docker", "start docker", "start containers" Starts Docker Compose services

How token caching works

When you first register a project, Octopus scans it lightly (README, package.json, folder structure) and writes a summary to local/maps/<ProjectName>.md. On every future session, the agent reads this cached file instead of re-exploring the repo — saving significant tokens.

To refresh a stale summary: "refresh map for MyApp"

Customization

Add your own skills

Create a new .md file in skills/ with this format:

---
name: my-skill
description: What it does and when to trigger it.
---

# My skill

## Trigger phrases
- "do the thing"

## Steps
1. Step one
2. Step two

Both Cursor and Claude Code will pick it up.

Preferences

Edit local/preferences.json:

{
  "verbosity": "short",    // tiny | short | normal | detailed
  "preferBullets": true
}

Privacy

Everything in local/ is gitignored:

  • Your project paths stay on your machine
  • Cached summaries stay on your machine
  • No secrets or personal data are ever committed

The committed files (skills, rules, examples, README) contain no personal information and are safe to share publicly.

About

A single workspace of reusable AI agent skills you can run across other projects by name. Work from this repo; the agent uses a stored map of repo names to paths to run those skills in the right place.

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