VibeCollab — Setup Instructions for AI Assistants
This skill guides an AI assistant through the process of setting up VibeCollab in a user's project, including installation, initialization, and initial documentation generation.
About this skill
VibeCollab is a tool designed to facilitate project setup and documentation, particularly for projects leveraging AI agents. This skill enables an AI assistant to expertly configure VibeCollab from scratch. It handles verifying Python prerequisites, managing virtual environments, installing the `vibe-collab` package, and initializing the project with essential files like `project.yaml`, `CONTRIBUTING_AI.md`, and an initial `docs/` directory. A key feature for existing projects is the automated backfilling of documentation. The AI assistant can analyze git history to summarize the project's current state into `docs/CONTEXT.md` and record important architectural decisions in `docs/DECISIONS.md`. It also prompts for the creation of `docs/ROADMAP.md` based on future plans. This skill streamlines the initial integration of VibeCollab, ensuring projects are set up with a robust framework for AI-assisted development and collaborative documentation. It's ideal for developers looking to standardize their project setup and leverage AI for consistent, high-quality documentation from the outset.
Best use case
The primary use case is onboarding a project to VibeCollab, whether it's a new endeavor or an existing codebase needing structured documentation and AI agent collaboration protocols. Developers and teams who want to rapidly integrate VibeCollab's capabilities, especially those aiming to use AI assistants for coding and project management, benefit most. This skill ensures a consistent and automated setup, reducing manual effort and potential errors.
This skill guides an AI assistant through the process of setting up VibeCollab in a user's project, including installation, initialization, and initial documentation generation.
VibeCollab will be installed, initialized, and its core documentation structure created and potentially backfilled within the user's project, ready for AI-assisted collaboration.
Practical example
Example input
I need to set up VibeCollab for my new project. It's a 'web' application called 'ProjectSpark'.
Example output
VibeCollab has been successfully installed and initialized for 'ProjectSpark' (web project). The `project.yaml`, `CONTRIBUTING_AI.md`, and `docs/` directory are now created. If this is an existing project, I can help backfill `CONTEXT.md` and `DECISIONS.md` by reviewing your git commits.
When to use this skill
- To set up VibeCollab in a new Python project.
- To integrate VibeCollab into an existing Python codebase.
- When preparing a project for AI agent-assisted development and structured documentation.
- To automate the initial creation and population of project context, decisions, and roadmap documents.
When not to use this skill
- For projects not written in Python or not requiring Python 3.10+.
- If VibeCollab is already fully configured and running in the project.
- If the project does not require the structured documentation or AI agent collaboration features provided by VibeCollab.
- In environments where shell command execution is restricted or undesirable.
How VibeCollab — Setup Instructions for AI Assistants Compares
| Feature / Agent | VibeCollab — Setup Instructions for AI Assistants | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | easy | N/A |
Frequently Asked Questions
What does this skill do?
This skill guides an AI assistant through the process of setting up VibeCollab in a user's project, including installation, initialization, and initial documentation generation.
How difficult is it to install?
The installation complexity is rated as easy. You can find the installation instructions above.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# VibeCollab — Setup Instructions for AI Assistants
You are helping a user set up VibeCollab in their project.
Execute the following steps in order. Stop and report if any step fails.
## Prerequisites
VibeCollab requires **Python 3.10 or higher**. Recommended version: **Python 3.12** (best balance of performance and compatibility).
Before installing, check the user's Python version:
```bash
python --version
```
If Python is not installed or is below 3.10, guide the user to install Python 3.12+ from https://www.python.org/downloads/
**Virtual environment** (strongly recommended): To keep the user's system clean and avoid dependency conflicts, always create a virtual environment before installing:
```bash
# Create a virtual environment (run once)
python -m venv .venv
# Activate it
# On Windows:
.venv\Scripts\activate
# On macOS/Linux:
source .venv/bin/activate
```
> If the project already has a virtual environment (`.venv/`, `venv/`, or similar), activate it instead of creating a new one.
## Step 1: Install
```bash
pip install vibe-collab
```
## Step 2: Initialize
Run in the user's project root directory:
```bash
vibecollab init -n "<PROJECT_NAME>" -d <DOMAIN>
```
- `<PROJECT_NAME>`: Ask the user for their project name
- `<DOMAIN>`: Ask the user to choose: `web` / `mobile` / `game` / `data` / `generic`
This creates `project.yaml`, `CONTRIBUTING_AI.md`, and `docs/` directory with protocol documents.
### For Existing Projects
If the project already has code (not an empty directory), do the following **after** `vibecollab init`:
1. **Backfill CONTEXT.md**: Review recent git commits and summarize the project's current state, active tasks, and recent decisions into `docs/CONTEXT.md`
2. **Backfill DECISIONS.md**: Look for important architectural choices in git history and record them in `docs/DECISIONS.md` with proper decision levels (S/A/B/C)
3. **Create ROADMAP.md**: If the project has future plans, create `docs/ROADMAP.md` following the milestone format (see ROADMAP Format section below)
4. **Capture Insights**: If reusable development experiences are found (debugging tricks, architectural patterns, workflow optimizations), capture them using `insight_add` MCP tool
### Quick Start After Init
After initialization completes, tell the user:
> VibeCollab is ready! Here's how to start:
>
> 1. **Describe your current task** — I'll help you work on it while following the collaboration protocol
> 2. **Or say "onboard"** — I'll read the project context and suggest what to do next
> 3. **Or show me a file/feature** — I'll understand it within the project's structured context
This gives users an immediate path forward instead of leaving them wondering "what now?"
## Step 3: Connect MCP to IDE
Ask the user which IDE they use, then run:
```bash
vibecollab mcp inject --ide cursor # or: cline / codebuddy / all
```
This injects VibeCollab MCP Server config into the IDE config file.
Use `--ide all` to inject config for all supported IDEs at once.
**OpenClaw / other MCP agents**: VibeCollab is a standard MCP Server. Any MCP-compatible agent can connect directly:
```bash
openclaw mcp add --transport stdio vibecollab vibecollab mcp serve
```
## Step 4: Verify
```bash
vibecollab check
```
Should return zero errors. Warnings about document staleness are normal for new projects. Insight consistency checks are included by default (use `--no-insights` to skip).
## Setup Complete
VibeCollab is ready. You now have MCP tools available in your IDE:
| Tool | When to use |
|------|-------------|
| `onboard` | **Start of every conversation** — get project context |
| `check` | **End of every conversation** — verify protocol compliance |
| `next_step` | When unsure what to do next |
| `insight_search` | Search past development experience |
| `insight_add` | Save a reusable insight |
| `insight_suggest` | Get signal-driven insight recommendations |
| `insight_graph` | View insight relationship graph |
| `insight_export` | Export insights in YAML format |
| `search_docs` | Semantic search across project documents |
| `task_list` | List current tasks |
| `task_create` | Create a new task (auto-links insights) |
| `task_transition` | Move task status (TODO → IN_PROGRESS → REVIEW → DONE) |
| `developer_context` | Get a specific role's context |
| `project_prompt` | Generate full context prompt |
| `roadmap_status` | View milestone progress |
| `roadmap_sync` | Sync ROADMAP.md <-> tasks.json |
| `session_save` | **End of conversation** — save session summary |
## Execution Plan — YAML-Driven Workflow Automation
VibeCollab includes a plan runner that orchestrates multi-round workflows with two modes:
| Mode | Command | Host Adapter | Description |
|------|---------|-------------|-------------|
| **File Exchange** | `vibecollab plan run --host file_exchange` | `file_exchange` | File polling with IDE AI (requires IDE rules setup) |
| **Subprocess** | `vibecollab plan run --host subprocess` | `subprocess` | Drives CLI tools (aider, claude) via stdin/stdout |
| **Auto (Keyboard)** | `vibecollab plan run --host auto:cursor` | `auto` | Keyboard simulation for hands-free IDE automation |
All modes use `vibecollab plan run` as the **unified execution engine**.
### Mode 1: File Exchange
Use when you want to stay in the IDE conversation and have AI execute plan steps.
```bash
vibecollab plan run plans/dev.yaml -v
```
**How it works**: vibecollab writes instructions to a file, IDE AI monitors and executes, writes response back.
```
vibecollab plan run IDE AI (Cursor/Cline)
│ │
│ write instruction.md │
├──────────────────────────────->│
│ │ execute with tool-use
│ poll response.md │
│<───────────────────────────────┤ write response
│ │
│ check goal, next round │
└────────────────────────────────┘
```
**Limitation**: Requires active IDE conversation. If conversation ends, loop stops.
**IDE Setup** — Add to Cursor Rules or Cline Custom Instructions:
```
Monitor .vibecollab/loop/instruction.md for new instructions.
When you see <!-- VIBECOLLAB_INSTRUCTION -->, execute the task using your tools.
After completion, write results to .vibecollab/loop/response.md and include
<!-- VIBECOLLAB_RESPONSE_READY --> at the end to signal completion.
```
### Mode 2: Auto (Keyboard Simulation)
Use when you want hands-free automation that can run for hours. The `auto` host adapter drives IDE AI through keyboard simulation (pyautogui).
**Step 1**: Create a launcher script
```bash
vibecollab auto init plans/dev.yaml --ide cursor
```
This creates `auto_dev.bat` that runs `vibecollab plan run ... --host auto:cursor`.
**Step 2**: Double-click the .bat file to start
- A cmd window opens
- Auto adapter finds IDE window, simulates Ctrl+L → paste → Enter
- PlanRunner polls response.md for completion
- Loop continues until goal met or max rounds
**How it works**:
```
vibecollab plan run --host auto:cursor IDE Window (Cursor/Cline)
│ │
│ PlanRunner._exec_loop() │
│ → AutoAdapter.send(instruction) │
│ → pyautogui: Ctrl+L │
│ → paste instruction via clipboard │
│ → Enter │
├──────────────────────────────────────->│
│ │ AI executes task
│ <- poll response.md │
│<────────────────────────────────────────┤ write response
│ │
│ check_goal() → next round │
└─────────────────────────────────────────┘
```
**Requirements**: `pip install vibe-collab[auto]` (includes pyautogui, pygetwindow, pyperclip)
**Commands**:
```bash
vibecollab auto list # Show preset plans
vibecollab auto init --preset dev-loop # Copy preset & create .bat launcher
vibecollab auto init plans/custom.yaml # Create .bat from local plan
vibecollab auto status # Check status
vibecollab auto stop # Stop running process
# Direct CLI usage (equivalent to double-clicking .bat):
vibecollab plan run plans/dev.yaml --host auto:cursor -v
```
### Preset Plans
VibeCollab includes ready-to-use automation plans:
| Plan | Purpose | Rounds |
|------|---------|--------|
| `dev-loop` | **Full development cycle** — onboard, develop, insight, check | 50 |
| `feature-dev` | **Feature implementation** — follow ROADMAP tasks | 30 |
| `quick-fix` | **Bug fixes** — rapid check-fix-commit loop | 10 |
| `doc-sync` | **Documentation** — sync CONTEXT/CHANGELOG/ROADMAP | 5 |
| `insight-harvest` | **Knowledge capture** — extract insights from work | 10 |
**Quick Start**:
```bash
# List available presets
vibecollab auto list
# Use a preset plan (copies to plans/ and creates .bat)
vibecollab auto init --preset dev-loop
# Double-click the generated .bat file to start!
```
### Example Plan
```yaml
name: "Iterate project"
host: file_exchange
steps:
- action: loop
max_rounds: 20
goal: "All vibecollab checks pass"
state_command: "vibecollab next --json"
prompt_template: |
## Round {{round}}/{{max_rounds}}
Current state:
{{state}}
Please complete the next recommended task using your tools.
Run `vibecollab check` when done.
check_command: "vibecollab check"
check_expect:
exit_code: 0
```
### CLI Commands
```bash
vibecollab plan run <plan.yaml> # Execute (default: file_exchange)
vibecollab plan run <plan.yaml> -v # Verbose logging
vibecollab plan run <plan.yaml> --host auto:cursor # Auto adapter (keyboard simulation)
vibecollab plan run <plan.yaml> --dry-run # Preview only
vibecollab plan validate <plan.yaml> # Validate syntax
```
### Plan Step Actions
| Action | Purpose | Example |
|--------|---------|---------|
| `cli` | Run shell command | `command: "vibecollab check"` |
| `assert` | Check file/content | `file: "README.md"`, `contains: "test"` |
| `wait` | Delay | `seconds: 1` |
| `prompt` | Send single message to host | `message: "Create a task"` |
| `loop` | Multi-round iteration | `max_rounds: 20`, `state_command: "..."` |
### Loop Configuration
| Field | Description |
|-------|-------------|
| `max_rounds` | Maximum iteration rounds |
| `goal` | Human-readable goal description |
| `state_command` | Command to gather current project state |
| `prompt_template` | Template with `{{state}}`, `{{round}}`, `{{max_rounds}}`, `{{goal}}` |
| `check_command` | Command to test if goal is met |
| `check_expect` | Expected `exit_code` and/or `stdout_contains` |
### Host Adapters
| Host | Config | Use Case |
|------|--------|----------|
| `file_exchange` | `host: file_exchange` | **Cursor/Cline/CodeBuddy** — drives IDE AI via file polling |
| `subprocess` | `host: {type: subprocess, command: "aider"}` | CLI tools (aider, claude, etc.) with stdin/stdout |
| `auto` | `host: auto:cursor` or `--host auto:cursor` | **Cursor/Cline/CodeBuddy** — drives IDE AI via keyboard simulation (pyautogui) |
> The `auto` adapter supports IDE sub-options via colon syntax: `auto:cursor`, `auto:cline`, `auto:codebuddy`. Default: `auto:cursor`.
### Auto Adapter Options
```yaml
host:
type: auto:cursor # or auto:cline, auto:codebuddy
response_timeout: 600 # wait up to 10 minutes per round (default: 600)
poll_interval: 5 # check every 5 seconds (default: 5)
```
Or via CLI flag:
```bash
vibecollab plan run plans/dev.yaml --host auto:cursor -v
```
### File Exchange Options
```yaml
host:
type: file_exchange
timeout: 600 # wait up to 10 minutes per round (default: 300)
poll_interval: 3 # check every 3 seconds (default: 2)
exchange_dir: ".vibecollab/loop" # directory for exchange files
```
### Variable Passing
Steps can store output and pass to later steps:
```yaml
steps:
- action: cli
command: "vibecollab health --json"
store_as: health_data
- action: prompt
message: "Health report: {{health_data}}"
```
## ROADMAP Format
If the project has a `docs/ROADMAP.md`, milestones must use this format for `roadmap_status` / `roadmap_sync` to work:
```markdown
### v0.1.0 - Milestone title
- [ ] Feature description (TASK-DEV-001)
- [x] Completed feature TASK-DEV-002
```
- Only `###` (H3) headers are recognized — `####` or `##` will not be parsed
- Version must start with `v` (semantic versioning)
- Task IDs follow `TASK-{ROLE}-{SEQ}` format (e.g., `TASK-DEV-001`)
## Daily Workflow
```
Conversation start → call onboard
↓
Work on tasks
↓
Reusable experience? → call insight_add (capture knowledge)
↓
Need past experience? → call insight_search
↓
Important decisions → record in docs/DECISIONS.md
↓
Conversation end → update docs/CONTEXT.md
→ update docs/CHANGELOG.md
→ call check (includes Insight consistency by default)
→ call session_save
→ git commit
```
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