Init

Purpose: Bootstrap AI assistant with project-specific information Usage: /init [--quick] [--update] Output: Populated project configuration files in .ai-project/

Constraints

• •Interactive workflow -- Do NOT skip confirmation questions
• •Replace ALL placeholders -- No {{PLACEHOLDER}} variables may remain unfilled in generated files (see references/template-variables.md)
• •Preserve existing customizations when using --update
• •Ask before overwriting if .ai-project/ already exists

Generated Files

Workflow

Phase 0: Create Project Layer

Step 0.1: Check for Existing Project Layer

ls -la .ai-project 2>/dev/null

If .ai-project/ exists, ask user:

• •Overwrite: Replace with fresh template
• •Update: Keep existing, only add missing files
• •Skip: Proceed to analysis without copying

Step 0.2: Copy Project Template

Copy the template from assets/ai-project/ within this skill directory to .ai-project/ at the project root.

cp -r <skill-dir>/assets/ai-project .ai-project

# Verify structure
ls -la .ai-project/

The assets/ai-project/ directory contains all scaffolding templates for project configuration, domains, workflows, todos, history, decisions, and file-lists. Refer to assets/ for the full directory structure.

Phase 1: Analyze Project

Step 1.1: Read Package Configuration

cat package.json 2>/dev/null || cat Cargo.toml 2>/dev/null || cat pyproject.toml 2>/dev/null

Extract:

• •Project name
• •Dependencies
• •Available scripts
• •Build tools

Step 1.2: Understand Directory Structure

find . -type f \( -name "*.ts" -o -name "*.tsx" -o -name "*.js" -o -name "*.jsx" \) \
  | grep -v node_modules | grep -v dist | head -50
tree -I 'node_modules|dist|.git' -L 3 2>/dev/null

Extract: source directories, test locations, configuration files, entry points.

Step 1.3: Identify Patterns

head -30 src/components/*.tsx 2>/dev/null | head -50
head -30 src/**/*.spec.ts 2>/dev/null | head -50
grep -rn "^import" src/ --include="*.ts" | head -20

Extract: component structure, test patterns, import conventions, naming conventions.

Step 1.4: Identify Tech Stack

Detect: framework, test framework, build tool, linter (ESLint), formatter (Prettier).

Phase 1.5: Interactive Confirmation

Present detected configuration and ask for confirmation:

## Project Analysis Complete

## Project Analysis Results

### Basic Info
| Field | Detected Value | Correct? |
|-------|----------------|----------|
| Project Name | `my-app` | ? |
| Project Type | Web Application | ? |

### Tech Stack
| Layer | Detected | Correct? |
|-------|----------|----------|
| Language | TypeScript 5.x | ? |
| Framework | React 18 | ? |
| Build Tool | Vite | ? |
| Test Framework | Vitest | ? |
| Package Manager | npm | ? |

### Commands
| Task | Detected Command | Correct? |
|------|------------------|----------|
| Dev | `npm run dev` | ? |
| Build | `npm run build` | ? |
| Test | `npm run test` | ? |
| Lint | `npm run lint` | ? |
| Type Check | `npm run typecheck` | ? |

---
**Is this detection accurate?**

**Confirm detection accuracy:** (yes / fix: [field]=[value] / show more)

GATE: Wait for confirmation before proceeding.

Phase 1.6: Gather Preferences

Ask about project conventions:

## Project Preferences

A few questions to complete setup:

### Git Workflow
1. **Main branch name?**
   Default: `main`

2. **Feature branch pattern?**
   Examples: `feature/description`, `ft/TICKET-description`
   Default: `feature/[description]`

### Commit Style
3. **Commit message format?**
   - (A) Conventional: `feat: add login`
   - (B) Ticket prefix: `PROJ-123: Add login`
   - (C) Simple: `Add login feature`
   Default: (A) Conventional

### Testing
4. **Test file location?**
   - (A) Co-located: `Component.spec.ts` next to `Component.ts`
   - (B) Separate: `tests/` directory
   - (C) Both
   Default: (A) Co-located

---
**Select preferences:** (provide answers or accept defaults)

GATE: Wait for preferences before generating files.

Phase 2: Generate Configuration

CRITICAL: Replace ALL {{PLACEHOLDER}} variables with actual values from detection and user input. See references/template-variables.md for the full variable table and population rules.

Step 2.1-2.4: Write Project Files

Generate the following files using detected values and user preferences. See references/template-variables.md for example output formats:

• •.ai-project/project/commands.md -- Based on package.json scripts
• •.ai-project/project/structure.md -- Based on directory analysis
• •.ai-project/project/patterns.md -- Based on code analysis
• •.ai-project/project/stack.md -- Based on dependencies

Step 2.5: Generate Domain Context Files

Detect stack components and generate project-specific domain instruction files. See references/domain-detection.md for the full detection table, generation rules, and example output.

Step 2.6: Update Project Entry Point

Generate/update CLAUDE.md at the project root using assets/CLAUDE.md as the template:

• •Replace all {{PLACEHOLDER}} variables with detected values
• •If a CLAUDE.md already exists, merge new content below any existing user content
• •The template is minimal by design -- project name, stack summary, key commands, and a pointer to .ai-project/
• •Remove table rows for commands that don't exist (e.g., no typecheck script)
• •Replace {{CONVENTION_*}} placeholders with 2-4 actual project conventions detected from the codebase (e.g., "Use PascalCase for components", "Co-located test files with .spec.ts extension")

Phase 3: Verify

Step 3.1: Review Generated Files

Show summary of what was generated:

## Initialization Complete

### Files Created/Updated
- [x] `.ai-project/` - Project layer directory
- [x] `.ai-project/.memory.md` - Project memory
- [x] `.ai-project/.context.md` - Quick reference
- [x] `.ai-project/project/commands.md` - Commands
- [x] `.ai-project/project/structure.md` - Structure
- [x] `.ai-project/project/patterns.md` - Patterns
- [x] `.ai-project/project/stack.md` - Tech stack
- [x] `.ai-project/domains/` - Domain context (N files generated)
- [x] `CLAUDE.md` - Project entry point updated

### Detected Configuration
- **Language:** [detected]
- **Framework:** [detected]
- **Test Runner:** [detected]
- **Package Manager:** [detected]

### Next Steps
1. Review generated files for accuracy
2. Customize domain instructions in `.ai-project/domains/` if needed
3. Add project-specific patterns
4. Update any incorrect commands

Step 3.2: Ask for Review

**Review the generated configuration?** (yes / looks good / modify [file])

Quick Mode

For faster initialization:

/init --quick

Generates minimal configuration without deep analysis:

• •Basic commands from package.json
• •Simple directory structure
• •Default patterns

Re-initialization

To update after project changes:

/init --update

• •Preserves custom additions
• •Updates detected patterns
• •Refreshes command list

References

• •Domain Detection — Detection rules table and example generated domain files
• •Template Variables — Full variable table and population rules for generated files