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Scans your project and generates a .ralph/ directory with configuration, prompts, guides, and scripts tailored to your codebase.

What happens

The init process has six phases:
1

Scanning

Wiggum runs parallel detectors across your project to identify your tech stack. Detects 80+ technologies including:
  • Core — Framework, package manager, testing (unit + E2E), styling
  • Data — Database, ORM, API layer
  • Frontend — State management, UI components, form handling
  • Services — Auth, analytics
  • Infra — Hosting, CI/CD, MCP servers
Each detection includes a confidence score (0-100).
2

Provider selection

Choose your AI provider: Anthropic, OpenAI, or OpenRouter.
3

API key

Enter your API key. Wiggum saves it to .ralph/.env.local (gitignored) so you don’t need to re-enter it.
4

Model selection

Pick models for each purpose:
  • Planning model (e.g. Opus) — Handles spec generation, architectural decisions, and verification
  • Implementation model (e.g. Sonnet) — Handles the coding loop
5

AI analysis

Wiggum runs an agentic analysis of your codebase, producing structured context:
  • Entry points and key files
  • Directory purposes
  • Build, dev, test, lint commands
  • Naming conventions
  • Project-specific implementation guidelines
6

File generation

Creates the .ralph/ directory with all configuration, prompts, guides, and scripts.

Flags

--provider
string
default:"anthropic"
AI provider to use. Options: anthropic, openai, openrouter.
-i, --interactive
boolean
default:"false"
Stay in interactive TUI mode after init completes.
-y, --yes
boolean
default:"false"
Accept all defaults and skip confirmation prompts.

Output

Creates the .ralph/ directory:
See configuration for details on each file and setting.

Examples

To rescan your project after changes without repeating the full init flow, use wiggum sync.