Ralph for Claude Code is a CLI automation framework written entirely in Bash (with one Python helper for E2B sandbox transport) that orchestrates repeated Claude Code CLI invocations in an autonomous loop. The core system parses output from Claude to detect completion, test saturation, permission denials, and stuck loops, using a dual-condition exit strategy. It includes a circuit breaker (CLOSED/HALF_OPEN/OPEN) for stagnation protection, dual rate limiting (calls and tokens per hour), sandbox execution via Docker or E2B cloud, session continuity with expiry, and backup/rollback via git branches. The system manages GitHub issue lifecycles (progress comments, auto-close, PR creation, follow-up issues) and provides a persistent queue for batch processing with dependency resolution and priority ordering. All state is maintained as JSON files in a .ralph directory with atomic writes. The repository also includes extensive test infrastructure (276 BATS tests) with mock binaries for gh, claude, docker, and e2b-python, a full E2E subprocess-level harness, and 24 unit test files plus integration and E2E tests. The project is not a hybrid data/research repository; it is purely an application for automating AI-assisted software development.
Ralph Wiggum for Cursor is an implementation of Geoffrey Huntley's Ralph Wiggum technique for autonomous AI development. It manages LLM context like memory by tracking token usage and rotating to fresh agent contexts when needed, persisting state in files and git. The system provides automated iteration loops with features like gutter detection, rate limit handling, task progress tracking via checkboxes, and support for both sequential and parallel execution modes. Key components include a sophisticated stream parser for real-time token and error monitoring, a YAML-backed task parser with caching, and retry logic with exponential backoff.