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Ralph Wiggum AI Loops

The Ralph Wiggum technique is an iterative AI development methodology. At its core, it's a simple while loop that repeatedly feeds Claude a prompt until completion.

while :; do cat PROMPT.md | claude ; done

Named after The Simpsons character, it embodies persistent iteration despite setbacks.

Philosophy​

  • Iteration > Perfection - Don't aim for perfect on first try
  • Failures Are Data - Deterministically bad means failures are predictable
  • Operator Skill Matters - Success depends on writing good prompts
  • Persistence Wins - Keep trying until success

When to Use​

Good for:

  • Well-defined tasks with clear success criteria
  • Tasks requiring iteration (getting tests to pass)
  • Greenfield projects you can walk away from
  • Tasks with automatic verification (tests, linters)
  • Overnight/weekend automated development

Not good for:

  • Tasks requiring human judgment
  • One-shot operations
  • Unclear/subjective success criteria
  • Production debugging

Skillflow​

Use the ralph-loop skillflow:

mcpammer_skillflow_execute ralph-loop inputs={
  "prompt": "Your task prompt here...",
  "completion_promise": "COMPLETE",
  "max_iterations": 30
}

Prompt Best Practices​

1. Clear Completion Criteria​

Bad:

Build a todo API and make it good.

Good:

Build a REST API for todos.

When complete:
- All CRUD endpoints working
- Input validation in place
- Tests passing (coverage > 80%)
- README with API docs

Output: <promise>COMPLETE</promise>

2. Incremental Goals​

Phase 1: User authentication (JWT, tests)
Phase 2: Product catalog (list/search, tests)
Phase 3: Shopping cart (add/remove, tests)

Output <promise>COMPLETE</promise> when all phases done.

3. Self-Correction Pattern​

Implement feature X following TDD:
1. Write failing tests
2. Implement feature
3. Run tests
4. If any fail, debug and fix
5. Refactor if needed
6. Repeat until all green
7. Output: <promise>COMPLETE</promise>

Templates​

Feature Implementation​

Implement [FEATURE_NAME].

Requirements:
- [Requirement 1]
- [Requirement 2]

Success criteria:
- All requirements implemented
- Tests passing with >80% coverage
- No linter errors
- Documentation updated

Output <promise>COMPLETE</promise> when done.

Bug Fixing​

Fix bug: [DESCRIPTION]

Steps:
1. Reproduce the bug
2. Identify root cause
3. Implement fix
4. Write regression test
5. Verify fix works

After 15 iterations if not fixed:
- Document blocking issues
- List attempted approaches

Output <promise>FIXED</promise> when resolved.

Safety​

  • Always set max_iterations - Prevents infinite loops
  • Include stuck handling - Document what to do after N failures
  • Use completion promise - Clear signal for success

Source​

https://awesomeclaude.ai/ralph-wiggum