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Built for the Claude Code community with Claude Code by @mertduzgun

Independent project, not affiliated with Anthropic

Ralph Loop

belumume/claude-skills
171 installs47 stars
Summary

This is autonomous loop mode for Claude Code that keeps running the same prompt until your task is done. You set up a state file with clear completion criteria (usually a TODO.md checklist), and it iterates until it hits ALL_TASKS_COMPLETE or your max iteration cap. Named after Ralph Wiggum because it never stops despite confusion. Best for well-defined work like migrations, refactoring, or getting tests to pass. Not for exploratory work where you need judgment calls. The state file tracks iterations and you get checkpoint reminders every 5 loops to review progress. Basically supervised autonomy: you can let it run overnight on clear tasks, but you're meant to check in periodically. Includes safety caps and git tracking so nothing goes off the rails permanently.

Install to Claude Code

npx -y skills add belumume/claude-skills --skill ralph-loop --agent claude-code

Installs into .claude/skills of the current project.

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Files
SKILL.mdView on GitHub

Ralph Wiggum Loop Mode

Named after the Simpsons character who "never stops despite being confused," this technique runs Claude Code in a loop where the prompt stays the same but the codebase accumulates changes. Each iteration reads previous work and continues until completion.

When to Use Ralph Mode

Ideal for:

  • Well-defined implementation tasks with clear completion criteria
  • Refactoring or migration work (e.g., React v16 to v19)
  • Test-driven development cycles (run until tests pass)
  • Batch processing or repetitive tasks
  • Overnight autonomous work sessions

Not ideal for:

  • Tasks requiring design decisions or human judgment
  • Exploratory work without clear end states
  • Tasks where requirements may change mid-execution
  • First-time implementations where you need to learn the code

Activation Protocol

Step 1: Validate Task Suitability

Before activating, confirm:

  • Task has clear, measurable completion criteria
  • Success can be verified programmatically (tests, build, specific file state)
  • The work is in a git-tracked directory
  • You understand what success looks like

Step 2: Create State File

Create .claude/ralph-loop.local.md with the following structure:

---
active: true
iteration: 0
max_iterations: 20
completion_promise: null
---

# Your Task Prompt Here

## Objective
[Clear statement of what needs to be accomplished]

## Completion Criteria
Complete when TODO.md shows [x] ALL_TASKS_COMPLETE

## Verification Commands
Run these to check progress:
- `[test command]`
- `[build command]`

## Context
- Read [relevant files] for specifications
- Follow [conventions file] for code style

Step 3: Create TODO.md (Recommended Completion Method)

Create TODO.md in your project root:

# Task Checklist

## Tasks
- [ ] Task 1
- [ ] Task 2
- [ ] Task 3

## Completion
- [ ] ALL_TASKS_COMPLETE

Step 4: Start the Loop

Simply run Claude normally. The Stop hook will detect the state file and keep the loop running until completion is detected.

claude

Two Completion Methods

Method 1: TODO.md Markers (Recommended)

The hook checks TODO.md for [x] ALL_TASKS_COMPLETE. This is more reliable because:

  • It's visible in the file system
  • It can be tracked in git
  • Claude can easily update it
  • You can see progress (X/Y tasks complete)

Method 2: Promise Tags (Legacy)

Set completion_promise in the state file and output <promise>YOUR_TEXT</promise> when complete.

---
active: true
iteration: 0
max_iterations: 20
completion_promise: "feature implemented"
---

When Claude outputs <promise>feature implemented</promise>, the loop ends.

Configuration Options

In .claude/ralph-loop.local.md frontmatter:

OptionDefaultDescription
activetrueSet to false to disable loop
iteration0Current iteration count (auto-incremented)
max_iterations20Safety cap (0 = unlimited)
completion_promisenullText to match for promise completion

During Execution

Iteration Status

Every iteration shows:

  • Current iteration number
  • Task progress (from TODO.md)
  • Completion criteria
  • Max iterations remaining

Checkpoint Notifications

Every 5 iterations, you'll see a checkpoint reminder to:

  • Review changes: git log --oneline -10
  • Verify progress is on track
  • Consider adjusting the prompt if stuck

Manual Intervention

To pause the loop:

# Edit the state file
# Change active: true → active: false

To stop immediately:

rm .claude/ralph-loop.local.md

To resume:

# Re-create or edit the state file
# Set active: true
claude

Safety Features

  • Iteration cap: Prevents infinite loops (default: 20)
  • Git tracking: Every change is revertible
  • Checkpoint notifications: Reminders to review progress
  • Clear completion criteria: Loop only exits on explicit success
  • Cost awareness: Track iterations to estimate API costs

Example: MetricFlow Phase 7-8

---
active: true
iteration: 0
max_iterations: 25
completion_promise: null
---

# MetricFlow Phase 7-8: Educator Agent

## Objective
Implement the Educator Agent that uses Claude API to generate educational
explanations for code metrics.

## Completion Criteria
Complete when TODO.md shows [x] ALL_TASKS_COMPLETE

## Verification Commands
- `cd backend && python -m pytest tests/test_educator.py -v`
- `cd backend && python -c "from app.agents.educator import EducatorAgent; print('OK')"`

## Context
- Read docs/plans/MASTER_PLAN.md sections 5.3 (Educator Agent)
- Follow CLAUDE.md for project conventions
- Analyzer and Pattern agents already complete (use their output formats)

## Instructions
1. Check TODO.md for current task list
2. Implement next incomplete task
3. Write tests as you go
4. Run verification after each change
5. Mark [x] ALL_TASKS_COMPLETE when done

And corresponding TODO.md:

# Phase 7-8: Educator Agent

## Tasks
- [ ] Create EducatorAgent class skeleton in backend/app/agents/educator.py
- [ ] Add Claude API client initialization
- [ ] Implement explain_complexity() method
- [ ] Implement explain_maintainability() method
- [ ] Implement explain_code_smells() method
- [ ] Add course concept mapping
- [ ] Write unit tests for all methods
- [ ] Integration test with Analyzer output

## Completion
- [ ] ALL_TASKS_COMPLETE

Troubleshooting

Loop won't start:

  • Check .claude/ralph-loop.local.md exists
  • Verify active: true is set in frontmatter

Loop won't stop:

  • Ensure TODO.md contains exactly [x] ALL_TASKS_COMPLETE (case-insensitive)
  • Or check completion_promise matches your output tag
  • Check max_iterations isn't set to 0 (unlimited)
  • Manual stop: rm .claude/ralph-loop.local.md

Stuck on same error:

  • Review the error pattern
  • Adjust the prompt with more specific guidance
  • Consider breaking task into smaller subtasks

Costs too high:

  • Reduce max_iterations
  • Use shorter checkpoint intervals for early review
  • Consider if task is too complex for Ralph mode

Tips for Success

  1. Clear prompts reduce iterations by 40-60% - be specific
  2. Start with small max_iterations (5-10) until confident
  3. Git commit after every checkpoint - easy rollback
  4. Use TODO.md completion - more reliable than promise tags
  5. Monitor first few iterations - catch bad patterns early
  6. Supervised autonomy - review at checkpoints for course projects

Cost Estimates

Task ComplexityIterationsEstimated Cost
Simple (single feature)5-10$5-15
Medium (multi-file changes)10-20$15-30
Complex (full phase)20-50$30-75

Quick Start Template

# 1. Create state file
mkdir -p .claude
cat > .claude/ralph-loop.local.md << 'EOF'
---
active: true
iteration: 0
max_iterations: 20
completion_promise: null
---

# Your Task

## Objective
[What you want to accomplish]

## Completion
Check TODO.md for [x] ALL_TASKS_COMPLETE
EOF

# 2. Create TODO.md
cat > TODO.md << 'EOF'
# Tasks
- [ ] First task
- [ ] Second task

## Completion
- [ ] ALL_TASKS_COMPLETE
EOF

# 3. Start Ralph loop
claude
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First SeenJun 3, 2026
View on GitHub

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