ralph-prompt-builder
Master orchestrator for generating Ralph Wiggum-compatible prompts. Analyzes task requirements and routes to appropriate generator (single-task, multi-task, project, or research). Use when you need to create any Ralph loop prompt and want automatic selection of the right generator.
Best use case
ralph-prompt-builder is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Master orchestrator for generating Ralph Wiggum-compatible prompts. Analyzes task requirements and routes to appropriate generator (single-task, multi-task, project, or research). Use when you need to create any Ralph loop prompt and want automatic selection of the right generator.
Teams using ralph-prompt-builder should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/ralph-prompt-builder/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How ralph-prompt-builder Compares
| Feature / Agent | ralph-prompt-builder | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Master orchestrator for generating Ralph Wiggum-compatible prompts. Analyzes task requirements and routes to appropriate generator (single-task, multi-task, project, or research). Use when you need to create any Ralph loop prompt and want automatic selection of the right generator.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Ralph Prompt Builder (Master Orchestrator)
## Overview
Master skill for generating prompts optimized for the Ralph Wiggum autonomous loop technique. This orchestrator analyzes your task description and routes to the appropriate specialized generator:
| Task Type | Generator | Best For |
|-----------|-----------|----------|
| Single focused task | `ralph-prompt-single-task` | Bug fixes, single features, refactoring |
| Multiple related tasks | `ralph-prompt-multi-task` | CRUD, multi-step features, migrations |
| Complete project | `ralph-prompt-project` | Greenfield apps, libraries, tools |
| Research/Analysis | `ralph-prompt-research` | Audits, planning, investigations |
## Quick Start
**Generate any Ralph prompt:**
```
Use ralph-prompt-builder to create a prompt for: [describe your task]
```
**Example:**
```
Use ralph-prompt-builder to create a prompt for: Implementing user authentication with JWT for our Express API
```
The skill will:
1. Classify your task
2. Route to the appropriate generator
3. Guide you through required inputs
4. Output a ready-to-use Ralph prompt
## Task Classification
### How Tasks Are Classified
| Indicators | Classification | Generator |
|------------|----------------|-----------|
| Fix, repair, single change, one module | Single Task | `ralph-prompt-single-task` |
| Multiple features, CRUD, several endpoints | Multi-Task | `ralph-prompt-multi-task` |
| Build from scratch, new app, create tool | Project | `ralph-prompt-project` |
| Analyze, audit, compare, plan, investigate | Research | `ralph-prompt-research` |
### Classification Questions
To classify your task, consider:
1. **Is this creating something new from scratch or modifying existing code?**
- New from scratch → Project or Multi-Task
- Modifying existing → Single Task or Multi-Task
2. **How many distinct deliverables?**
- One deliverable → Single Task
- 2-5 related deliverables → Multi-Task
- Complete application/tool → Project
- Analysis document → Research
3. **Does it involve investigation before action?**
- Yes, research required → Research
- No, implementation focus → Single/Multi/Project
4. **What's the completion criteria?**
- Tests pass → Single Task
- Multiple features working → Multi-Task
- Complete app running → Project
- Document produced → Research
## Classification Examples
### Single Task Examples
- "Fix the race condition in token refresh"
- "Add pagination to the users endpoint"
- "Refactor database queries to use async/await"
- "Write tests for the auth module"
- "Optimize the image upload function"
### Multi-Task Examples
- "Implement CRUD for Products resource"
- "Add login, signup, logout, and password reset"
- "Set up CI/CD pipeline with lint, test, build, deploy"
- "Add validation, error handling, and logging to API"
- "Create user, profile, and settings endpoints"
### Project Examples
- "Build a REST API for a todo list application"
- "Create a CLI tool for database migrations"
- "Build a URL shortener service"
- "Create a markdown documentation generator"
- "Build an authentication microservice"
### Research Examples
- "Analyze the codebase for security vulnerabilities"
- "Compare React vs Vue vs Svelte for our needs"
- "Create a migration plan from MongoDB to PostgreSQL"
- "Audit dependencies for outdated packages"
- "Document the current API architecture"
## Workflow
### Step 1: Describe Your Task
Provide a description including:
- What needs to be done
- What technology/context
- Any specific requirements
- Desired outcome
**Template:**
```
Task: [What you want to accomplish]
Context: [Relevant background - tech stack, existing code, etc.]
Requirements: [Specific requirements or constraints]
Outcome: [What success looks like]
```
### Step 2: Review Classification
The orchestrator will classify your task and explain why:
```
CLASSIFICATION: [Task Type]
REASONING: [Why this classification]
GENERATOR: ralph-prompt-[type]
Does this classification look correct? If not, specify your preferred type.
```
### Step 3: Provide Generator Inputs
Each generator requires specific inputs:
**Single Task:**
- Task description
- Success criteria (how to verify)
- Completion promise text
**Multi-Task:**
- List of tasks
- Dependencies between tasks
- Final completion promise
**Project:**
- Project description
- Tech stack
- Feature list
- Completion promise
**Research:**
- Research objective
- Scope (in/out)
- Deliverable format
- Completion promise
### Step 4: Generate & Review
The appropriate generator creates the prompt. Review and customize:
1. Verify requirements are complete
2. Check verification commands are correct
3. Confirm completion criteria match your needs
4. Adjust max-iterations recommendation
### Step 5: Execute with Ralph
```bash
/ralph-wiggum:ralph-loop "[generated prompt]" --completion-promise "[YOUR_PROMISE]" --max-iterations [recommended]
```
## Generator Summaries
### ralph-prompt-single-task
**Purpose:** Focused tasks with clear success criteria
**Structure:**
1. Task title and objective
2. Context
3. Requirements
4. Success criteria (checkboxes)
5. Verification steps with commands
6. TDD approach
7. Completion conditions
8. If stuck guidance
**Best practices:**
- Include actual test commands
- Make criteria binary (pass/fail)
- Include TDD loop
**Recommended iterations:** 15-35
---
### ralph-prompt-multi-task
**Purpose:** Multiple related tasks organized in phases
**Structure:**
1. Task inventory table
2. Phase breakdown (Foundation → Core → Enhancement → Validation)
3. Per-phase tasks with deliverables
4. Phase checkpoints
5. Progress tracking
6. Final verification
**Best practices:**
- Group tasks into logical phases
- Clear dependencies
- Document checkpoints
**Recommended iterations:** 35-100
---
### ralph-prompt-project
**Purpose:** Complete projects from scratch
**Structure:**
1. Project vision and specs
2. Six phases:
- Phase 0: Setup
- Phase 1: Architecture
- Phase 2: Core
- Phase 3: Features
- Phase 4: Testing
- Phase 5: Documentation
3. Per-phase tasks and deliverables
4. Final verification
5. Progress tracking
**Best practices:**
- Define non-goals explicitly
- Complete all phases in order
- Don't skip testing/documentation
**Recommended iterations:** 60-200
---
### ralph-prompt-research
**Purpose:** Analysis, audits, planning, investigations
**Structure:**
1. Research objective and scope
2. Five phases:
- Phase 1: Discovery
- Phase 2: Analysis
- Phase 3: Synthesis
- Phase 4: Recommendations
- Phase 5: Documentation
3. Deliverables at each phase
4. Evidence-based conclusions
**Best practices:**
- Define scope boundaries clearly
- Create artifacts as you go
- Support conclusions with evidence
**Recommended iterations:** 30-100
## Common Patterns
### Choosing a Completion Promise
**Good promises are:**
- Specific to the task
- Verifiable (you can check if it's true)
- Action-oriented
**Examples:**
| Task Type | Good Promise | Why |
|-----------|--------------|-----|
| Bug fix | `AUTH_FIX_COMPLETE` | Specific to what was fixed |
| CRUD | `PRODUCT_CRUD_DONE` | Names the resource |
| Project | `TODO_API_V1_COMPLETE` | Identifies the project |
| Research | `SECURITY_AUDIT_DELIVERED` | References deliverable |
### The Ralph Philosophy
The Ralph Wiggum technique is built on a key insight: **failures are deterministic and fixable**.
- **Deterministically bad**: When prompts fail, they fail in predictable ways
- **Fixable through iteration**: Each failure provides data to improve
- **Prompt tuning > tool changing**: Fix failures by improving the prompt, not switching approaches
This means: Don't fear failures. They're expected and correctable. The loop will iterate until success.
### Setting Max Iterations
Base recommendations by complexity:
| Complexity | Single Task | Multi-Task | Project | Research |
|------------|-------------|------------|---------|----------|
| Simple | 15 | 35 | 60 | 30 |
| Medium | 25 | 50 | 100 | 50 |
| Complex | 35 | 70 | 150 | 80 |
| Very Complex | - | 100 | 200 | 100 |
**Adjust based on:**
- Familiarity with codebase (-20%)
- External dependencies (+30%)
- Unclear requirements (+50%)
- Comprehensive testing needed (+25%)
### Splitting Large Tasks
If task feels too large, consider splitting:
**Project → Multiple Projects:**
```
Instead of: "Build complete e-commerce platform"
Split into:
1. Project: User authentication service
2. Project: Product catalog API
3. Project: Shopping cart service
4. Project: Order processing service
```
**Multi-Task → Separate Multi-Tasks:**
```
Instead of: "Build full admin dashboard"
Split into:
1. Multi-Task: User management (CRUD + roles)
2. Multi-Task: Analytics dashboard
3. Multi-Task: Settings panel
```
## Troubleshooting
### Task Won't Complete
**Symptoms:** Hitting max iterations without completion
**Causes and fixes:**
1. **Scope too large** → Split into smaller tasks
2. **Unclear criteria** → Make success criteria more specific
3. **External dependencies** → Document or mock dependencies
4. **Infinite tests** → Check for flaky tests
### Wrong Generator Selected
**Fix:** Specify the generator explicitly:
```
Use ralph-prompt-single-task (not multi-task) for: [task]
```
### Prompt Too Vague
**Fix:** Ensure your input includes:
- Specific files/modules affected
- Actual test commands
- Concrete success criteria
- Technology context
## Integration with Ralph Loop
After generating a prompt:
```bash
# Copy the generated prompt to a file or use directly
/ralph-wiggum:ralph-loop "[YOUR_GENERATED_PROMPT]" \
--completion-promise "YOUR_PROMISE" \
--max-iterations 50
# Monitor progress
head -10 .claude/ralph-loop.local.md
# Cancel if needed
/ralph-wiggum:cancel-ralph
```
## Best Practices
### DO:
- Start with the right generator for your task type
- Provide complete context and requirements
- Include specific verification commands
- Set appropriate max-iterations for complexity
- Review generated prompts before running
### DON'T:
- Use vague task descriptions
- Skip the classification step
- Ignore the "If Stuck" guidance in generated prompts
- Set max-iterations too low (iterations are normal)
- Expect first-try perfection—Ralph embraces iteration
## Quick Reference
### Task Type Decision Tree
```
Is this research/analysis/planning?
├─ YES → ralph-prompt-research
└─ NO → Is this building a complete app from scratch?
├─ YES → ralph-prompt-project
└─ NO → Are there multiple related deliverables?
├─ YES → ralph-prompt-multi-task
└─ NO → ralph-prompt-single-task
```
### Input Checklist
Before generating, have ready:
- [ ] Clear task description
- [ ] Technology context (language, framework)
- [ ] Success criteria (how to verify done)
- [ ] Completion promise text
- [ ] Any specific requirements
### Output Checklist
Before running the prompt:
- [ ] All requirements captured
- [ ] Verification commands are correct
- [ ] Success criteria are binary (pass/fail)
- [ ] TDD/iteration approach included
- [ ] "If Stuck" guidance provided
- [ ] Max iterations set appropriately
---
**Specialized Generators:**
- `ralph-prompt-single-task` - Single focused implementations
- `ralph-prompt-multi-task` - Multiple related tasks
- `ralph-prompt-project` - Complete projects
- `ralph-prompt-research` - Analysis and planning
**Ralph Loop Commands:**
- `/ralph-wiggum:ralph-loop` - Start a loop
- `/ralph-wiggum:cancel-ralph` - Cancel active loop
- `/ralph-wiggum:help` - Get helpRelated Skills
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