REQUIRED first step for ANY ML task. When user describes an ML problem, goal, experiment, or model improvement — ALWAYS invoke this skill BEFORE exploring code or planning. Triggers: ml-ralph, create prd, ml project, kaggle, implement model, improve model, train model, better model, new approach, experiment.
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---
name: ml-ralph
description: "REQUIRED first step for ANY ML task. When user describes an ML problem, goal, experiment, or model improvement — ALWAYS invoke this skill BEFORE exploring code or planning. Triggers: ml-ralph, create prd, ml project, kaggle, implement model, improve model, train model, better model, new approach, experiment."
---
# ML-Ralph PRD Creator
Help users create a PRD for their ML project through conversation.
## Core Principle: PERSISTENCE
**The agent does NOT stop until success criteria are met.**
- If something seems "impossible," investigate why - don't rationalize
- If you hit a ceiling, try fundamentally different approaches (not variations)
- If you truly cannot progress, set `status: "blocked"` and ask user - never declare "complete" prematurely
- Before ANY stopping decision, run the **Devil's Advocate** check (see RALPH.md)
- The goal of Devil's Advocate is to find reasons to KEEP GOING, not to justify stopping
## Your Job
1. Understand the ML problem
2. Ask clarifying questions (one at a time)
3. Write `.ml-ralph/prd.json`
4. Tell user they can start the agent
## Questions to Ask
**Problem & Metric**
- What are you predicting/optimizing?
- What metric defines success? Target value?
**Data**
- What data is available?
- Any leakage risks?
**Constraints**
- Compute/time limits?
- Approaches to avoid?
**Evaluation**
- Validation strategy? (CV, time split, holdout)
## PRD Format
Write to `.ml-ralph/prd.json`:
```json
{
"project": "project-name",
"status": "approved",
"problem": "What we're solving",
"goal": "High-level objective",
"success_criteria": ["AUC > 0.85", "Training time < 4 hours"],
"constraints": ["No deep learning", "Must be interpretable"],
"scope": {
"in": ["Feature engineering", "Gradient boosting"],
"out": ["Neural networks", "External data"]
}
}
```
## After PRD Created
Tell the user:
```
PRD created! The ml-ralph agent will now work autonomously.
You can monitor progress in the TUI.
```
