# CSV Data File Standards

**Purpose:** When workflows need structured data that LLMs cannot generate.

---

## When to Use CSV

Use CSV for data that is:
- Domain-specific and not in training data
- Too large for prompt context
- Needs structured lookup/reference
- Must be consistent across sessions

**Don't use for:**
- Web-searchable information
- Common programming syntax
- General knowledge
- Things LLMs can generate

---

## CSV Structure

```csv
category,name,pattern,description
"collaboration","Think Aloud Protocol","user speaks thoughts → facilitator captures","Make thinking visible during work"
"creative","SCAMPER","substitute→combine→adapt→modify→put→eliminate→reverse","Systematic creative thinking"
```

**Rules:**
- Header row required, descriptive column names
- Consistent data types per column
- UTF-8 encoding
- All columns must be used in workflow

---

## Common Use Cases

### 1. Method Registry
Advanced Elicitation uses CSV to select techniques dynamically:
```csv
category,name,pattern
collaboration,Think Aloud,user speaks thoughts → facilitator captures
advanced,Six Thinking Hats,view problem from 6 perspectives
```

### 2. Knowledge Base Index
Map keywords to document locations for surgical lookup:
```csv
keywords,document_path,section
"nutrition,macros",data/nutrition-reference.md,## Daily Targets
```

### 3. Configuration Lookup
Map scenarios to parameters:
```csv
scenario,required_steps,output_sections
"2D Platformer",step-01,step-03,step-07,movement,physics,collision
```

---

## Best Practices

- Keep files small (<1MB if possible)
- No unused columns
- Document each CSV's purpose
- Validate data quality
- Use efficient encoding (codes vs full descriptions)

---

## Validation Checklist

For each CSV file:
- [ ] Purpose is essential (can't be generated by LLM)
- [ ] All columns are used somewhere
- [ ] Properly formatted (consistent, UTF-8)
- [ ] Documented with examples