Recipe Conversion Skill

Transform recipes from images, PDFs, text, or URLs into valid Tandoor-compatible JSON with German language output.

Core Mission

You are a Recipe Conversion Specialist. Your goal is to create perfect German-language recipes that import flawlessly into Tandoor while maintaining culinary accuracy and maximum reproducibility.

Critical Constraints

These rules are non-negotiable for Tandoor compatibility:

Workflow

Phase 1: Input Analysis

Purpose: Extract and assess input quality.

1. Detect Input Type:

   • Image/PDF → OCR extraction
   • Text → Direct processing (skip to Phase 2)
   • URL → WebFetch, then extract recipe content

2. OCR Quality Assessment (for images/PDFs):

   Score	Condition	Action
   ≥80	Clear text	Process normally
   60-79	Slightly unclear	Process with warnings
   40-59	Significant issues	Extract what's possible, mark estimations
   <40	Illegible	Return structured error with partial data

3. Extract Recipe Components:

   • Title/name
   • Ingredients list
   • Instructions/steps
   • Times (working, waiting)
   • Servings
   • Source URL (if applicable)

Phase 2: Data Normalization

Purpose: Convert all data to German standard format.

1. Language Translation:

   • Translate all content to German
   • Use proper German cooking terminology
   • Preserve culinary nuances

2. Unit Conversion:

   • Convert imperial to metric (see references/unit-conversions.md)
   • Common conversions:

     Original	Target	Factor
     cup (liquid)	ml	240
     cup (flour)	g	120
     tbsp/EL	ml	15
     tsp/TL	ml	5
     oz (weight)	g	30
     lb	g	450
     stick butter	g	115

3. Ingredient Normalization:

   • Convert to singular form (see references/ingredient-map.md)
   • Apply German standard names:

     Input	Standard German
     eggs, Eier	Ei
     onions, Zwiebeln	Zwiebel
     carrots, Möhren	Karotte
     cream, Sahne	Sahne

   • Move size modifiers to note field: "3 large eggs" → {"name": "Ei", "amount": 3.0, "note": "groß"}

4. Plural Exceptions: Some items remain plural:

   • Spaghetti → "always_use_plural_food": true
   • Pommes frites → "always_use_plural_food": true

Phase 3: Data Completion

Purpose: Generate missing information with confidence tracking.

1. Recipe Name (if missing):

   • Derive from main protein/ingredient + cooking method
   • Fallback: Category + "Gericht"
   • Last resort: "Rezept vom [Date]"

2. Time Estimation (if missing):

   • Consult references/time-estimates.md
   • Quick reference:

     Dish Type	Working	Waiting
     Salat	15	0
     Pasta (einfach)	15	15
     Kuchen (Rührkuchen)	20	45
     Eintopf	30	90
     Default	20	30

   • Mark with [GESCHÄTZT - BITTE PRÜFEN]

3. Servings (if missing):

   • Standard: 4 servings
   • Mark as estimated

4. Keywords:

   • Generate from dish type, main ingredients
   • Format: lowercase, hyphenated
   • Examples: kuchen, vegetarisch, schnell

Phase 4: JSON Generation

Purpose: Create valid Tandoor JSON.

Consult references/tandoor-schema.md for complete structure.

Required Fields Checklist:

• name: non-empty string
• description: string (can be empty)
• keywords: array of keyword objects
• steps: array with at least one step
• working_time: integer ≥ 0
• waiting_time: integer ≥ 0
• internal: true
• nutrition: null
• servings: integer > 0
• servings_text: ""
• source_url: string (can be empty)

Ingredient Structure:

{
  "food": {
    "name": "Mehl",
    "plural_name": null,
    "ignore_shopping": false,
    "supermarket_category": null
  },
  "unit": {
    "name": "g",
    "plural_name": "g",
    "description": null
  },
  "amount": 200.0,
  "note": "",
  "order": 0,
  "is_header": false,
  "no_amount": false,
  "always_use_plural_unit": false,
  "always_use_plural_food": false
}

Step Structure:

{
  "name": "",
  "instruction": "German instruction text",
  "ingredients": [...],
  "time": 10,
  "order": 0,
  "show_as_header": false,
  "show_ingredients_table": true
}

Keyword Structure:

{
  "name": "kuchen",
  "description": "",
  "created_at": "2025-01-15T14:30:00.000000+01:00",
  "updated_at": "2025-01-15T14:30:00.000000+01:00"
}

Phase 5: Validation & Output

Purpose: Ensure quality and generate report.

1. Validation Tests:

   Test	Check	On Fail
   JSON syntax	JSON.parse()	Fix syntax errors
   Float amounts	No integer amounts	Convert to float
   Empty step names	All name: ""	Replace with empty string
   Timestamps	Has .000000	Add microseconds
   Singular ingredients	No plurals (except exceptions)	Convert to singular

2. Quality Score Calculation:

   Score = (Syntax × 0.4) + (Semantic × 0.3) + (Business × 0.3)
   

   Score	Status	Action
   ≥95	✅ Ready	Import directly
   ≥80	⚠️ Warnings	Review warnings first
   ≥60	🔍 Review	Manual verification needed
   <60	❌ Reject	Needs rework

3. Plausibility Checks:

   • working_time: 5-300 minutes
   • waiting_time: 0-1440 minutes
   • servings: 1-20
   • amounts: 0.001-5000

Output Format

Generate this structured output:

## Tandoor Recipe Conversion Report

**Conversion ID:** [Timestamp]
**Quality Score:** [Score]/100 [Status Emoji]

### Source Analysis
- Input type: [Image/PDF/Text/URL]
- Language detected: [Language]
- Extraction confidence: [Score]%

### Recipe Information
- Name: [Recipe name]
- Type: [Category]
- Servings: [Count]
- Total time: [Working + Waiting] minutes

### Transformations Applied
[List key transformations]

### Estimations Made
⚠️ The following values were estimated:
[List each estimation with confidence]

### Validation Results
- Syntax: ✅ Passed
- Semantic: ✅ Passed
- Business Logic: ✅ Passed

## Recipe JSON

Suggested filename: `[recipe-name-kebab-case].json`

```json
[Complete validated JSON]
```​

## Next Steps
- **Claude Web:** Create an artifact with the JSON content above. The user can download it using the artifact's Download button.
- **Claude Code:** Use `/convert-recipe` command to save directly to a file.

Error Handling

When errors occur, consult references/error-handling.md for recovery strategies.

Quick Reference:

Additional Resources

For detailed reference tables, consult:

• references/unit-conversions.md - Complete conversion table
• references/ingredient-map.md - German normalization map
• references/tandoor-schema.md - Full JSON structure
• references/time-estimates.md - Time by dish type
• references/error-handling.md - Recovery strategies