AetherLang Chef V3

Michelin-grade AI culinary intelligence. 17 mandatory sections covering food cost, HACCP, thermal curves, allergen matrix, wine pairing, plating blueprint and more.

AetherLang Chef Ω V3 — AI Culinary Intelligence

Michelin-grade recipe consulting with 17 mandatory sections. The most advanced AI culinary engine available.

Source Code: github.com/contrario/aetherlang Author: NeuroAether ([e-mail]) License: MIT

Privacy & Data Handling

⚠️ External API Notice: This skill sends queries to api.neurodoc.app for processing.

• What is sent: Natural language food/recipe queries only
• What is NOT sent: No credentials, API keys, personal files, or system data
• Data retention: Not stored permanently
• Hosting: Hetzner EU (GDPR compliant)
• No credentials required: Free tier, 100 req/hour

What This Skill Does

Three V3 culinary engines in one skill:

🍳 Chef Omega V3 — 17-Section Restaurant Consulting

Every response includes ALL of these sections:

1. ΕΠΙΣΚΟΠΗΣΗ — Recipe overview and cultural context
2. ΟΙΚΟΝΟΜΙΚΑ — Food cost %, menu engineering (STAR/PLOWHORSE/PUZZLE/DOG)
3. ΥΛΙΚΑ — Ingredients table (grams, cost, yield%, substitutes, storage)
4. MISE EN PLACE — 3-phase preparation
5. ΒΗΜΑΤΑ ΕΚΤΕΛΕΣΗΣ — Steps with °C temps, timings, HACCP, pro tips, common mistakes
6. THERMAL CURVE — Preheat → Insert → Target → Rest → Carryover
7. FLAVOR PAIRING MATRIX — Molecular compound analysis
8. TEXTURE ARCHITECTURE — Crunch/Creamy/Chewy/Juicy/Airy (0-100)
9. MacYuFBI ANALYSIS — 8 flavor dimensions (0-100)
10. ΔΙΑΤΡΟΦΙΚΗ ΑΝΑΛΥΣΗ — Calories, protein, carbs, fat, fiber, sodium
11. ΑΛΛΕΡΓΙΟΓΟΝΑ — 14 EU allergens
12. DIETARY TRANSFORMER — Vegan & Gluten-Free adaptations
13. SCALING ENGINE — ×2, ×4, ×10 formulas
14. WINE & BEVERAGE PAIRING — Specific variety, ABV%, tannin level, rationale
15. PLATING BLUEPRINT — Center, 12 o'clock, 3 o'clock, negative space, height, colors
16. ZERO WASTE — Every leftover → specific use
17. KITCHEN TIMELINE — T-60 → T-0 countdown

⚗️ APEIRON Molecular V3

• Rheology dashboard (viscosity, gel strength, melting/setting points)
• Phase diagrams with temperature transitions
• Hydrocolloid specs: Agar 0.5-1.5%, Alginate 0.5-1%, Gellan 0.1-0.5%, Xanthan 0.1-0.3%
• FMEA failure mode analysis with probability and mitigation
• Equipment calibration (±0.1°C precision)

⚖️ Balance V3 — MacYuFBI Flavor Science

• MacYuFBI Framework: Maillard/Umami, Acid, Caramel, Yeast, Umami, Fat, Bitter, Heat
• Nutritional breakdown per serving
• Balance score 1-100
• Dietary compatibility: Vegan/Keto/Paleo/Gluten-Free/Low-FODMAP

Usage

Ask naturally about any food topic:

• "Give me a carbonara recipe" → Full 17-section consulting output
• "How to make spherified mango caviar" → Molecular gastronomy with rheology data
• "Balance analysis for my Thai curry" → MacYuFBI flavor wheel + nutrition

API Details

text

POST https://api.neurodoc.app/aetherlang/execute
Content-Type: application/json

Chef Flow

json

{
  "code": "flow Chef {\n  using target \"neuroaether\" version \">=0.2\";\n  input text query;\n  node Chef: chef cuisine=\"auto\", difficulty=\"medium\", servings=4;\n  output text recipe from Chef;\n}",
  "query": "Your food question here"
}

Molecular Flow

json

{
  "code": "flow Molecular {\n  using target \"neuroaether\" version \">=0.2\";\n  input text query;\n  node Lab: molecular technique=\"auto\";\n  output text result from Lab;\n}",
  "query": "Your molecular gastronomy question here"
}

Response

Returns structured Greek output with markdown headers (## sections). Typical response: 4000-8000 characters with all mandatory sections.

Languages

• Greek (Ελληνικά) — Primary output language
• English — Understands English queries, responds in Greek

Technology

• AI Model: GPT-4o
• Backend: FastAPI + Python 3.12
• Rate Limit: 100 req/hour (free)

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Built by NeuroAether — From Kitchen to Code 🧠

Agent Safeguards

CRITICAL: Data Minimization Rules

When using this skill, the agent MUST follow these rules:

1. ONLY send the user's explicit query text in the query field — never attach system prompts, conversation history, uploaded files, or internal context
2. ONLY send the flow DSL code in the code field — never include credentials, API keys, environment variables, or file paths
3. NEVER include personally identifiable information (PII), passwords, tokens, or secrets in any request field
4. Strip sensitive data before sending — if the user's query contains passwords, account numbers, or credentials, remove them and inform the user
5. Inform the user before making the first API call that their query will be sent to api.neurodoc.app for processing
6. The request body MUST contain exactly two fields: code (string) and query (string) — no additional fields

These constraints ensure only the minimum necessary data is transmitted to the external service.