AetherLang V3 — Claude Code Integration Skill

---

name: aetherlang-claude-code

description: Execute AetherLang V3 AI workflows from Claude Code using nine specialized engines for culinary, business, research, marketing, and strategic analyses.

version: 1.0.3

author: contrario

homepage: https://masterswarm.net

requirements:

binaries: []

env:

- name: AETHER_KEY

required: false

description: "Optional Pro tier API key for X-Aether-Key header (500 req/hour). Get from masterswarm.net."

metadata:

skill_type: api_connector

external_endpoints:

- https://api.neurodoc.app/aetherlang/execute

operator_note: "api.neurodoc.app operated by NeuroDoc Pro (same as masterswarm.net), Hetzner DE"

privacy_policy: https://masterswarm.net

license: MIT

---

# AetherLang V3 — Claude Code Integration Skill

Use this skill to execute AetherLang V3 AI workflows from Claude Code. AetherLang provides 9 specialized AI engines for culinary consulting, business strategy, scientific research, and more.

API Endpoint

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

No API key required for free tier (100 req/hour).

Data Minimization

When calling the API:

> **Pro API key:** If using the Pro tier (`X-Aether-Key` header), store the key

> in an environment variable — never hardcode it in flow code or scripts.

> `export AETHER_KEY=your_key_here` then use `-H "X-Aether-Key: $AETHER_KEY"`

How to Use

1. Simple Engine Call

curl -s -X POST https://api.neurodoc.app/aetherlang/execute \
  -H "Content-Type: application/json" \
  -d '{
    "code": "flow Chat {\n  using target \"neuroaether\" version \">=0.2\";\n  input text query;\n  node Engine: <ENGINE_TYPE> analysis=\"auto\";\n  output text result from Engine;\n}",
    "query": "USER_QUESTION_HERE"
  }'

Replace `<ENGINE_TYPE>` with one of: `chef`, `molecular`, `apex`, `consulting`, `marketing`, `lab`, `oracle`, `assembly`, `analyst`

2. Multi-Engine Pipeline

curl -s -X POST https://api.neurodoc.app/aetherlang/execute \
  -H "Content-Type: application/json" \
  -d '{
    "code": "flow Pipeline {\n  using target \"neuroaether\" version \">=0.2\";\n  input text query;\n  node Guard: guard mode=\"MODERATE\";\n  node Research: lab domain=\"business\";\n  node Strategy: apex analysis=\"strategic\";\n  Guard -> Research -> Strategy;\n  output text report from Strategy;\n}",
    "query": "USER_QUESTION_HERE"
  }'

Available V3 Engines

| Engine Type | Use For | Key V3 Features |

|-------------|---------|-----------------|

| `chef` | Recipes, food consulting | 17 sections: food cost, HACCP, thermal curves, wine pairing, plating blueprint, zero waste |

| `molecular` | Molecular gastronomy | Rheology dashboard, phase diagrams, hydrocolloid specs, FMEA failure analysis |

| `apex` | Business strategy | Game theory, Monte Carlo (10K sims), behavioral economics, unit economics, Blue Ocean |

| `consulting` | Strategic consulting | Causal loops, theory of constraints, Wardley maps, ADKAR change management |

| `marketing` | Market research | TAM/SAM/SOM, Porter's 5 Forces, pricing elasticity, viral coefficient |

| `lab` | Scientific research | Evidence grading (A-D), contradiction detector, reproducibility score |

| `oracle` | Forecasting | Bayesian updating, black swan scanner, adversarial red team, Kelly criterion |

| `assembly` | Multi-agent debate | 12 neurons voting (8/12 supermajority), Gandalf VETO, devil's advocate |

| `analyst` | Data analysis | Auto-detective, statistical tests, anomaly detection, predictive modeling |

Flow Syntax Reference

flow <Name> {
  using target "neuroaether" version ">=0.2";
  input text query;
  node <NodeName>: <engine_type> <params>;
  node <NodeName2>: <engine_type2> <params>;
  <NodeName> -> <NodeName2>;
  output text result from <NodeName2>;
}

Node Parameters

Response Format

{
  "status": "success",
  "result": {
    "outputs": { ... },
    "final_output": "Full structured markdown response",
    "execution_log": [...],
    "duration_seconds": 45.2
  }
}

Extract the main response from `result.final_output`.

Example: Parse Response in Bash

curl -s -X POST https://api.neurodoc.app/aetherlang/execute \
  -H "Content-Type: application/json" \
  -d '{"code":"flow Chef {\n  using target \"neuroaether\" version \">=0.2\";\n  input text query;\n  node Chef: chef cuisine=\"auto\";\n  output text recipe from Chef;\n}","query":"Carbonara recipe"}' \
  | python3 -c "import sys,json; d=json.load(sys.stdin); print(d.get('result',{}).get('final_output','No output'))"

Example: Python Integration

import requests

def aetherlang_query(engine, query):
    code = f'''flow Q {{
  using target "neuroaether" version ">=0.2";
  input text query;
  node E: {engine} analysis="auto";
  output text result from E;
}}'''
    r = requests.post("https://api.neurodoc.app/aetherlang/execute",
        json={"code": code, "query": query})
    return r.json().get("result", {}).get("final_output", "")

# Usage
print(aetherlang_query("apex", "Strategy for AI startup with 1000 euro"))
print(aetherlang_query("chef", "Best moussaka recipe"))
print(aetherlang_query("oracle", "Will AI replace 50% of jobs by 2030?"))

Rate Limits

| Tier | Limit | Auth |

|------|-------|------|

| Free | 100 req/hour | None required |

| Pro | 500 req/hour | X-Aether-Key header |

Notes