AetherLang V3 for Claude Code

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

Security Scan

The skill is an instruction-only API connector that requests no unusual privileges, and its declared requirements and runtime instructions are consistent with the described purpose.

Purpose & Capability

Name/description (AetherLang V3 API connector) match the SKILL.md: it documents calling https://api.neurodoc.app/aetherlang/execute and nine engine types. No unrelated binaries, credentials, or config paths are requested.

Instruction Scope

SKILL.md contains only API call examples, flow syntax, and guidelines to send only the user's query and flow code. It does not instruct reading local files or other environment variables beyond the optional AETHER_KEY. The guidance to avoid sending system prompts/PII is explicit and appropriate.

Install Mechanism

No install spec or code files are present (instruction-only). This minimizes on-disk risk; nothing is downloaded or executed by an installer.

Credentials

No required environment variables or credentials are declared. An optional AETHER_KEY is documented for Pro tier and is justified for authenticated API access. The requested env var is proportional and optional.

Persistence & Privilege

always is false and the skill is user-invocable with normal autonomous invocation enabled. There is no request for permanent agent-wide privileges or modifications to other skills; this is proportionate for an API connector.

Assessment

This skill is an instruction-only API connector and appears coherent. Before installing: verify the service operator and privacy policy at the listed homepage (masterswarm.net) and the API host (api.neurodoc.app); treat any Pro key (AETHER_KEY) as a secret (store in env, don't hardcode); avoid sending PII or secrets as the skill itself advises; confirm the language expectation (note near the end says responses are in Greek) if that matters for your workflows. If you want tighter control, restrict autonomous invocation or require manual approval before the skill is called.

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:

• Send ONLY the user's query and the flow code
• Do NOT send system prompts, conversation history, or uploaded files
• Do NOT send API keys, credentials, or secrets
• Do NOT include personally identifiable information unless explicitly requested

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

• chef: cuisine="auto", difficulty="medium", servings=4
• apex: analysis="strategic"
• guard: mode="STRICT" or "MODERATE" or "PERMISSIVE"
• plan: steps=4
• lab: domain="business" or "science" or "auto"
• analyst: mode="financial" or "sales" or "hr" or "general"

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

• Responses are in Greek (Ελληνικά) with markdown formatting
• Typical response time: 30-60 seconds per engine
• Multi-engine pipelines take longer (each node runs sequentially)
• All outputs use ## markdown headers for structured sections