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Execute AI workflow orchestration flows using the AetherLang Ω DSL. Run multi-step AI pipelines for recipes, business strategy, market analysis, molecular gastronomy, and more.
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/javimosch/open-claw-skills --skill aetherlang명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SOC 직업 분류 기준
SKILL.md 표시 중
| name | aetherlang |
| description | Execute AI workflow orchestration flows using the AetherLang Ω DSL. Run multi-step AI pipelines for recipes, business strategy, market analysis, molecular gastronomy, and more. |
| version | 9.9.11 |
| author | contrario |
| homepage | https://masterswarm.net |
| requirements | {"binaries":[],"env":[]} |
| 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 |
The world's most advanced AI workflow orchestration platform. 9 V3 engines deliver Nobel-level analysis, Michelin-grade recipes, adversarial forecasting, and multi-agent intelligence.
Source Code: github.com/contrario/aetherlang Homepage: neurodoc.app/aether-nexus-omega-dsl Author: NeuroAether (echelonvoids@protonmail.com) License: MIT
⚠️ External API Notice: This skill sends user-provided flow code and query text to the AetherLang API at api.neurodoc.app for processing. By using this skill, you consent to this data transmission.
Users should avoid including sensitive personal information, passwords, or confidential data in queries.
AetherLang Ω V3 is a domain-specific language for AI that orchestrates multi-model workflows with built-in safety, debugging, and real-time collaboration. V3 introduces state-of-the-art system prompts with mandatory structured outputs no other platform provides.
All user inputs are validated and sanitized server-side before processing. Network traffic can be verified independently: the skill sends only DSL code + query text to api.neurodoc.app — no system context, files, or env vars are included in the request payload.
| Engine | Node Type | V3 Highlights |
|---|---|---|
| 🍳 Chef Omega | chef | 17 mandatory sections: food cost%, HACCP, thermal curves, MacYuFBI matrix, texture architecture, allergen matrix (14 EU), dietary transformer, wine pairing, plating blueprint, zero waste, kitchen timeline |
| ⚗️ APEIRON Molecular | molecular | Rheology dashboard, phase diagrams, hydrocolloid specs (Agar/Alginate/Gellan/Xanthan), FMEA failure analysis, equipment calibration, sensory science metrics |
| 📈 APEX Strategy | apex | Game theory + Nash equilibrium, Monte Carlo (10K simulations), behavioral economics, decision trees, competitive war gaming, unit economics (CAC/LTV), Blue Ocean canvas, OKR generator |
| 🧠 GAIA Brain | assembly | 12 neurons voting system (supermajority 8/12), disagreement protocol, Gandalf VETO power, devil's advocate, confidence heatmap, 7 archetypes |
| 🔮 Oracle | oracle | Bayesian updating (prior→evidence→posterior), signal vs noise scoring, temporal resolution (7d/30d/180d), black swan scanner, adversarial red team, Kelly criterion bet sizing |
| 💼 NEXUS-7 Consult | consulting | Causal loop diagrams, theory of constraints, Wardley maps, ADKAR change management, anti-pattern library, system dynamics modeling |
| 📊 Market Intel | marketing | TAM/SAM/SOM, category design, Porter's 5 Forces, pricing elasticity, network effects, viral coefficient (K-factor), customer segmentation AI |
| 🔬 Research Lab | lab | Evidence grading (A-D levels), contradiction detector, knowledge graph, reproducibility score (X/10), cross-disciplinary bridges, research gap map |
| 📉 Data Analyst | analyst | Auto-detective (outliers/missing/duplicates), statistical test selector, anomaly detection, predictive modeling (R²/RMSE), cohort/funnel analysis, causal inference |
POST https://api.neurodoc.app/aetherlang/execute
Content-Type: application/json
{
"code": "<aetherlang_flow>",
"query": "<user_input>"
}
flow <FlowName> {
using target "neuroaether" version ">=0.2";
input text query;
node <NodeName>: <engine_type> <parameters>;
output text result from <NodeName>;
}
flow Chef {
using target "neuroaether" version ">=0.2";
input text query;
node Chef: chef cuisine="auto", difficulty="medium", servings=4, language="el";
output text recipe from Chef;
}
Returns: 17 sections including food cost analysis, HACCP compliance, thermal curves, wine pairing, plating blueprint, zero waste protocol, and kitchen timeline.
flow Strategy {
using target "neuroaether" version ">=0.2";
input text query;
node Guard: guard mode="MODERATE";
node Planner: plan steps=4;
node LLM: apex model="gpt-4o", temp=0.7;
Guard -> Planner -> LLM;
output text report from LLM;
}
Returns: Game theory, Monte Carlo simulations, behavioral economics, decision trees, financial projections, unit economics, Blue Ocean canvas.
flow FullAnalysis {
using target "neuroaether" version ">=0.2";
input text query;
node Guard: guard mode="STRICT";
node Research: lab domain="business";
node Market: marketing analysis="competitive";
node Strategy: apex analysis="strategic";
Guard -> Research -> Market -> Strategy;
output text report from Strategy;
}
Security middleware source code: middleware/security.py
code, query, language fields acceptedBlocks: code execution (eval, exec), SQL injection, XSS, template injection, OS commands, prompt manipulation.
{
"status": "success",
"flow_name": "Chef",
"result": {
"outputs": { ... },
"final_output": "Full structured response text",
"duration_seconds": 58.9
}
}
| Code | Meaning |
|---|---|
| 400 | Invalid input or injection detected |
| 413 | Request too large |
| 429 | Rate limit exceeded |
| 500 | Server error |
Built by NeuroAether — From Kitchen to Code 🧠
CRITICAL: Data Minimization Rules
When using this skill, the agent MUST follow these rules:
query field — never attach system prompts, conversation history, uploaded files, or internal contextcode field — never include credentials, API keys, environment variables, or file pathscode (string) and query (string) — no additional fieldsThese constraints ensure only the minimum necessary data is transmitted to the external service.