AetherLang Strategy Ω V3 — Nobel-Level Business Intelligence
name: aetherlang-strategy
by contrario · published 2026-03-22
$ claw add gh:contrario/contrario-aetherlang-strategy---
name: aetherlang-strategy
description: Nobel-level strategic business intelligence with game theory, Monte Carlo simulations, market analysis, and implementation roadmaps.
version: 2.0.0
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
---
# AetherLang Strategy Ω V3 — Nobel-Level Business Intelligence
> Game theory, Monte Carlo simulations, behavioral economics, and competitive war gaming. The most advanced AI strategy engine available.
**Source Code**: [github.com/contrario/aetherlang](https://github.com/contrario/aetherlang)
**Author**: NeuroAether (info@neurodoc.app)
**License**: MIT
Privacy & Data Handling
⚠️ **External API Notice**: This skill sends queries to `api.neurodoc.app` for processing.
What This Skill Does
Three V3 strategy engines in one skill:
📈 APEX Strategy V3 — Nobel-Level Analysis
Every response includes:
📊 Market Intel V3
💼 NEXUS-7 Consult V3
Usage
Ask naturally about any business/strategy topic:
API Details
POST https://api.neurodoc.app/aetherlang/execute
Content-Type: application/jsonAPEX Strategy Flow
{
"code": "flow Strategy {\n using target \"neuroaether\" version \">=0.2\";\n input text query;\n node Guard: guard mode=\"MODERATE\";\n node Engine: apex analysis=\"strategic\";\n Guard -> Engine;\n output text report from Engine;\n}",
"query": "Your strategy question here"
}Market Intel Flow
{
"code": "flow Market {\n using target \"neuroaether\" version \">=0.2\";\n input text query;\n node Engine: marketing analysis=\"competitive\";\n output text report from Engine;\n}",
"query": "Your market question here"
}Response
Returns structured Greek output with markdown headers. Typical response: 4000-8000 characters covering all mandatory sections with quantified data.
Languages
Technology
---
*Built by NeuroAether — From Kitchen to Code* 🧠
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