Add nexus-edge-deployer agent skill v2.1

README.md

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+---
+license: mit
+tags:
+  - agent-skill
+  - infrastructure
+  - enterprise
+  - nexus-ai
+language:
+  - en
+  - es
+library_name: agent-skills
+pipeline_tag: text-generation
+---
+
+# Nexus Edge Deployer
+
+Deploy 1-bit AI models on VPS — AaaS with 98% margins
+
+## Agent Skills Standard
+
+This skill follows the [Agent Skills Standard](https://agentskills.io) and is compatible
+with any LLM agent framework (Claude, ChatGPT, LangChain, AutoGen, CrewAI).
+
+## Usage
+
+Place the SKILL.md file in `.claude/skills/nexus-edge-deployer/SKILL.md` and the agent
+will automatically discover and activate the skill.
+
+## Pricing
+
+$2.00 per execution (outcome-based).
+
+## Publisher
+
+**NEXUS AI Corp** — 68 AI agents, 23 departments, enterprise-grade.
+
+## Category
+
+infrastructure
+
+## Certification
+
+Gold certified (agentskills.io certification program).

SKILL.md

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+---
+name: nexus-edge-deployer
+description: "Deploy 1-bit quantized AI models on cheap VPS for Agent-as-a-Service. Calculate unit economics, provision Hetzner servers, configure Ollama/llama.cpp inference, and manage multi-tenant agent fleets with 98% margins."
+license: proprietary
+compatibility: "NEXUS Ecosystem 1.0"
+metadata:
+  department: devops
+  agents: [edge-deploy, devops-infra]
+  price_per_execution: "$2.00"
+  nexus_version: "1.0"
+  version: "1.0.0"
+  author: "NEXUS AI Corp"
+allowed-tools: web-search web-fetch filesystem
+---
+
+# Edge AI Deployer
+
+Enterprise-grade edge deployment for 1-bit quantized models (PrismML Bonsai, Microsoft BitNet) on minimal infrastructure.
+
+## Capabilities
+- Deploy Bonsai 8B (1.15GB), 4B (0.57GB), and 1.7B (0.24GB) models on VPS
+- Calculate AaaS unit economics: cost per agent, margin per VPS, break-even analysis
+- Configure Ollama or llama.cpp for multi-tenant inference serving
+- Auto-provision Hetzner CX22 (EUR 3.79/mo) via Cloud API
+- Monitor fleet resource usage: RAM, CPU, tokens/sec per agent
+- GDPR/HIPAA compliance via local inference (no data leaves server)
+- Scale from 1 to 100+ agents across VPS fleet
+
+## Workflow
+1. Assess client requirements: model quality, latency, privacy, platform
+2. Select optimal model tier (8B for quality, 4B for balance, 1.7B for mobile)
+3. Provision VPS via Hetzner API with cloud-init (Ollama + model pre-loaded)
+4. Deploy agent with client-specific persona and capabilities
+5. Benchmark inference quality against full-precision baseline
+6. Configure monitoring, alerting, and auto-scaling rules
+7. Generate unit economics report: revenue, cost, margin, projections
+
+## Guidelines
+- Always benchmark 1-bit model quality before deploying to production
+- Maximum 3 Bonsai 8B agents per 4GB VPS (reserve 0.5GB for OS)
+- Maintain cloud API fallback for quality-critical tasks
+- Report cost savings to finance department monthly
+- Authenticate all inference endpoints — never expose publicly
+- Use GGUF format for Ollama compatibility