Tech Hub Skills

200+ production-ready AI agent skills for Claude Code and GitHub Copilot.

Features a hierarchical multi-agent system with a Brainstorm → Plan → Implement workflow, 95% token efficiency, and advanced domain expertise.

Quick Install

For Claude Code (CLI)

npx tech-hub-skills install

For GitHub Copilot (VSCode)

npx tech-hub-skills install --copilot

This creates .github/copilot-instructions.md with all expert skills.

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v2.2: Hierarchical Agent Architecture

95% token reduction with on-demand skill loading and intelligent coordination.

Multi-Agent Hierarchy

1. Orchestrator Agent (visible) - The master coordinator. Analyzes requests, brainstorms approaches, and creates execution plans.
2. 5 Lead Agents (visible) - Domain experts for AI/ML, Platform, Security, Data, and Product development.
3. 25 Specialist Agents (internal) - Deep technical specialists (e.g., AI Engineer, MLOps, SRE) loaded dynamically by Leads.

Workflow: Brainstorm → Plan → Implement

• Brainstorm: Understands requirements, constraints, and risks BEFORE acting.
• Plan: Scans registries to select ONLY the needed skills (typically 3-7 per task).
• Implement: Executes step-by-step with validation checkpoints and adaptive planning.

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What's Included

• 200+ Skills: LLMs, RAG, MLOps, DevSecOps, Lakehouse, Cloud (AWS/Azure/GCP), and more.
• Lazy-Loading: Significant token savings via internal skill registries.
• Security First: Built-in PII detection, security hardening, and compliance automation.
• Cost Aware: AI/ML cost optimization and efficient tool usage.

Usage

Claude Code - Slash Commands

Route directly to the master coordinator or domain leads:

# Recommended entry point (Full Workflow)
/orchestrator "Build a customer churn prediction model"

# Domain specific
/ai       # AI, ML, and Data Science
/platform # DevOps and Cloud Infrastructure
/security # Security and Compliance
/data     # Data Engineering
/product  # Full-stack Development

GitHub Copilot

Copilot automatically applies expert knowledge via instructions. Reference roles in comments to steer:

# Using AI Engineer approach for RAG pipeline
def build_rag_system():
    pass

# Apply Security Architect best practices
def handle_user_upload(file_data):
    pass

Available Lead Roles

Lead	Domain	Specialists
AI/ML Lead	AI, ML, Data Science	AI Engineer, ML Engineer, Data Scientist, MLOps
Platform Lead	Infrastructure, DevOps	DevOps, SRE, Platform Eng, Network, Docker, Cloud, FinOps
Security Lead	Security, Compliance	Security Architect, Compliance Officer, Security Hardener
Data Lead	Data Engineering	Data Engineer, Data Governance, Database Admin
Product Lead	Product Development	Product Designer, Frontend/Backend Dev, QA, Tech Writer

Documentation

• Full System: AGENTS.md
• GitHub Copilot Guide: GITHUB_COPILOT.md
• Changelog: CHANGELOG.md

License

MIT