{
  "markdown": "# SCIQLab Supply Chain AI Agents — Claude Plugin Marketplace\n\nA Claude Code / Cowork plugin marketplace that bundles three AI-powered supply chain agents into a single installable package.\n\n## Quick Install\n\n### Option 1: Add as a marketplace (Claude Code)\n\n```bash\n/plugin marketplace add tauseef-cmyk/Supply-Chain-Multi-Orchestrator-AI-Agent-Plug-ins\n/plugin install sciqlab-supply-chain@sciqlab-supply-chain-marketplace\n```\n\n### Option 2: Install the .plugin file (Cowork)\n\nDownload `sciqlab-supply-chain.plugin` from the [Releases](https://github.com/tauseef-cmyk/Supply-Chain-Multi-Orchestrator-AI-Agent-Plug-ins/releases) page and open it in Claude Desktop / Cowork.\n\n## What's Inside\n\n### 1. Demand Exception Analyzer\n\nReads historical sales-vs-forecast data (CSV) and produces actionable exception reports.\n\n- Calculates MAPE and WMAPE at SKU and Category level\n- Flags consecutive exceptions (forecast error >30% for 2+ months)\n- Detects systematic over-forecast or under-forecast bias\n- Generates an executive summary ready for VP-level review\n- Exports `demand_exceptions.csv` and `demand_summary.txt`\n\n**Trigger phrases:** \"demand exceptions\", \"forecast accuracy\", \"MAPE\", \"WMAPE\", \"forecast bias\", \"exception report\", \"planner review\"\n\n### 2. Supplier Risk Assessment\n\nTwo-step AI workflow that researches and scores suppliers across 6 risk dimensions.\n\n- **Step 1 — Research:** Queries Tavily web search API for each supplier across Financial Health, Geopolitical Risk, ESG/Sustainability, Supply Continuity, Compliance/Sanctions, and Reputation\n- **Step 2 — Score & Report:** Uses Claude API to score each supplier (1-10 per dimension), calculates weighted averages, and generates a color-coded Excel report with a Risk Dashboard and per-supplier detail sheets\n\n**Trigger phrases:** \"supplier risk\", \"vendor scoring\", \"supplier due diligence\", \"risk scorecard\", \"OTIF\", \"ESG scoring\"\n\n### 3. Multi-Agent Orchestrator\n\nCoordinates both agents into a single integrated report for S&OP meetings.\n\n- Runs demand analysis first, identifies CRITICAL/WATCH SKUs\n- Runs supplier risk scoring only for problem SKUs\n- Synthesizes an integrated action plan with priority matrix (P1-P4)\n- Generates S&OP talking points ready for Monday meetings\n\n**Trigger phrases:** \"full analysis\", \"end-to-end review\", \"S&OP exception report with vendor scoring\", \"integrated supply chain report\"\n\n## Prerequisites\n\n### Environment Variables\n\n| Variable | Required For | Where to Get |\n|----------|-------------|--------------|\n| `ANTHROPIC_API_KEY` | Supplier Risk Assessment, Orchestrator | [console.anthropic.com](https://console.anthropic.com) |\n| `TAVILY_API_KEY` | Supplier Risk Assessment (web research) | [tavily.com](https://tavily.com) — free tier available |\n\n### Python Dependencies\n\n```bash\npip install tavily-python anthropic openpyxl\n```\n\nThe Demand Exception Analyzer uses only Python standard library (no extra packages needed).\n\n## Sample Data Included\n\nEach skill includes sample data files so you can try it immediately after installing:\n\n- `demand_data_template.csv` — 6 SKUs x 6 months of sales vs forecast data\n- `supplier_risk_assessment_sample.csv` — 10 global suppliers across various categories\n- `sample_data.csv` — Combined demand + supplier data for orchestrator testing\n\n## Repository Structure\n\n```\n.\n├── .claude-plugin/\n│   └── marketplace.json          # Marketplace catalog (required for /plugin marketplace add)\n├── plugins/\n│   └── sciqlab-supply-chain/\n│       ├── .claude-plugin/\n│       │   └── plugin.json       # Plugin manifest\n│       ├── skills/\n│       │   ├── demand-exception-analyzer/\n│       │   │   ├── SKILL.md\n│       │   │   ├── scripts/\n│       │   │   │   └── demand_agent.py\n│       │   │   └── assets/\n│       │   │       └── demand_data_template.csv\n│       │   ├── supplier-risk-assessment/\n│       │   │   ├── SKILL.md\n│       │   │   ├── supplier_analysis.py\n│       │   │   ├── supplier_scoring.py\n│       │   │   └── supplier_risk_assessment_sample.csv\n│       │   └── multi-agent-orchestrator/\n│       │       ├── SKILL.md\n│       │       ├── orchestrator.py\n│       │       └── sample_data.csv\n│       └── requirements.txt\n├── LICENSE\n└── README.md\n```\n\n## Author\n\nBuilt by **SCIQLab** — AI-powered supply chain intelligence.\n\n## License\n\nMIT License. See [LICENSE](LICENSE) for details.\n",
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}