sciqlab-supply-chain
Three AI agents for supply chain operations — demand exception analysis, supplier risk scoring, and a multi-agent orchestrator for S&OP revi
Open source Repository Open in the app JSON README (API)
About
Three AI agents for supply chain operations — demand exception analysis, supplier risk scoring, and a multi-agent orchestrator for S&OP reviews. This plugin gives supply chain teams AI-powered demand planning and supplier risk intelligence, directly inside Claude. It includes three skills that work independently or together: Demand Exception Analyzer — Upload a CSV of historical sales vs forecast data and get MAPE/WMAPE calculations, forecast bias detection, consecutive exception flagging, and a VP-ready executive summary in seconds. Supplier Risk Assessment — Provide a list of suppliers and the agent researches each one via web search, then scores them across 6 risk dimensions (Financial Health, Geopolitical Risk, ESG, Supply Continuity, Compliance, Reputation) and generates a color-coded Excel report. Multi-Agent Orchestrator — Combines both agents into a single workflow: runs demand analysis first, identifies problem SKUs, then scores suppliers for those SKUs, and produces an integr
Details
- Kind
- Plugins
- Topic
- Files & documents
- Publisher
- tauseef-cmyk
- Origin
- marketplace
- Category
- ferramentas
- Stars
- 2
- Last push
- 2026-04-25T04:22:42Z
- Repository state
- ativo
- Language
- Python
- License
- MIT
- Added
- 2026-08-30 01:48:58
- Updated
- 2026-08-30 01:48:58
- Origin id
tauseef-cmyk/supply-chain-multi-orchestrator-ai-agent-plug-ins/sciqlab-supply-chain
README
# SCIQLab Supply Chain AI Agents — Claude Plugin Marketplace A Claude Code / Cowork plugin marketplace that bundles three AI-powered supply chain agents into a single installable package. ## Quick Install ### Option 1: Add as a marketplace (Claude Code) ```bash /plugin marketplace add tauseef-cmyk/Supply-Chain-Multi-Orchestrator-AI-Agent-Plug-ins /plugin install sciqlab-supply-chain@sciqlab-supply-chain-marketplace ``` ### Option 2: Install the .plugin file (Cowork) Download `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. ## What's Inside ### 1. Demand Exception Analyzer Reads historical sales-vs-forecast data (CSV) and produces actionable exception reports. - Calculates MAPE and WMAPE at SKU and Category level - Flags consecutive exceptions (forecast error >30% for 2+ months) - Detects systematic over-forecast or under-forecast bias - Generates an executive summary ready for VP-level review - Exports `demand_exceptions.csv` and `demand_summary.txt` **Trigger phrases:** "demand exceptions", "forecast accuracy", "MAPE", "WMAPE", "forecast bias", "exception report", "planner review" ### 2. Supplier Risk Assessment Two-step AI workflow that researches and scores suppliers across 6 risk dimensions. - **Step 1 — Research:** Queries Tavily web search API for each supplier across Financial Health, Geopolitical Risk, ESG/Sustainability, Supply Continuity, Compliance/Sanctions, and Reputation - **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 **Trigger phrases:** "supplier risk", "vendor scoring", "supplier due diligence", "risk scorecard", "OTIF", "ESG scoring" ### 3. Multi-Agent Orchestrator Coordinates both agents into a single integrated report for S&OP meetings. - Runs demand analysis first, identifies CRITICAL/WATCH SKUs - Runs supplier risk scoring only for problem SKUs - Synthesizes an integrated action plan with priority matrix (P1-P4) - Generates S&OP talking points ready for Monday meetings **Trigger phrases:** "full analysis", "end-to-end review", "S&OP exception report with vendor scoring", "integrated supply chain report" ## Prerequisites ### Environment Variables | Variable | Required For | Where to Get | |----------|-------------|--------------| | `ANTHROPIC_API_KEY` | Supplier Risk Assessment, Orchestrator | [console.anthropic.com](https://console.anthropic.com) | | `TAVILY_API_KEY` | Supplier Risk Assessment (web research) | [tavily.com](https://tavily.com) — free tier available | ### Python Dependencies ```bash pip install tavily-python anthropic openpyxl ``` The Demand Exception Analyzer uses only Python standard library (no extra packages needed). ## Sample Data Included Each skill includes sample data files so you can try it immediately after installing: - `demand_data_template.csv` — 6 SKUs x 6 months of sales vs forecast data - `supplier_risk_assessment_sample.csv` — 10 global suppliers across various categories - `sample_data.csv` — Combined demand + supplier data for orchestrator testing ## Repository Structure ``` . ├── .claude-plugin/ │ └── marketplace.json # Marketplace catalog (required for /plugin marketplace add) ├── plugins/ │ └── sciqlab-supply-chain/ │ ├── .claude-plugin/ │ │ └── plugin.json # Plugin manifest │ ├── skills/ │ │ ├── demand-exception-analyzer/ │ │ │ ├── SKILL.md │ │ │ ├── scripts/ │ │ │ │ └── demand_agent.py │ │ │ └── assets/ │ │ │ └── demand_data_template.csv │ │ ├── supplier-risk-assessment/ │ │ │ ├── SKILL.md │ │ │ ├── supplier_analysis.py │ │ │ ├── supplier_scoring.py │ │ │ └── supplier_risk_assessment_sample.csv │ │ └── multi-agent-orchestrator/ │ │ ├── SKILL.md │ │ ├── orchestrator.py │ │ └── sample_data.csv │ └── requirements.txt ├── LICENSE └── README.md ``` ## Author Built by **SCIQLab** — AI-powered supply chain intelligence. ## License MIT License. See [LICENSE](LICENSE) for details.