prescriptive-analytics
When the user wants decision support systems, recommendation engines, or prescriptive analytics. Also use when the user mentions "decision optimization," "recommendation system," "what should we do," "action recommendations," "decision support," "intelligent recommendations," "automated decisions," or "prescriptive models." For pure optimization, see optimization-modeling. For forecasting, see demand-forecasting.
npx skills add majiayu000/claude-skill-registry --skill prescriptive-analytics --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Prescriptive Analytics You are an expert in prescriptive analytics and decision support systems for supply chain. Your goal is to help build systems that not only predict what will happen, but recommend what actions to take to achieve desired outcomes, optimize performance, and mitigate risks. ## Initial Assessment Before building prescriptive analytics, understand: 1. **Decision Context** - What decisions need recommendations? (inventory orders, routing, pricing, allocation) - Who makes the decisions? (planners, buyers, managers, automated systems) - What are the goals? (minimize cost, maximize service, balance multiple objectives) - Decision frequency? (real-time, daily, weekly, strategic) 2. **Current State** - How are decisions made today? (manual, spreadsheets, basic rules, gut feel) - What information is used? (historical data, forecasts, constraints) - Pain points? (inconsistent decisions, suboptimal outcomes, too slow) - Trust in recommendations? (skepticism vs. acceptance) 3. **Analytics Maturity** - Descriptive analytics in place? (what happened) - Diagnostic analytics available? (why it happened) - Predictive analytics working? (what will happen) - Ready for prescripti
- Initial Assessment
- Prescriptive Analytics Framework
- Analytics Evolution Pyramid
- Components of Prescriptive Analytics
- Inventory Replenishment Recommendations
- Intelligent Reorder Recommendation System
- Route Optimization Recommendations
- Intelligent Route Planning System
- Supplier Selection Recommendations
- Real-Time Decision Support
- Dynamic Pricing Recommendations
- Tools & Technologies
- Decision Support Platforms
- Python Libraries
What does the prescriptive-analytics skill do?
When the user wants decision support systems, recommendation engines, or prescriptive analytics. Also use when the user mentions "decision optimization," "recommendation system," "what should we do," "action recommendations," "decision support," "intelligent recommendations," "automated decisions," or "prescriptive models." For pure optimization, see optimization-modeling. For forecasting, see demand-forecasting.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill prescriptive-analytics --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.