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analyze-copper-supply-concentration-risk

Quantify global copper supply concentration risk with HHI, CR4, and CR8 metrics.

3|1|Updated Jan 12, 2026
Search Tags:#scenario#analyze#risk#concentration#replacement#data-sources#copper
One-click install
npx skills add https://github.com/fatfingererr/macro-skills --skill analyze-copper-supply-concentration-risk
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: analyze-copper-supply-concentration-risk
Source: https://github.com/fatfingererr/macro-skills/tree/main/skills/analyze-copper-supply-concentration-risk
Command: npx skills add https://github.com/fatfingererr/macro-skills --skill analyze-copper-supply-concentration-risk

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, matplotlib, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill quantifies whether global copper supply is overly concentrated, whether major producing countries show structural decline, and whether substitutes can close supply gaps under different demand scenarios, using publicly available data.

Core Features & Use Cases

  • Analyze market concentration indicators (HHI, CR4, CR8) across countries and over time.
  • Assess Chile's structural trend, including peak-to-trough dynamics and potential breakpoints.
  • Evaluate replacement potential from Peru and DRC under multiple demand scenarios.
  • Output Bloomberg-style visualizations and JSON/Markdown reports for stakeholder communication.

Quick Start

Start by running the included workflow to fetch data, compute metrics, and generate outputs. Use the quick check to get an immediate snapshot: python scripts/copper_concentration_analyzer.py --quick; for full analysis, run with start/end years and output options as needed.

Frequently Asked Questions about analyze-copper-supply-concentration-risk

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I analyze copper supply concentration risk using public data?▼

This Skill quantifies copper supply concentration risk by computing HHI, CR4, and CR8 indicators across countries over time using public data. It generates Bloomberg-style visualizations alongside JSON and Markdown reports for stakeholder communication.

How do I calculate HHI and CR4 metrics for mining market concentration in Python?▼

You calculate HHI, CR4, and CR8 metrics for copper market concentration using Python with pandas and numpy. The workflow processes historical production data to quantify market dominance and structural shifts over time.

Can I assess Chile's copper production decline and replacement potential from Peru and DRC?▼

Yes, you can assess Chile's structural decline by analyzing peak-to-trough dynamics and breakpoints, then evaluate replacement potential from Peru and DRC under multiple demand scenarios to determine if they can close supply gaps.

Does this concentration risk analysis require matplotlib for generating reports?▼

Yes, generating Bloomberg-style visualizations requires matplotlib, while reproducible workflows output JSON and Markdown reports. The analysis depends on pandas, numpy, and matplotlib to compute concentration metrics and produce stakeholder-ready outputs.

What is the best way to run a quick copper supply risk snapshot check?▼

The best way to run a quick copper supply risk snapshot is executing the analyzer script with the quick flag. For full analysis, specify start and end years with output options to generate complete concentration metrics and visualizations.

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