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Analyze re-rate scores and nine-factor breakdowns for junior precious-metals miners.
Copy the install command and let the AI configure it · recommended for beginners
Please install the "io.github.Gren70/gold-silver-analytics" MCP server from askskill: Run: claude mcp add --transport http 'io-github-gren70-gold-silver-analytics' 'https://gold-silver-analytics-mcp-production.up.railway.app/mcp'
List the junior precious-metals miners with the highest re-rate scores and briefly explain the strongest points in their nine-factor breakdowns.
A list of top-scoring companies with a brief summary of each firm's key scoring strengths.
Compare the re-rate scores and nine-factor breakdowns of two junior precious-metals miners and highlight the main differences.
A side-by-side comparison showing differences in overall scores and factor-level performance.
Find junior precious-metals miners that stand out on a specific factor in the nine-factor model and rank them by re-rate score.
A ranked list of matching companies sorted by overall re-rate score.
Researchers or data analysts tracking precious-metals miners can use this tool to review re-rate scores and nine-factor breakdowns across about 300 companies, then prioritize which ones deserve deeper analysis.
When comparing the relative performance of multiple junior precious-metals miners, this tool provides a consistent scoring framework that helps produce more structured comparison results.
No documentation provided
Check the source repo for usage and examples.
It provides Analytical Re-Rate (RR) scores for about 300 junior precious-metals miners, along with nine-factor breakdowns. You can use it to review both overall scores and factor-level performance.
Based on the description, it covers about 300 junior precious-metals miners. For the exact coverage and company list, see the source repository.
No documentation excerpt is provided, so the installation steps, dependencies, and prerequisites cannot be confirmed here. Please see the source repository.
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