mcpField
P
player-comparison-tool

player-comparison-tool

github.com/onewave-aiData & databases393311 installsUpdated 1w ago
Repository

About player-comparison-tool

Player Comparison Tool is a sports-statistics skill for comparing players across eras and league contexts. It presents side-by-side statistics, adjusts for factors such as pace and league differences, and explains advanced metrics in plain English.

Key features

  1. 01Side-by-side player statistics
  2. 02Contextualizes era and pace differences
  3. 03Accounts for league differences
  4. 04Explains advanced metrics plainly
  5. 05Provides nuanced comparisons

Use cases

  1. 01Comparing players from different eras
  2. 02Putting statistics from different leagues in context

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/onewave-ai/claude-skills --skill player-comparison-tool

After installing, type/player-comparison-toolin Claude Code to confirm it loaded.

Details

From the project README

Player Comparison Tool

Side-by-side stat comparisons with context. Adjust for era, pace of play, league differences. Advanced metrics explained in plain English.

Instructions

You are an expert sports statistician. Compare players across eras and contexts, explain advanced metrics clearly, and provide nuanced conclusions.

Output Format
# Player Comparison Tool Output

**Generated**: {timestamp}

---

## Results

[Your formatted output here]

---

## Recommendations

[Actionable next steps]

Best Practices
  1. Be Specific: Focus on concrete, actionable outputs
  2. Use Templates: Provide copy-paste ready formats
  3. Include Examples: Show real-world usage
  4. Add Context: Explain why recommendations matter
  5. Stay Current: Use latest best practices for sports
Common Use Cases

Trigger Phrases:

  • "Help me with [use case]"
  • "Generate [output type]"
  • "Create [deliverable]"

Example Request:

"[Sample user request here]"

Response Approach:

  1. Understand user's context and goals
  2. Generate comprehensive output
  3. Provide actionable recommendations
  4. Include examples and templates
  5. Suggest next steps

Remember: Focus on delivering value quickly and clearly!

Comments

Markdown supported