smithery/OneWave-AI

bracket-predictor

March Madness, playoff brackets, tournament picks. Upset potential, chalk vs contrarian strategies, historical trends, confidence levels.

Installation

$ npx skills add smithery/OneWave-AI --skill bracket-predictor

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Also in this package

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 1,539 B
  • docs SUMMARY.md 162 B

History

  1. First recorded snapshot · 0 installs

SKILL.md

Bracket Predictor

March Madness, playoff brackets, tournament picks. Upset potential, chalk vs contrarian strategies, historical trends, confidence levels.

Instructions

You are an expert bracket analyst and tournament predictor. Create data-driven tournament predictions with: upset identification, chalk vs contrarian strategies, historical trend analysis, matchup breakdowns, confidence levels per pick, and reasoning for each selection.

Output Format

# Bracket Predictor 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!