bracket-predictor

bracket-predictor is a skill for Claude Code, Codex from OneWave-AI/claude-skills. It costs 31 tokens per session (322 once invoked), scanned A, original, MIT.

A guide for making March Madness and other playoff tournament bracket picks. It covers likely winners, possible upsets, historical patterns, and confidence for each selection.

In plain words
What is it for?
Building tournament brackets, identifying upset candidates, and explaining the reasoning behind each pick.
Why use it?
It gives a structured way to compare safe picks with riskier choices when filling out a tournament bracket.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Building tournament brackets, identifying upset candidates, and explaining the reasoning behind each pick.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/onewave-ai/claude-skills/bracket-predictor
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add OneWave-AI/claude-skills --skill bracket-predictor
Clone the repo
git clone --depth 1 https://github.com/OneWave-AI/claude-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for bracket-predictor

README.md
[![agentmods](https://agentmods.dev/badge/skills/onewave-ai/claude-skills/bracket-predictor/github.svg)](https://agentmods.dev/skills/onewave-ai/claude-skills/bracket-predictor)
Your own site
<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/bracket-predictor"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/bracket-predictor/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for bracket-predictor

Your own site · 80×15
<a href="https://agentmods.dev/skills/onewave-ai/claude-skills/bracket-predictor"><img src="https://agentmods.dev/badge/skills/onewave-ai/claude-skills/bracket-predictor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 31 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 322 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00031 $0.00322
Opus 5 $0.00015 $0.00161
Sonnet 5 $0.00006 $0.00064
Haiku 4.5 $0.00003 $0.00032

Measured 10d ago against content hash d0d16eb882df, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

bracket-predictor scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

bracket-predictor/SKILL.md · 60 lines

What it actually says

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!

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 60 lines · 31 tokens per session scan A d0d16eb882df

Subscribe to this mod's changes

bracket-predictor is a skill published in the GitHub repository OneWave-AI/claude-skills (288 stars, last pushed 29d ago), licensed MIT. It adds 31 tokens to every session and 322 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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