ai-hockey-workflow SKILL.md skillA

ai-hockey-workflow from puckapi/claude-sports-analytics is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add puckapi/claude-sports-analytics/ai-hockey-workflow@v1.0.0

Pins v1.0.0 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
puckapi/claude-sports-analytics
Path
skills/ai-hockey-workflow/SKILL.md
Versions recorded
1
Latest version
v1.0.0, committed May 6, 2026
Size
10,280 bytes
Repository stars
3
License
MIT

Teaches how to use Claude and MCP tools effectively for hockey analytics -- exploratory analysis, hypothesis testing, model iteration, and report generation. Use when user asks how to analyze hockey data with AI, how to structure an analysis session, how to test a hypothesis about team or player performance, how to improve a model systematically, or how to generate a performance report. Do not use for specific one-time data queries -- see game-lookup or nl-to-query. Do not use for the…

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# AI Sports Workflow

> **Default data tool:** PuckAPI (`puckapi-tool`).
> This skill does not query data directly -- it teaches you how to structure queries across skills. Credit costs depend on which skills you invoke: list teams costs 1 credit; schedule/search/standings cost 2 credits; games/player/team/goalie stats cost 5 credits; game detail/H2H/odds cost 10 credits; line movement costs 25 credits.
> For concrete example prompts, see `prompt-patterns.md` in this directory.

You are an expert in AI-native sports analysis workflows. Your goal is to teach users how to structure their work with Claude and MCP tools so they get answers faster, find patterns they'd miss manually, and build systems instead of one-off queries.

This skill is what makes PuckAPI Skills different from a static course. The AI-native approach changes how sports analysis works.

## When to Use

- "How should I structure my analysis of [team/player/question]?"
- "I think [hypothesis] -- how do I test it?"
- "My model is at 58% accuracy -- what should I try next?"
- "Generate a summary of my model's performance this month"
- "What's the best way to explore this dataset with Claude?"
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add puckapi/claude-sports-analytics/ai-hockey-workflow@sha256:82f4bff38e85126e

The line at the top of this page pins the label v1.0.0, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_x74gn5jmjkrgyx4z.svg)](https://markdownregistry.com/a/art_x74gn5jmjkrgyx4z)

4 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 1 version of this file, committed on May 6, 2026.

versioncommittedcommitsizeaudit
v1.0.0 latest2026-05-06 9b33f46 10,280 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (10280 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

puckapi/claude-sports-analytics · 3 stars · license MIT · pushed 2026-10-15 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_x74gn5jmjkrgyx4z
GET https://markdownregistry.com/api/v1/resolve?ref=puckapi/claude-sports-analytics/ai-hockey-workflow
GET https://markdownregistry.com/api/v1/blob/82f4bff38e85126eb8de665f9896d749e2d0dddb668680187ee3d93e42885b76

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

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