ai-hockey-workflow skillA
ai-hockey-workflow is agent-read markdown (skill) from puckapi/claude-sports-analytics: 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 mechanics .
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns 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
mdr add puckapi/claude-sports-analytics/ai-hockey-workflow@v1.0.0mdr add puckapi/claude-sports-analytics/ai-hockey-workflow@sha256:82f4bff38e85126ePin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_x74gn5jmjkrgyx4z)
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Versions
Audit of the latest version
- 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
puckapi/claude-sports-analytics · 3 stars · license MIT · pushed 2026-09-21 · 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
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