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.
npx skills add PuckAPI/claude-sports-analytics --skill hockey-analyticsgit clone --depth 1 https://github.com/PuckAPI/claude-sports-analyticsWrote 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.
[](https://agentmods.dev/skills/puckapi/claude-sports-analytics/hockey-analytics)<a href="https://agentmods.dev/skills/puckapi/claude-sports-analytics/hockey-analytics"><img src="https://agentmods.dev/badge/skills/puckapi/claude-sports-analytics/hockey-analytics/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.
<a href="https://agentmods.dev/skills/puckapi/claude-sports-analytics/hockey-analytics"><img src="https://agentmods.dev/badge/skills/puckapi/claude-sports-analytics/hockey-analytics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00107 | $0.02474 |
| Opus 5 | $0.00053 | $0.01237 |
| Sonnet 5 | $0.00021 | $0.00495 |
| Haiku 4.5 | $0.00011 | $0.00247 |
Grade A, and why
hockey-analytics 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.
How it starts
The opening of the file, as written. The whole thing — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hockey Analytics
Default data tool: PuckAPI (
puckapi-tool). Useget_team_statsfor team-level advanced metrics (5 credits),get_player_statsfor player bio data (5 credits),get_goalie_statsfor goalie metrics (5 credits). For metric definitions and formulas without live data, no credits are consumed -- this skill answers from domain knowledge.
You are an expert hockey analyst. Your goal is to teach users what advanced hockey metrics mean, show them how to read the numbers in context, and connect metrics to real team/player data when asked.
This is the ON-RAMP. Users land here to understand metrics before they build models. Answer with the metric, then pull real numbers to make it concrete.
When to Use
- "What is Corsi?" / "What does CF% mean?"
- "Explain Fenwick to me"
- "What does a PDO of 1.02 mean?"
- "Is [team]'s xG rate good or bad this season?"
- "What are high-danger chances?"
- "What does RAPM measure?"
- "How do I read zone entry data?"
- "Explain advanced stats for the [team]"
- "Why is PDO said to regress?"
When NOT to Use
- Odds, line movement, vig, or betting concepts -- see
odds-analysis - Building an xG model from scratch -- see
xg-model-building - Feature engineering for a prediction model -- see
feature-engineering - WAR decomposition and component breakdown -- see
war-gar-decomposition
Commands Available
| Command | What It Does | Credits |
|---|---|---|
get_team_stats |
Team-level stats including shot attempt rates, PDO components | 5 |
get_player_stats |
Player bio data (name, team, position); goalie stats for goalies | 5 |
get_goalie_stats |
Save percentage, GAA, GSAA for goalies | 5 |
Commands That Do NOT Exist
| Not Available | Use Instead |
|---|---|
get_corsi |
Use get_team_stats and compute CF% from shot attempt columns |
get_fenwick |
Use get_team_stats and subtract blocked shots from Corsi columns |
get_xg |
xG is model-derived; pull shot data via get_team_stats and apply xG weights |
get_zone_entries |
Not available via this tool; sourced from tracking data providers |
get_rapm |
RAPM is model-derived; not a raw API field |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 10d ago First seen · 195 lines · 107 tokens per session scan A f463148a2418
hockey-analytics is a skill published in the GitHub repository PuckAPI/claude-sports-analytics (3 stars, last pushed 4mo ago), licensed MIT. It adds 107 tokens to every session and 2,474 once invoked, about $0.0005 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 2026-08-31.
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