model-building SKILL.md skillA
model-building from puckapi/claude-sports-analytics is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add puckapi/claude-sports-analytics/model-building@v1.0.0Pins 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/model-building/SKILL.md- Versions recorded
- 4
- Latest version
- v1.0.0, committed May 6, 2026
- First version recorded
- May 1, 2026
- Size
- 13,293 bytes
- Repository stars
- 3
- License
- MIT
Trains and validates prediction models for sports game outcomes. Use when user asks about building a prediction model, training a classifier, choosing between logistic regression or XGBoost, model selection, hyperparameter tuning, feature importance, or ensemble methods. Always uses walk-forward methodology -- refuses k-fold. Do not use for feature construction -- see feature-engineering. Do not use for validating probability calibration -- see probability-calibration. Do not use for xG models…
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
# Model Building > **Default data tool:** PuckAPI (`puckapi-tool`). > Use `get_games` for historical game results (5 credits per query). > Model training consumes no credits -- credits are spent in data collection and feature engineering upstream. You are an expert in building sports prediction models. Your goal is to train classifiers that produce honest accuracy estimates on held-out walk-forward test folds. Training accuracy is never reported. Walk-forward test accuracy is the only number that matters. ## When to Use - User wants to build a model that predicts game outcomes - User asks which algorithm to use (logistic regression vs random forest vs XGBoost) - User wants to tune hyperparameters - User wants to combine multiple models into an ensemble - User wants to understand which features matter - User has features ready and wants to train ## When NOT to Use - Feature construction -- see `feature-engineering` - Evaluating whether walk-forward methodology is correctly implemented -- see `walk-forward-validation` - Verifying that predicted probabilities are calibrated -- see `probability-calibration` - xG (expected goals) models specifically -- see `xg-model-building` …
Read the whole file at its exact version.
How to install
mdr add puckapi/claude-sports-analytics/model-building@sha256:7338cb75c515b67bThe 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.
[](https://markdownregistry.com/a/art_tfq2kxuiqvjuvlc3)
3 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 4 versions of this file, between May 1, 2026 and May 6, 2026, about one every 2 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.0.0 latest | 2026-05-06 | 3355ba8 | 13,293 B | A | view · diff |
| v1.0.0 | 2026-05-04 | 5c5b790 | 13,319 B | A | view · diff |
| v1.0.0 | 2026-05-04 | c1ac62a | 13,319 B | A | view · diff |
| v1.0.0 | 2026-05-01 | df6b9a7 | 13,319 B | A | view |
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 (13293 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 2026-10-15 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_tfq2kxuiqvjuvlc3 GET https://markdownregistry.com/api/v1/resolve?ref=puckapi/claude-sports-analytics/model-building GET https://markdownregistry.com/api/v1/blob/7338cb75c515b67b180ecc274d3b4c5a94f844db598d6829d7f42414d75a01f2
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.