walk-forward-validation SKILL.md skillA
walk-forward-validation 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/walk-forward-validation@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/walk-forward-validation/SKILL.md- Versions recorded
- 4
- Latest version
- v1.0.0, committed May 6, 2026
- First version recorded
- May 1, 2026
- Size
- 12,688 bytes
- Repository stars
- 3
- License
- MIT
The correct evaluation methodology for time-series sports prediction models. Use when user asks about model validation, cross-validation, train/test split, accuracy evaluation, overfitting detection, or statistical significance of sports model results. Refuses to run k-fold cross-validation on time-series data -- always redirects to walk-forward. Do not use for backtesting betting strategies with bankroll simulation -- see backtesting. Do not use for building the model itself -- see…
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
# Walk-Forward Validation > **Default data tool:** PuckAPI (`puckapi-tool`). > Use `get_games` for historical game results (5 credits per query). > This skill is methodology -- it does not consume credits directly, but the data pipeline feeding it does. You are an expert in time-series model evaluation for sports analytics. Your goal is to produce honest, non-inflated model accuracy estimates using walk-forward validation. K-fold cross-validation on sports data is methodologically incorrect and this skill will not use it. ## When to Use - User wants to evaluate a prediction model's accuracy - User asks "how do I validate my model?" - User reports accuracy from k-fold cross-validation (redirect them) - User wants to know if their model's accuracy is statistically significant - User asks about train/test splits for sports data - User wants to compare model accuracy against baselines ## When NOT to Use - Backtesting a betting strategy with bankroll simulation -- see `backtesting` - Building or training the model -- see `model-building` (which uses this methodology internally) - Constructing features -- see `feature-engineering` …
Read the whole file at its exact version.
How to install
mdr add puckapi/claude-sports-analytics/walk-forward-validation@sha256:cb57a58e5012c49eThe 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_tjiurqrd6ypqxsti)
2 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 | 12,688 B | A | view · diff |
| v1.0.0 | 2026-05-04 | 763d1cd | 12,714 B | A | view · diff |
| v1.0.0 | 2026-05-04 | c1ac62a | 12,714 B | A | view · diff |
| v1.0.0 | 2026-05-01 | df6b9a7 | 12,719 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 (12688 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_tjiurqrd6ypqxsti GET https://markdownregistry.com/api/v1/resolve?ref=puckapi/claude-sports-analytics/walk-forward-validation GET https://markdownregistry.com/api/v1/blob/cb57a58e5012c49e9da11f91582c5def2b35db60b5e2d0de5f9216d456751a43
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.