probability-calibration SKILL.md skillA
probability-calibration 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/probability-calibration@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/probability-calibration/SKILL.md- Versions recorded
- 3
- Latest version
- v1.0.0, committed May 6, 2026
- First version recorded
- May 1, 2026
- Size
- 11,249 bytes
- Repository stars
- 3
- License
- MIT
Verifies and corrects model probability outputs so predicted win percentages match actual win rates. Use when user asks about calibration, reliability diagrams, Brier score, Platt scaling, isotonic regression, probability quality, or whether model probabilities are accurate. Also use when user has a trained model and wants to know if outputs can be trusted for betting. Do not use for odds math or devigging -- see odds-analysis instead. Do not use for model training -- see model-building instead.
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
# Probability Calibration > **Default data tool:** PuckAPI (`puckapi-tool`). > Use `get_games` (5 credits) to retrieve historical results for calibration analysis. > Calibration works on model outputs vs actual outcomes -- no specialized endpoint needed. > Credits consumed only if fetching results data; calibration math uses your model outputs directly. You are an expert in probability calibration for sports prediction models. Your goal is to verify that a model's stated win probabilities match observed win rates, then correct systematic bias when they don't. This is the most commonly skipped step in sports analytics and the one that breaks downstream betting calculations the most. A model that outputs 0.63 win probability is useless until you know whether 63% actually means 63%. If it really means 55%, every downstream calculation -- expected value, Kelly sizing, edge detection -- is wrong. ## When to Use - User has a trained model and wants to know if probabilities can be trusted - User is seeing unexplained losses despite positive expected value - User wants to compare model probability against devigged market odds …
Read the whole file at its exact version.
How to install
mdr add puckapi/claude-sports-analytics/probability-calibration@sha256:7bb77f7c8dcc6fa5The 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_ulek2wd6gwp43w2k)
4 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 3 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 | 11,249 B | A | view · diff |
| v1.0.0 | 2026-05-04 | c1ac62a | 11,275 B | A | view · diff |
| v1.0.0 | 2026-05-01 | df6b9a7 | 11,274 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 (11249 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_ulek2wd6gwp43w2k GET https://markdownregistry.com/api/v1/resolve?ref=puckapi/claude-sports-analytics/probability-calibration GET https://markdownregistry.com/api/v1/blob/7bb77f7c8dcc6fa5fb38ffe5ac0cf2309f35732af515b2d0a1287d42ef76ecc9
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.