evaluating-machine-learning-models SKILL.md skillA
evaluating-machine-learning-models from foryourhealth111-pixel/vibe-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add foryourhealth111-pixel/vibe-skills/evaluating-machine-learning-models@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
- foryourhealth111-pixel/vibe-skills
- Path
bundled/skills/evaluating-machine-learning-models/SKILL.md- Versions recorded
- 4
- Latest version
- v1.0.0, committed Apr 28, 2026
- First version recorded
- Feb 26, 2026
- Size
- 1,560 bytes
- Repository stars
- 3,758
- License
- Apache-2.0
Evaluate trained machine learning models with the right metrics and comparison logic. Use for benchmark review, threshold selection, calibration, validation, and model comparison; not for feature engineering or leakage auditing.
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 Evaluation Suite Use this skill when the model exists and the question is whether it is good enough. ## Overview This skill focuses on choosing and interpreting the right evaluation metrics for the problem, then comparing candidate models or thresholds. ## When to Use This Skill - Comparing candidate models with consistent metrics - Reviewing precision/recall/F1/AUC, regression error, calibration, or ranking quality - Stress-testing validation strategy before deployment or publication ## Not For / Boundaries - Building the training pipeline itself: use `scikit-learn` for classical modeling or `ml-pipeline-workflow` for end-to-end workflow ownership - Engineering features: use `preprocessing-data-with-automated-pipelines` - Checking train/test contamination: use `ml-data-leakage-guard` ## Typical Outputs - Metric suite recommendations - Model comparison tables - Notes on threshold tradeoffs, calibration, and validation weaknesses ## Related Skills - `scikit-learn` for class-level error breakdowns and confusion matrices - `scientific-reporting` when the evaluation must become a deliverable
Read the whole file at its exact version.
How to install
mdr add foryourhealth111-pixel/vibe-skills/evaluating-machine-learning-models@sha256:29dd1c57e2ae537fThe 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_pfnediybo2ftzieu)
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Versions
The registry has recorded 4 versions of this file, between Feb 26, 2026 and Apr 28, 2026, about one every 20 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v1.0.0 latest | 2026-04-28 | f550004 | 1,560 B | A | view · diff |
| v1.0.0 | 2026-04-27 | 8e5b0d2 | 1,495 B | A | view · diff |
| v1.0.0 | 2026-04-18 | 11fb2de | 1,486 B | A | view · diff |
| v1.0.0 | 2026-02-26 | 1632f40 | 3,495 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 (1560 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
foryourhealth111-pixel/vibe-skills · 3,758 stars · license Apache-2.0 · pushed 2026-10-22 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_pfnediybo2ftzieu GET https://markdownregistry.com/api/v1/resolve?ref=foryourhealth111-pixel/vibe-skills/evaluating-machine-learning-models GET https://markdownregistry.com/api/v1/blob/29dd1c57e2ae537f01912b5a1f24c4509b98bb84f800ee49136f6da63f06f2f1
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.