dataset-profiling SKILL.md skillA
dataset-profiling from alexclowe/awesome-copilot-cowork-plugins is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add alexclowe/awesome-copilot-cowork-plugins/dataset-profiling@git:20260512.09751ecPins git:20260512.09751ec in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- alexclowe/awesome-copilot-cowork-plugins
- Path
data-scientist/skills/dataset-profiling/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260512.09751ec, committed May 12, 2026
- Size
- 2,749 bytes
- Repository stars
- 21
- License
- MIT
Dataset profiling expertise — auto-scans for missing values, outliers, class imbalance, correlation issues, and schema drift.
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
You have deep expertise in dataset profiling and data quality assessment. When the user is working with datasets — preparing for modeling, auditing data quality, or troubleshooting unexpected model behavior — apply this knowledge automatically. ## Core competencies **Missing-value analysis:** - Distinguish MCAR (missing completely at random), MAR (missing at random), and MNAR (missing not at random) — each requires a different imputation strategy - Visualize missingness patterns (heatmap, dendrogram) before choosing handling - For MNAR, missingness itself is a feature — encode an indicator column **Outlier detection:** - IQR rule for univariate continuous, z-score for normally distributed columns - Isolation Forest or DBSCAN for multivariate outliers - Always distinguish data-entry errors (drop) from legitimate extreme values (keep, but consider robust models or transformation) **Class imbalance:** - Below 10% positive class, flag accuracy as misleading; recommend ROC-AUC, PR-AUC, F1 - Below 1%, recommend resampling techniques (SMOTE, undersampling) or anomaly-detection framing - Stratified splits are mandatory for imbalanced data **Correlation and leakage:** …
Read the whole file at its exact version.
How to install
mdr add alexclowe/awesome-copilot-cowork-plugins/dataset-profiling@sha256:29668962e6c379b9The line at the top of this page pins the label git:20260512.09751ec, 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_6ibfrricuezkcw6p)
4 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 1 version of this file, committed on May 12, 2026.
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 (2749 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
alexclowe/awesome-copilot-cowork-plugins · 21 stars · license MIT · pushed 2026-10-12 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_6ibfrricuezkcw6p GET https://markdownregistry.com/api/v1/resolve?ref=alexclowe/awesome-copilot-cowork-plugins/dataset-profiling GET https://markdownregistry.com/api/v1/blob/29668962e6c379b9892781e2a424e08c1c2ab627c3bf4eee283f7549177e42a3
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.