clean-data SKILL.md skillA
clean-data from aperivue/medsci-skills is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add aperivue/medsci-skills/clean-data@git:20260930.c8ed96cPins git:20260930.c8ed96c in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- aperivue/medsci-skills
- Path
skills/clean-data/SKILL.md- Versions recorded
- 8
- Latest version
- git:20260930.c8ed96c, committed Sep 30, 2026
- First version recorded
- Apr 18, 2026
- Size
- 8,063 bytes
- Repository stars
- 346
- License
- MIT
Use when a clinical CSV/Excel dataset needs profiling and cleaning before analysis (missing values, outliers, duplicates, type mismatches). Profiles, flags and generates cleaning code in three stages, each gated on the researcher's approval. Never auto-cleans.
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
# Data Profiling and Cleaning Skill
Profile, flag, and generate cleaning code for a clinical dataset in three stages, each ending at a
user-approval gate. You generate code and reports; you do NOT auto-clean data. Every cleaning decision
needs the researcher's explicit confirmation, because clinical cleaning calls need domain knowledge.
**PHI first.** If the dataset contains PHI or PII, run `/deidentify` before proceeding, and use
`*_deidentified.*` files when they exist in the working directory. Otherwise work from the data
dictionary / codebook alone, or in a local-only environment with no network access. The skill writes
code that runs on the data; it does not need to see the raw rows to write it.
## Three-Stage Workflow
### Stage 1: Profiling
**Input**: CSV/Excel file path OR data dictionary/codebook
1. Adapt `${CLAUDE_SKILL_DIR}/references/profiling_template.py` (pandas) to the dataset. It reports:
variable and row counts, data types; missing count and percentage per variable; unique counts for
categorical variables; min/max/mean/median/SD for numeric variables; histograms and bar charts.
…Read the whole file at its exact version.
How to install
mdr add aperivue/medsci-skills/clean-data@sha256:6acb2b638a089e4fThe line at the top of this page pins the label git:20260930.c8ed96c, 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_p67pvsjstpjkg7wb)
5 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 8 versions of this file, between Apr 18, 2026 and Sep 30, 2026, about one every 24 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| git:20260930.c8ed96c latest | 2026-09-30 | c8ed96c | 8,063 B | A | view · diff |
| git:20260930.30387c2 | 2026-09-30 | 30387c2 | 8,078 B | A | view · diff |
| git:20260930.913abeb | 2026-09-30 | 913abeb | 8,174 B | A | view · diff |
| git:20260815.a0dd7c1 | 2026-08-15 | a0dd7c1 | 11,403 B | A | view · diff |
| git:20260628.dab2331 | 2026-06-28 | dab2331 | 11,378 B | A | view · diff |
| git:20260620.899635d | 2026-06-20 | 899635d | 10,116 B | A | view · diff |
| git:20260606.f5f5f19 | 2026-06-06 | f5f5f19 | 9,025 B | A | view · diff |
| git:20260418.11caf95 | 2026-04-18 | 11caf95 | 8,065 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 (8063 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
aperivue/medsci-skills · 346 stars · license MIT · pushed 2026-10-19 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_p67pvsjstpjkg7wb GET https://markdownregistry.com/api/v1/resolve?ref=aperivue/medsci-skills/clean-data GET https://markdownregistry.com/api/v1/blob/6acb2b638a089e4f703dfd2b3dfb38028e894471f99d7ed2a435a3446e1d79b0
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.