data-quality-assessment SKILL.md skillA
data-quality-assessment from hollandkevint/data-product-operator is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add hollandkevint/data-product-operator/data-quality-assessment@v0.1.0Pins v0.1.0 in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- hollandkevint/data-product-operator
- Path
skills/data-quality-assessment/SKILL.md- Versions recorded
- 2
- Latest version
- v0.1.0, committed Nov 3, 2026
- First version recorded
- Feb 19, 2026
- Size
- 3,401 bytes
- Repository stars
- 5
- License
- MIT
Systematic data quality evaluation covering completeness, accuracy, timeliness, consistency, and validity. Use when assessing data pipelines, reviewing data product quality, auditing data sources, defining quality SLAs, building data quality monitors, or when someone asks "is this data trustworthy?" or "how do we measure data quality?".
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
## Five Quality Dimensions Score each dimension 1-5 when evaluating any data source or pipeline: **1. Completeness** - What percentage of expected records and fields are present? - Null rate per column - Missing record detection (expected vs actual row counts) - Required field coverage - Score 5: <1% nulls in required fields. Score 1: >20% missing data. **2. Accuracy** - Does the data reflect reality? - Cross-field validation (age matches birth date, totals match line items) - Reference data matching (codes exist in terminology tables) - Statistical outlier detection - Score 5: <0.1% error rate verified against gold standard. Score 1: Known systematic errors unresolved. **3. Timeliness** - Is the data fresh enough for its intended use? - Data freshness (time since last update vs SLA) - Pipeline latency (ingestion to availability) - Score 5: Real-time or within SLA. Score 1: Data is days/weeks stale. **4. Consistency** - Does the same fact look the same everywhere? - Format standardization (dates, codes, identifiers) - Cross-system agreement (same patient, same record across sources) - Naming convention compliance …
Read the whole file at its exact version.
How to install
mdr add hollandkevint/data-product-operator/data-quality-assessment@sha256:86aa9a967aa23874The line at the top of this page pins the label v0.1.0, 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_a2fbklpfgnrlur3s)
6 badge image fetches in 30 days. What the badge shows.
Versions
The registry has recorded 2 versions of this file, between Feb 19, 2026 and Nov 3, 2026, about one every 256 days.
| version | committed | commit | size | audit | |
|---|---|---|---|---|---|
| v0.1.0 latest | 2026-11-03 | 2939ae2 | 3,401 B | A | view · diff |
| v0.1.0 | 2026-02-19 | 7457173 | 3,411 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 (3401 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
hollandkevint/data-product-operator · 5 stars · license MIT · pushed 2026-11-03 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_a2fbklpfgnrlur3s GET https://markdownregistry.com/api/v1/resolve?ref=hollandkevint/data-product-operator/data-quality-assessment GET https://markdownregistry.com/api/v1/blob/86aa9a967aa238747e089f0a29ee033fad9dbf3ecd8d737aed78fb96a13b28d2
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.