ethical-risk-assessment SKILL.md skillA

ethical-risk-assessment from hollandkevint/data-product-operator is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add hollandkevint/data-product-operator/ethical-risk-assessment@v0.1.0

Pins 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/ethical-risk-assessment/SKILL.md
Versions recorded
2
Latest version
v0.1.0, committed Nov 3, 2026
First version recorded
Feb 19, 2026
Size
4,480 bytes
Repository stars
5
License
MIT

Ethical data risk evaluation, bias testing protocols, and governance practices for data products. Use when evaluating ML/AI features for fairness, designing bias testing protocols, planning phased rollouts for high-risk changes, reviewing data governance practices, or when someone asks "could this model be biased?" or "how do we ship AI features responsibly?" For HIPAA-specific guidance, see healthcare-data-domain.

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

## The Fifth Risk

Standard product risk frameworks cover four risks: value, usability, feasibility, and business viability (see `data-product-thinking`). Data products add a fifth: **ethical data risk**.

Ethical data risk asks: Can we build this without bias, privacy violations, or unintended harm?

This risk is owned by the Data Lead, who has veto authority. A technically correct model that produces biased outcomes is worse than no model. This is not optional and not delegated to a compliance review.

## Ethics Canvas

Before committing to any ML/AI feature, complete this structured evaluation:

1. **Training data**: What are the sources? What biases exist in the collection method? Which populations are overrepresented or underrepresented?
2. **Features used**: Which input variables could proxy for protected classes? (ZIP code proxies for race; insurance type proxies for income)
3. **Accuracy by group**: Does model performance vary across demographic groups? Test across race, gender, age, and geography at minimum.
4. **Known limitations**: What does the model NOT do well? Document before shipping, not after complaints.
…

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add hollandkevint/data-product-operator/ethical-risk-assessment@sha256:d4802ca6ddbaf963

The 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.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_icom4civ2kpgnsma.svg)](https://markdownregistry.com/a/art_icom4civ2kpgnsma)

4 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.

versioncommittedcommitsizeaudit
v0.1.0 latest2026-11-03 2939ae2 4,480 BA view · diff
v0.1.02026-02-19 7457173 4,490 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (4480 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

GitHub

hollandkevint/data-product-operator · 5 stars · license MIT · pushed 2026-11-03 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_icom4civ2kpgnsma
GET https://markdownregistry.com/api/v1/resolve?ref=hollandkevint/data-product-operator/ethical-risk-assessment
GET https://markdownregistry.com/api/v1/blob/d4802ca6ddbaf963a115844fc6717a1839af83701996dbaeb041add885127906

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.

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