Skills for Real Engineers. Straight from my .agents directory.
ai-ethics-review
Agent skill frommohitagw15856/pm-claude-skills
Conduct a structured ethical review of an AI or ML feature, model, or product. Use when preparing to deploy an AI system, assessing algorithmic risk, auditing a model for bias, or producing a responsible AI impact assessment. Produces a structured ethics review covering fairness, transparency, privacy, safety, accountability, and societal impact with a risk tier score, pre-deployment checklist, and prioritised mitigations.
How to install ai-ethics-review
npx skills add mohitagw15856/pm-claude-skills# or add only this skill to Claude Code: copy the folder
skills/ai-ethics-review/
# into
~/.claude/skills/ai-ethics-review/ (all projects)
.claude/skills/ai-ethics-review/ (one project)
1# AI Ethics Review Skill23This skill produces a structured ethical review of an AI or machine learning feature, model, or product. Output covers fairness, transparency, privacy, safety, accountability, and societal impact — with risk scoring, prioritised mitigations, and a checklist suitable for governance review or responsible AI documentation.45> ⚠️ This skill provides a structured framework for identifying and documenting ethical risks. It is not a substitute for legal advice, regulated algorithmic impact assessments, or specialist ethics review required in specific jurisdictions (e.g. EU AI Act, UK AI regulation).67## Required Inputs89Work from what is given. If any of these is missing, still produce the complete output: fill each gap with a reasonable assumption marked *(assumed, confirm)* and list those assumptions at the end. Ask a question first only when the core subject itself is missing (there is nothing to write about).10- **Feature or model name** and what it does11- **Who it affects** — which users or people does the AI interact with, make decisions about, or collect data from?12- **What decisions or outputs it produces** — recommendations, predictions, classifications, generation, automation?13- **Consequentiality** — how significant are the AI's decisions? (low-stakes suggestions vs decisions that affect employment, credit, health, safety, etc.)14- **Data used** — what training data, user data, or third-party data is used?15…
Excerpt shown under the repository's MIT license.
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