Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-automated-decisionsgit clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mukul975/privacy-data-protection-skills/ai-automated-decisions)<a href="https://agentmods.dev/skills/mukul975/privacy-data-protection-skills/ai-automated-decisions"><img src="https://agentmods.dev/badge/skills/mukul975/privacy-data-protection-skills/ai-automated-decisions/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mukul975/privacy-data-protection-skills/ai-automated-decisions"><img src="https://agentmods.dev/badge/skills/mukul975/privacy-data-protection-skills/ai-automated-decisions.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00073 | $0.02857 |
| Opus 5 | $0.00036 | $0.01429 |
| Sonnet 5 | $0.00015 | $0.00571 |
| Haiku 4.5 | $0.00007 | $0.00286 |
Grade A, and why
ai-automated-decisions scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 13d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Automated Decision-Making and Human Oversight
Overview
GDPR Article 22 grants data subjects the right not to be subject to decisions based solely on automated processing, including profiling, which produce legal or similarly significant effects. The EU AI Act Art. 14 supplements this with specific human oversight design requirements for high-risk AI systems. Together, these provisions require organisations to identify when AI systems make consequential decisions, ensure meaningful human intervention where required, provide explainable decision logic, and offer effective contestation mechanisms. This skill provides the complete framework for Art. 22 compliance and AI Act human oversight implementation.
Art. 22 Scope and Applicability
Three Cumulative Conditions
Art. 22(1) is triggered only when all three conditions are met:
| Condition | Requirement | AI Application |
|---|---|---|
| 1. Decision | A decision is made (not merely a recommendation or input) | The AI output directly determines an outcome — no genuine human decision-making step between AI output and action |
| 2. Solely automated | Based solely on automated processing including profiling | No meaningful human intervention in the decision chain; rubber-stamping does not constitute human intervention |
| 3. Legal/significant effects | Produces legal effects or similarly significantly affects the data subject | Affects legal rights, contractual status, access to services, financial outcomes, or other significant life impacts |
"Solely Automated" — EDPB Interpretation
The EDPB Guidelines 06/2020 on automated decision-making clarify:
- Solely automated means no meaningful human involvement in the decision process
- A human who merely confirms an AI recommendation without genuine assessment is not providing meaningful intervention
- Meaningful human intervention requires:
- The reviewer has authority and competence to change the decision
- The reviewer has access to all relevant information
- Sufficient time is allocated for genuine consideration
- The reviewer routinely exercises independent judgment (not just confirming AI output)
- Override capability is actually used in practice
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 13d ago First seen · 230 lines · 73 tokens per session scan A bd76eb1529e0
ai-automated-decisions is a skill published in the GitHub repository mukul975/Privacy-Data-Protection-Skills (272 stars, last pushed 6mo ago), licensed Apache-2.0. It adds 73 tokens to every session and 2,857 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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