Pre-deployment privacy compliance checklist for AI/ML systems covering DPIA completion, lawful basis verification, transparency notices, human oversight mechanisms, bias testing, and post-deployment…
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-deployment-checklist -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills ai-deployment-checklist --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/privacy/ai-deployment-checklist .claude/skills/ai-deployment-checklist && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "ai-deployment-checklist" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/ai-deployment-checklist into .claude/skills/ai-deployment-checklist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-deployment-checklist", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/ai-deployment-checklistType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-deployment-checklist -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills ai-deployment-checklist --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/privacy/ai-deployment-checklist .agents/skills/ai-deployment-checklist && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ai-deployment-checklist" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/ai-deployment-checklist into .agents/skills/ai-deployment-checklist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-deployment-checklist", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-deployment-checklist -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills ai-deployment-checklist --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/privacy/ai-deployment-checklist .cursor/skills/ai-deployment-checklist && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ai-deployment-checklist" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/ai-deployment-checklist into .cursor/skills/ai-deployment-checklist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-deployment-checklist", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/mukul975/Privacy-Data-Protection-Skills.git --path skills/privacy/ai-deployment-checklist--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-deployment-checklist -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills ai-deployment-checklist --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/privacy/ai-deployment-checklist .gemini/skills/ai-deployment-checklist && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ai-deployment-checklist" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/ai-deployment-checklist into .gemini/skills/ai-deployment-checklist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-deployment-checklist", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install mukul975/Privacy-Data-Protection-Skills ai-deployment-checklistInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-deployment-checklist -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/privacy/ai-deployment-checklist .github/skills/ai-deployment-checklist && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ai-deployment-checklist" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/ai-deployment-checklist into .github/skills/ai-deployment-checklist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-deployment-checklist", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-deployment-checklist -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mukul975/Privacy-Data-Protection-Skills ai-deployment-checklist --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mukul975/Privacy-Data-Protection-Skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/privacy/ai-deployment-checklist .opencode/skills/ai-deployment-checklist && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ai-deployment-checklist" agent skill from https://github.com/mukul975/Privacy-Data-Protection-Skills/tree/main/skills/privacy/ai-deployment-checklist into .opencode/skills/ai-deployment-checklist/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ai-deployment-checklist", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
ai-deployment-checklistPre-deployment privacy compliance checklist for AI/ML systems covering DPIA completion, lawful basis verification, transparency notices, human oversight mechanisms, bias testing, and post-deployment…
AI Deployment Checklist is an agent skill from mukul975/Privacy-Data-Protection-Skills. Pre-deployment privacy compliance checklist for AI/ML systems covering DPIA completion, lawful basis verification, transparency notices, human oversight mechanisms, bias testing, and post-deployment monitoring setup. Keywords: AI deployment, privacy checklist, go-live, model deployment, compliance gate.
Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 7 other files, including scripts, reference files and assets (for example `assets/template.md`, `references/standards.md` and `references/workflows.md`).
It sits in Legal & Compliance, covering Privacy and GDPR and Deployment. The repository describes itself as: 282+ structured privacy & data protection skills for AI agents. GDPR, CCPA, EU AI Act, HIPAA, LGPD, PIPL, DPDP Act. The licence is Apache-2.0.
Read from SKILL.md and the folder at commit 9b2ef9e. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 1 file in scripts/ (Python), which the agent can run.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
AI Deployment Checklist loads about 2.1k tokens when it runs, and up to ~4.3k if it reads all its reference files. Until then it costs about 82 tokens; SKILL.md has 882 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from mukul975/Privacy-Data-Protection-Skills at commit 9b2ef9e, republished under its Apache-2.0 licence (© mukul975). 882 words, ~2,075 tokens.
.claude/skills/ai-deployment-checklist/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.Deploying an AI system that processes personal data requires verification of privacy compliance across multiple dimensions before the system goes live. This checklist serves as a compliance gate in the Cerebrum AI Labs ML deployment pipeline. No AI system may be deployed to production until all mandatory items are verified and signed off by the Data Protection Officer (DPO). The checklist is structured around GDPR requirements, the EU AI Act obligations (for high-risk systems), and internal governance standards.
| Check | Requirement | Status | Evidence |
|---|---|---|---|
| Lawful basis documented | Art. 6(1) basis identified and recorded for all personal data processing | Required | LIA or consent records |
| Special categories assessed | Art. 9 data identified; explicit consent or Art. 9(2) exception documented | Required | Data classification report |
| DPIA completed | Art. 35 DPIA completed for high-risk processing (profiling, systematic monitoring, large-scale special categories) | Required if applicable | DPIA document signed by DPO |
| DPIA risks mitigated | All high/critical risks from DPIA have documented mitigations | Required | Risk treatment plan |
| Prior consultation | Art. 36 consultation with supervisory authority if residual risk remains high | Required if applicable | Consultation record |
| Legitimate interest assessment | If relying on Art. 6(1)(f), LIA balancing test completed | Required if LI basis | LIA document |
| Check | Requirement | Status | Evidence |
|---|---|---|---|
| Privacy notice updated | Art. 13-14 information includes AI processing details | Required | Updated privacy notice |
| Logic described | "Meaningful information about the logic involved" documented for data subjects | Required for automated decisions | Explanation document |
| Significance disclosed | Envisaged consequences of AI processing disclosed | Required for automated decisions | Privacy notice section |
| Profiling disclosed | If system profiles individuals, this is disclosed in privacy notice | Required if profiling | Privacy notice section |
| AI Act transparency | Art. 52 transparency obligations met (if applicable): inform that they are interacting with AI | Required for AI Act | User interface disclosure |
| Check | Requirement | Status | Evidence |
|---|---|---|---|
| Access process defined | Process for responding to access requests for AI data (inputs, outputs, profiles) | Required | Documented SOP |
| Explanation mechanism | Individual explanations can be generated on request | Required for Art. 22 | Technical capability verified |
| Human intervention available | Art. 22(3) human review process established | Required for solely automated decisions | Process document + trained staff |
| Contestation channel | Data subjects can contest AI decisions and have them reviewed | Required for Art. 22 | Appeal process document |
| Rectification process | Process for correcting AI input data and regenerating outputs | Required | Documented SOP |
| Erasure process | Process for deleting data from training sets, inference logs, embeddings | Required | Documented SOP |
| Check | Requirement | Status | Evidence |
|---|---|---|---|
| Training data documented | Data sources, size, collection method, preprocessing documented | Required | Data card / dataset documentation |
| Bias testing completed | Model tested for bias across protected attributes (gender, race, age, disability) | Required | Bias test report |
| Fairness metrics acceptable | Disparate impact ratio >0.8 (four-fifths rule) or equivalent metric within acceptable range | Required | Fairness metrics report |
| Data quality verified | Training data completeness, accuracy, representativeness verified | Required | Data quality report |
| Art. 9 data removed or justified | Special category data either removed or lawful basis documented | Required | Data classification report |
| Check | Requirement | Status | Evidence |
|---|---|---|---|
| Data encryption at rest | Training data and model weights encrypted (AES-256 or equivalent) | Required | Security configuration |
| Data encryption in transit | All API endpoints use TLS 1.2+ | Required | SSL certificate |
| Access controls | Role-based access to model, training data, and inference logs | Required | IAM policy |
| Audit logging | All model invocations logged with timestamp, input hash, output, user | Required | Logging configuration |
| Adversarial robustness | Model tested against common adversarial attacks relevant to its domain | Recommended | Security test report |
| Model versioning | Model versioned in registry with rollback capability | Required | MLflow / model registry |
| Check | Requirement | Status | Evidence |
|---|---|---|---|
| Performance monitoring | Dashboard tracking accuracy, latency, error rates in production | Required | Monitoring setup |
| Drift detection | Data drift and concept drift detection implemented | Required | Drift monitoring configuration |
| Bias monitoring | Post-deployment bias metrics tracked continuously | Required | Fairness monitoring dashboard |
| Incident response | Process for handling AI-related privacy incidents (e.g., discriminatory output, data leak) | Required | Incident response plan |
| Retraining schedule | Defined schedule for model retraining with fresh data | Required | Retraining plan |
| Retention enforcement | Automated deletion of inference logs and training data per retention schedule | Required | Retention policy + automation |
| Check | Requirement | Status | Evidence |
|---|---|---|---|
| Risk classification | System classified per Annex III | Required | Classification document |
| Technical documentation | Annex IV documentation complete | Required | Tech doc package |
| Risk management system | Art. 9 continuous risk management implemented | Required | Risk register + process |
| Conformity assessment | Internal or third-party conformity assessment completed | Required | Assessment report |
| EU Declaration of Conformity | Art. 47 declaration prepared | Required | Signed declaration |
| EU database registration | Art. 49 registration completed | Required | Registration confirmation |
| Role | Name | Approval | Date |
|---|---|---|---|
| ML Engineering Lead | [ ] Approved / [ ] Blocked | ||
| Data Protection Officer | [ ] Approved / [ ] Blocked | ||
| Information Security Officer | [ ] Approved / [ ] Blocked | ||
| Product Owner | [ ] Approved / [ ] Blocked | ||
| Legal Counsel | [ ] Approved / [ ] Blocked (high-risk only) |
© mukul975, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 4 other files (scripts, references, assets) in skills/privacy/ai-deployment-checklist of mukul975/Privacy-Data-Protection-Skills.
Open the folder on GitHubat commit 9b2ef9e
AI Deployment Checklist next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| AI Deployment Checklist this skillmukul975/Privacy-Data-Protection-Skills | 301 | — | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Msp Website SetupRTFM-IT-Services-LLC/msp-claude-skills | 115 | — | ~3.6k | Automated safety check: Notes | Custom licence | |
| Add Session Recordinggotempsh/temps | 831 | — | ~1.9k | Automated safety check: Pass | Apache-2.0 | |
| Policy OpaAgentSecOps/SecOpsAgentKit | 220 | 1 repos | ~3.5k | Automated safety check: Pass | Custom licence | |
| Data Protection And Encryptioncbrock84/headcount | 2k | — | ~1.3k | Automated safety check: Pass | MIT | |
| AI Ethics Reviewmohitagw15856/pm-claude-skills | 1.4k | — | ~3.4k | Automated safety check: Pass | MIT |
RTFM-IT-Services-LLC/msp-claude-skills
Your MSP's standard process for setting up a new static client website hosted on your static hosting platform with a git-based dev/prod CI/CD pipeline, plus the client-practice rules around it.
gotempsh/temps
Add privacy-aware session recording and replay to React applications using the Temps SDK.
AgentSecOps/SecOpsAgentKit
Policy-as-code enforcement and compliance validation using Open Policy Agent (OPA).
cbrock84/headcount
Protects data itself rather than the systems around it — classifying what you hold, encrypting in transit and at rest and understanding what each actually defends against, managing keys and their…
mohitagw15856/pm-claude-skills
Conduct a structured ethical review of an AI or ML feature, model, or product.
c15t/c15t
Work with c15t consent management docs, APIs, and integrations for Next.js, React, and JavaScript.
mukul975/Privacy-Data-Protection-Skills
Implements age-gating mechanisms for online services to restrict access based on user age.
mukul975/Privacy-Data-Protection-Skills
Manages AI model retention and machine unlearning requirements.
mukul975/Privacy-Data-Protection-Skills
Conducts Data Protection Impact Assessments for AI and ML systems per EDPB Guidelines 04/2025 on AI processing.
mukul975/Privacy-Data-Protection-Skills
Structures risk mitigation planning and residual risk tracking for Data Protection Impact Assessments under GDPR Article 35(7)(d).
mukul975/Privacy-Data-Protection-Skills
Guides implementation of the GDPR accountability principle under Articles 5(2) and 24, including documentation requirements for policies, DPIAs, RoPA, training records, and breach logs.
mukul975/Privacy-Data-Protection-Skills
Conducts pre-DPIA threshold screening to determine whether a full Data Protection Impact Assessment is required under GDPR Article 35.
Categories
Pre-deployment privacy compliance checklist for AI/ML systems covering DPIA completion, lawful basis verification, transparency notices, human oversight mechanisms, bias testing, and post-deployment…. AI Deployment Checklist is an agent skill from mukul975/Privacy-Data-Protection-Skills. Pre-deployment privacy compliance checklist for AI/ML systems covering DPIA completion, lawful basis verification, transparency notices, human oversight mechanisms, bias testing, and post-deployment monitoring setup.
AI Deployment Checklist fits situations like: tasks that involve Privacy and GDPR; tasks that involve Deployment.
Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-deployment-checklist -a claude-code`. Or copy the skill folder (skills/privacy/ai-deployment-checklist in mukul975/Privacy-Data-Protection-Skills) into .claude/skills/ai-deployment-checklist in your project. Claude Code loads it when a task matches its description.
Run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-deployment-checklist -a codex`. Or copy the skill folder (skills/privacy/ai-deployment-checklist in mukul975/Privacy-Data-Protection-Skills) into .agents/skills/ai-deployment-checklist in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add mukul975/Privacy-Data-Protection-Skills --skill ai-deployment-checklist -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ai-deployment-checklist, .gemini/skills/ai-deployment-checklist, .github/skills/ai-deployment-checklist and .opencode/skills/ai-deployment-checklist in your project.
Going by SKILL.md and its folder, AI Deployment Checklist needs Python for the scripts in its folder. Our summary lists: Python 3.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
AI Deployment Checklist is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.1k tokens (SKILL.md is roughly 8.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 2.2k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with AI Deployment Checklist: Msp Website Setup (RTFM-IT-Services-LLC/msp-claude-skills, 115 stars), Add Session Recording (gotempsh/temps, 831 stars), Policy Opa (AgentSecOps/SecOpsAgentKit, 220 stars) and Data Protection And Encryption (cbrock84/headcount, 2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
mukul975 (a GitHub user) maintains it in mukul975/Privacy-Data-Protection-Skills, which has 301 GitHub stars. The repository holds 280 skills in this directory. The repository was last updated on March 16, 2026.
Source: mukul975/Privacy-Data-Protection-Skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.
