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Privacy And Data Protection

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cbrock84
privacy-and-data-protection

Assesses and improves how personal data is collected, used, shared, and retained — data mapping, lawful basis, consent, processor agreements, subject rights, and breach obligations. Use this before launching anything that handles personal data, when adding a vendor that will process it, when a data subject request arrives, when assessing exposure under GDPR or US state privacy laws, or when preparing for a privacy review.

Overview

Publishercbrock84
Repositoryheadcount
Skill nameprivacy-and-data-protection
Stars
2K
Forks
316
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by cbrock84 on GitHub. Read the source before you install it.

Installation

Install the Privacy And Data Protection AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/cbrock84/headcount/tree/main/plugins/legal-risk/skills/privacy-and-data-protection
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/cbrock84/headcount.git /tmp/headcount
mkdir -p .claude/skills
cp -r /tmp/headcount/plugins/legal-risk/skills/privacy-and-data-protection .claude/skills/privacy-and-data-protection
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Privacy And Data Protection in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Privacy And Data Protection on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Privacy And Data Protection is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Privacy and data protection

Not legal advice. Regimes differ by jurisdiction and change; material questions need qualified counsel. This structures the assessment and identifies what to escalate.

Start from the data map

You cannot assess what you have not inventoried. For each category of personal data:

  • What is collected, from whom, and where it came from.
  • Why — the specific purpose, and the lawful basis where one is required.
  • Where it lives, who can reach it, and which vendors receive it.
  • How long it is kept, and what deletes it. "Indefinitely" is a finding, not an answer.
  • Whether it crosses a border, and under what mechanism.

Most privacy failures are inventory failures: data nobody remembered was being collected, in a system nobody owned.

Design decisions that prevent problems

  • Collect less. Every field is a liability with a maintenance cost. The cheapest way to protect data is not to hold it.
  • Purpose limitation is real. Data collected for one purpose is not automatically available for another — particularly for training models, which is where this most often goes wrong now.
  • Separate identifiers from behavior where analysis does not require linkage.
  • Retention with an enforcing mechanism. A policy with no deletion job is a statement of intent.

Consent, where it applies

Specific, informed, freely given, and as easy to withdraw as to give. Pre-ticked boxes, bundled consent, and cookie walls that offer no genuine choice fail on their face in the regimes that require consent.

Note that consent is one lawful basis among several and often the weakest — it can be withdrawn, and then the processing must stop.

Vendors

Any third party processing personal data on your behalf needs a written agreement covering purpose, security, sub-processors, deletion, and assistance with subject rights. Sending data to a vendor without one is a common and easily avoided violation.

Assess the vendor's actual security, not their questionnaire answers, in proportion to the sensitivity of what they will hold.

Subject rights and breaches

Have a working process before the first request: how it arrives, how identity is verified, how the data is located across systems, and the deadline. Locating the data is the part that fails.

For breaches, know your notification clock before you need it — several regimes measure it in hours from awareness. Decide in advance who determines that awareness has occurred.

Sources

references/sources.md in this skill lists the outside authorities that settle the questions here — what each one is authoritative for, and what you may do with it. Check them before answering on anything they cover, and cite what you used. Most are free to read and not free to reproduce; the use note on each is binding.

Never

  • Collect data because it may be useful later. Purpose first, then collection.
  • Retain personal data past the period you published.
  • Send personal data to a vendor before the contract terms and the transfer basis are in place.
  • Load production personal data into a test environment.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Privacy And Data Protection AI skill do?

Assesses and improves how personal data is collected, used, shared, and retained — data mapping, lawful basis, consent, processor agreements, subject rights, and breach obligations. Use this before launching anything that handles personal data, when adding a vendor that will process it, when a data subject request arrives, when assessing exposure under GDPR or US state privacy laws, or when preparing for a privacy review.

Why use Privacy And Data Protection on TypingMind?

Because you install it once and use it with any model. Privacy And Data Protection is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Privacy And Data Protection in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/cbrock84/headcount/tree/main/plugins/legal-risk/skills/privacy-and-data-protection. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Privacy And Data Protection?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Privacy And Data Protection?

As many as you like. As long as a model supports skills, you can use Privacy And Data Protection with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Privacy And Data Protection AI skill free?

Yes. It is published on GitHub by cbrock84 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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