privacy-and-data-protection

privacy-and-data-protection is a skill for Claude Code from cbrock84/headcount. It costs 86 tokens per session (657 once invoked), scanned A, original, MIT.

A guide to handling personal information: what is collected, why it is used, where it goes, how long it is kept, and what rights people have. Personal data means information that can identify or relate to a person.

In plain words
What is it for?
Use it to map data, assess consent and other legal bases, review processors, handle data requests, and plan for breaches.
Why use it?
It helps find forgotten data, unclear purposes, risky vendors, excessive collection, and retention problems before they become privacy issues.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the legal-risk plugin — 8 skills shipped together

Good fit Use it to map data, assess consent and other legal bases, review processors, handle data requests, and plan for breaches.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/cbrock84/headcount/privacy-and-data-protection
About the project

headcount is an organization of independently installable Claude Code plugins, each grouping skills for a department such as finance, security, or demand generation. Claude Code users install the departments they need and invoke their skills for specialized work; the catalogue entries are skills and related agent tooling from that organization.

cbrock84/headcount · 1,320 stars · on GitHub · cbrock84.github.io

Install

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.

Any agent
npx skills add cbrock84/headcount --skill privacy-and-data-protection
Clone the repo
git clone --depth 1 https://github.com/cbrock84/headcount

Made for: Claude Code.

Or install legal-risk, the plugin that ships this one along with the rest of its 8 skills.

Wrote 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.

agentmods badge for privacy-and-data-protection

README.md
[![agentmods](https://agentmods.dev/badge/skills/cbrock84/headcount/privacy-and-data-protection/github.svg)](https://agentmods.dev/skills/cbrock84/headcount/privacy-and-data-protection)
Your own site
<a href="https://agentmods.dev/skills/cbrock84/headcount/privacy-and-data-protection"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/privacy-and-data-protection/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.

agentmods 80×15 button for privacy-and-data-protection

Your own site · 80×15
<a href="https://agentmods.dev/skills/cbrock84/headcount/privacy-and-data-protection"><img src="https://agentmods.dev/badge/skills/cbrock84/headcount/privacy-and-data-protection.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 657 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00086 $0.00657
Opus 5 $0.00043 $0.00329
Sonnet 5 $0.00017 $0.00131
Haiku 4.5 $0.00009 $0.00066

Measured 5d ago against content hash f66b59ed7c2a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

privacy-and-data-protection 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 5d 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.

plugins/legal-risk/skills/privacy-and-data-protection/SKILL.md · 65 lines

How it starts

The opening of the file, as written. The whole thing — 65 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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.

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.

Read the full file on GitHub · 65 lines

Changes

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.

  1. 5d ago First seen · 65 lines · 86 tokens per session scan A f66b59ed7c2a

Subscribe to this mod's changes

privacy-and-data-protection is a skill published in the GitHub repository cbrock84/headcount (1,320 stars, last pushed 6d ago), licensed MIT. It adds 86 tokens to every session and 657 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 2026-09-03.

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