privacy-policy-drafting

privacy-policy-drafting is a skill for Claude Code, Codex from seb1n/awesome-ai-agent-skills. It costs 58 tokens per session (1,769 once invoked), scanned A, original, MIT.

A workflow for drafting a business’s privacy policy and a review checklist based on its data practices and jurisdictions. It is a working draft, not proof of legal compliance.

In plain words
What is it for?
Use it to document collected data, cookies, analytics, storage, retention, sharing, user rights, and possible GDPR or CCPA requirements.
Why use it?
It helps reveal which personal-data disclosures are needed and which business details or legal questions are still unresolved.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to document collected data, cookies, analytics, storage, retention, sharing, user rights, and possible GDPR or CCPA requirements.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/seb1n/awesome-ai-agent-skills/privacy-policy-drafting
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 seb1n/awesome-ai-agent-skills --skill privacy-policy-drafting
Clone the repo
git clone --depth 1 https://github.com/seb1n/awesome-ai-agent-skills

Made for: Claude Code, Codex.

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-policy-drafting

README.md
[![agentmods](https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/privacy-policy-drafting/github.svg)](https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/privacy-policy-drafting)
Your own site
<a href="https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/privacy-policy-drafting"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/privacy-policy-drafting/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-policy-drafting

Your own site · 80×15
<a href="https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/privacy-policy-drafting"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/privacy-policy-drafting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 58 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,769 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 $0.00058 $0.01769
Opus 5 $0.00029 $0.00885
Sonnet 5 $0.00012 $0.00354
Haiku 4.5 $0.00006 $0.00177

Measured 9d ago against content hash ef1a2a121a43, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

privacy-policy-drafting 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 9d 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.

legal-and-compliance/privacy-policy-drafting/SKILL.md · 106 lines

How it starts

The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Privacy Policy Drafting

Draft legally informed privacy-policy language that addresses potentially applicable privacy frameworks and exposes unresolved business inputs. Treat the result as a working draft and review checklist, not proof of compliance. Verify current law, regulator guidance, product behavior, and jurisdiction with qualified counsel before publication.

Workflow

  1. Gather Business Information — Collect details about the business entity (name, jurisdiction, contact info), the product or service offered, target user demographics, and geographic reach. Determine which regulations apply based on where users are located, not just where the business is incorporated. A US-based SaaS serving EU customers must address GDPR.

  2. Identify Data Collection Practices — Map every category of personal data collected: direct inputs (forms, account creation), automatic collection (cookies, analytics, device info, IP addresses), third-party sources (OAuth providers, data brokers), and derived data (usage patterns, preferences). For each category, document the collection method, storage location, retention period, and whether it includes sensitive/special category data.

  3. Map Legal Requirements — Cross-reference collected data types against applicable frameworks. GDPR requires lawful basis for each processing activity, CCPA requires disclosure of sale/sharing practices and opt-out mechanisms, COPPA applies if users under 13 may access the service, and sector-specific rules (HIPAA, FERPA, GLBA) may layer additional requirements. Identify all required policy sections.

  4. Draft Policy Sections — Generate each section with plain-language explanations alongside legally precise disclosures. Required sections include: data collected and purposes, legal basis for processing (GDPR), data sharing and third parties, cookies and tracking technologies, data retention, user rights and how to exercise them, international data transfers, children's privacy, security measures, and policy change notification procedures.

Read the full file on GitHub · 106 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. 9d ago First seen · 106 lines · 58 tokens per session scan A ef1a2a121a43

Subscribe to this mod's changes

privacy-policy-drafting is a skill published in the GitHub repository seb1n/awesome-ai-agent-skills (179 stars, last pushed 1mo ago), licensed MIT. It adds 58 tokens to every session and 1,769 once invoked, about $0.0003 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.