phuryn/pm-skills is a marketplace of reusable skills, commands, and plugins that guide AI assistants through product-management work such as discovery, strategy, planning, metrics, launches, and growth. It is for product managers and teams using Claude Code, Cowork, or compatible assistants. The catalogue entries are the project's own workflows and extensions.
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 phuryn/pm-skills --skill privacy-policygit clone --depth 1 https://github.com/phuryn/pm-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/phuryn/pm-skills/privacy-policy)<a href="https://agentmods.dev/skills/phuryn/pm-skills/privacy-policy"><img src="https://agentmods.dev/badge/skills/phuryn/pm-skills/privacy-policy/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/phuryn/pm-skills/privacy-policy"><img src="https://agentmods.dev/badge/skills/phuryn/pm-skills/privacy-policy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
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 | $0.00042 | $0.02307 |
| Opus 5.5 | $0.00017 | $0.00923 |
| Sonnet 5.5 | $0.00008 | $0.00461 |
| Haiku 4.5 | $0.00004 | $0.00231 |
Grade A, and why
privacy-policy 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 1mo 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.
Copies of this mod
3 near-identical copies found in the catalogue:
- privacy-policy — 100% identical, 0 lines differ
- privacy-policy — 100% identical, 0 lines differ
- privacy-policy — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 239 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Privacy Policy Generator
You are an experienced data privacy and compliance specialist. Your role is to help draft comprehensive, clear, and compliant privacy policies for digital products and services.
Purpose
Draft a detailed privacy policy for a product or service. The policy covers data types handled, applicable jurisdiction, and clearly marks clauses that require legal review. Provide plain-language explanations to ensure accessibility and transparency.
Important Disclaimer
This is for informational purposes only and does not constitute legal advice. Always have a qualified attorney specializing in data privacy law review the final policy before publication. Privacy policies are legally binding documents that establish your company's responsibilities and users' rights; professional legal review is essential.
Input Arguments
$PRODUCT_NAME: Name of the product or service$PRODUCT_URL: URL or description of the product (optional; will be researched if provided)$COMPANY_NAME: Legal name of your company$COMPANY_ADDRESS: Company headquarters or registered address$CONTACT_EMAIL: Email for privacy inquiries (e.g., [email protected])$INFORMATION_TYPES: Types of data collected (e.g., "names, emails, usage behavior, location data, payment information, device identifiers")$JURISDICTION: Applicable jurisdiction (e.g., "United States," "European Union (GDPR)," "California (CCPA)")
Process
Step 1: Research (if URL provided)
If $PRODUCT_URL is provided:
- Visit the product website
- Identify what data is collected (forms, tracking, login, payments)
- Note any third-party integrations (analytics, payment processors, SDKs)
- Understand the product's primary features and use cases
Step 2: Clarify Data Collection
Map out all data your product collects:
- Direct collection: What users enter (name, email, preferences)
- Automatic collection: What is tracked (IP address, usage behavior, device info, cookies)
- Third-party data: What comes from partners, integrations, or service providers
- Special categories: Does the product handle health data, financial data, children's data, biometric data?
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.
- 1mo ago First seen · 239 lines · 42 tokens per session scan A 4388e746dbde
privacy-policy is a skill published in the GitHub repository phuryn/pm-skills (27,091 stars, last pushed yesterday), licensed MIT. It adds 42 tokens to every session and 2,307 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-15.
Other skills, from other repositories
privacy-policy
Draft a jurisdiction-aware privacy policy for any digital product — use this skill whenever a PMM or Product Manager needs to create, update, audit, or review data protection documentation, asks about GDPR, CCPA, or UK GDPR obligations, mentions "privacy policy", "cookie policy", "data retention", "right to be…
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writing-assistant
Rewrites, sharpens and drafts B2B writing in the writer's real voice: Slack messages, emails, memos, PRDs, decks, plus marketing content (blog posts, landing pages, press releases, case studies, newsletters, social posts). Use whenever someone wants to rewrite, tighten, draft or audit copy, asks why copy isn't landing…