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.
git 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/commands/phuryn/pm-skills/privacy-policy)<a href="https://agentmods.dev/commands/phuryn/pm-skills/privacy-policy"><img src="https://agentmods.dev/badge/commands/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/commands/phuryn/pm-skills/privacy-policy"><img src="https://agentmods.dev/badge/commands/phuryn/pm-skills/privacy-policy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00015 | $0.00467 |
| Opus 5.5 | $0.00006 | $0.00187 |
| Sonnet 5.5 | $0.00003 | $0.00093 |
| Haiku 4.5 | $0.00002 | $0.00047 |
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.
How it starts
The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/privacy-policy -- Privacy Policy Generator
Draft a comprehensive privacy policy for your product. Covers data types, jurisdiction, compliance (GDPR, CCPA), and marks clauses needing legal review.
Invocation
/privacy-policy SaaS analytics tool that collects user behavior data — serving US and EU customers
/privacy-policy Mobile app with location data and third-party integrations
Workflow
Step 1: Gather Context
Ask:
- What product or service?
- What data is collected? (personal info, usage data, cookies, location, payment)
- Where are your users? (determines applicable regulations: GDPR, CCPA, etc.)
- Any third-party data sharing? (analytics, advertising, integrations)
- Data storage: where and how long?
- Age restrictions? (COPPA considerations)
Step 2: Draft the Policy
Apply the privacy-policy skill:
Generate sections covering:
- What data is collected and how
- How data is used (purposes)
- Legal basis for processing (GDPR)
- Data sharing and third parties
- Data retention and deletion
- User rights (access, deletion, portability, opt-out)
- Cookie policy
- Security measures
- Children's privacy (if applicable)
- International transfers
- Contact information
- Policy update process
Step 3: Deliver
## Privacy Policy: [Product]
[Full policy text]
### Compliance Checklist
| Regulation | Status | Notes |
|-----------|--------|-------|
### Clauses Requiring Legal Review
| Clause | Why | Priority |
|--------|-----|----------|
### Implementation Checklist
- [ ] Cookie consent banner
- [ ] Data subject request process
- [ ] Data processing records
- [ ] DPA with processors
Save as markdown. Offer DOCX export.
Notes
- This is a template — legal counsel should review before publishing
- GDPR and CCPA have specific requirements that can't be approximated — flag where expert review is essential
- Privacy policies should be in plain language, not legalese
- Update the policy when data practices change, not just annually
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 · 77 lines · 15 tokens per session scan A cbf350ef69f0
privacy-policy is a command published in the GitHub repository phuryn/pm-skills (27,091 stars, last pushed yesterday), licensed MIT. It adds 15 tokens to every session and 467 once invoked, about $0.0001 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 commands, from other repositories
privacy
Draft a jurisdiction-aware privacy policy for a digital product.
customer-stories
Kick off, interview for, draft, send for customer review or audit a B2B customer story in one fixed structure, with stats and named quotes checked.
experiment-ideas
Generate several concrete, brain-grounded growth ideas — channel, message, rationale, cost-efficiency — ranked by effort vs. impact.
value-prop-statements
Fan an existing positioning statement out into segment- and channel-specific value-prop copy variants, trace-checked against drift.
pmm-metrics
Define a North Star Metric and capped scorecard, or audit an existing metrics list for sprawl and vanity metrics.
alternatives-map
Build or deepen your competitive alternatives map — direct competitors, adjacent tools, DIY, and status quo — from real win/loss data.