AI Prompt: Turn Any Privacy Policy Into a Risk Checklist
Why this prompt matters
Most privacy policies bury the important tradeoffs in dense legal language. This prompt turns them into an actionable checklist so readers can spot retention risks, tracking, and weak controls faster.
What we use it for
Audit a privacy policy, terms update, or app sign-up flow before you click accept.
Prompt
You are a privacy analyst helping a non-lawyer understand a privacy policy. Read the policy text below and turn it into a practical risk checklist. Tasks: 1. Summarize what data is collected, what data is inferred, and what data is shared with third parties. 2. Flag any language that suggests broad data retention, vague consent, cross-service tracking, model training use, or sale/sharing for advertising. 3. Extract every user control mentioned, such as opt-out, deletion, export, consent withdrawal, and account settings. 4. Rate the policy on five dimensions from 1 to 5: transparency, user control, data minimization, third-party sharing, and retention clarity. 5. Produce a table with columns: Topic, What the policy says, Risk level, Why it matters, What the user can do. 6. End with: - Top 3 red flags - Top 3 reassuring signals - Questions I should ask before I agree Rules: - Quote short relevant snippets where helpful. - If something is missing or ambiguous, say that clearly. - Do not give legal advice. - Write in plain English for a smart general reader. Privacy policy text: [PASTE THE POLICY HERE]
Result
Top red flag: The policy allows sharing behavioral data with advertising partners without clearly defining retention limits.
Generated Image
Privacy policies are where products quietly tell you what they collect, how long they keep it, and who else may see it. The problem is that most people do not have time to decode that language every time they install a new app or sign up for a service.
This prompt helps with that. Paste in a privacy policy and ask an AI model to turn it into a practical checklist, with the risks, controls, and missing details called out clearly.
Best for
Reviewing app sign-up flows, SaaS terms updates, browser extension policies, and AI tool privacy disclosures.
Model
GPT-5 or Claude 3.7 Sonnet
Prompt
You are a privacy analyst helping a non-lawyer understand a privacy policy. Read the policy text below and turn it into a practical risk checklist.
Tasks:
1. Summarize what data is collected, what data is inferred, and what data is shared with third parties.
2. Flag any language that suggests broad data retention, vague consent, cross-service tracking, model training use, or sale/sharing for advertising.
3. Extract every user control mentioned, such as opt-out, deletion, export, consent withdrawal, and account settings.
4. Rate the policy on five dimensions from 1 to 5: transparency, user control, data minimization, third-party sharing, and retention clarity.
5. Produce a table with columns: Topic, What the policy says, Risk level, Why it matters, What the user can do.
6. End with:
- Top 3 red flags
- Top 3 reassuring signals
- Questions I should ask before I agree
Rules:
- Quote short relevant snippets where helpful.
- If something is missing or ambiguous, say that clearly.
- Do not give legal advice.
- Write in plain English for a smart general reader.
Privacy policy text:
[PASTE THE POLICY HERE]Why this prompt is useful
It forces the model to do more than summarize. Instead of a vague overview, you get a structured review of data collection, retention, third-party sharing, and user control. That makes it much easier to compare services or catch warning signs before agreeing to new terms.
Tip
For the best result, paste only the relevant sections first, such as data collection, sharing, retention, and user rights. Then run the full policy if you want a complete review.