Core
Identity, privacy, trackers, commercial flows, forms, third parties, accessibility, marketing, IP, security and AI use.
Magic / Legal Preflight
Before you ask an AI to “make the site compliant”, tell it what you are building, where it operates and whether it can affect someone's health, job, home, money or rights.
The model
A restaurant website, a recruiting AI and a clinical decision-support product should not receive the same checklist. The preflight builds the applicable stack in four layers.
Identity, privacy, trackers, commercial flows, forms, third parties, accessibility, marketing, IP, security and AI use.
France, Germany, USA or multi-country triage. The tool loads the legal layer from where you are established and where you operate.
Health, jobs, finance, insurance, housing, education, minors, biometrics, public services, justice or critical infrastructure.
Drafting is not ranking. Ranking is not an automatic decision. The tool asks how much the AI can actually affect a person.
Layer 02 · Where?
“International compliance” is not one legal regime. The tool starts with establishment, customers and users, then combines only the relevant country layers.
LCEN · RGPD · CNIL · consumer
French website identity, privacy, tracking and consumer rules layered on top of EU law.
DDG · DSGVO · TDDDG · BGB · BFSG
German digital-service, privacy, device-tracking, e-commerce and accessibility rules.
Federal baseline · state detector
A federal baseline plus state and local rules selected from the actual users, customers and use case.
Jurisdiction triage
There is no single international checklist: determine establishment, target markets and regulated activities first.
Layer 03 · What can the product affect?
The relevant question is often not your “industry”. It is what the software does: publishing health information is different from recommending treatment; listing apartments is different from ranking tenants.
Health data · clinical decisions
General health content, patient data and clinical decision support are three very different regulatory situations.
Candidates · workers · ranking
CV screening, ranking, assessment and employee monitoring can become high-consequence decision systems.
Credit · affordability · investment
Creditworthiness, lending and financial recommendations can trigger both sector regulation and explainability duties.
Underwriting · pricing · claims
Life and health insurance risk assessment is explicitly sensitive under the EU AI Act and is heavily regulated elsewhere.
Tenant screening · eligibility
A property-listing site is not the same thing as software that scores applicants or recommends who gets a home.
Admissions · scoring · proctoring
Admissions, exam scoring, placement and remote proctoring can create high-impact decisions and sensitive data flows.
Age · parental consent · design
Minor users change privacy, consent, advertising and product-design obligations.
Face · voice · unique identification
Face, voice, emotion and identity systems can trigger special-category data and specific AI / state-law restrictions.
Eligibility · benefits · triage
Systems that influence access to public assistance, healthcare benefits or emergency services deserve specialist review.
Rights · disputes · justice
Tools influencing legal rights, courts, law enforcement or dispute outcomes require a much higher review threshold.
Energy · water · transport · telecom
Safety-relevant infrastructure can add cybersecurity, resilience and regulated-AI obligations.
Layer 04 · Decision intensity
If AI ranks people, recommends a consequential outcome or executes one automatically, the prompt stops treating compliance like a footer exercise. It asks who is affected, what evidence drives the decision, who can override it, how someone can contest it, and which specialist must review it.
Examples that trigger extra review
What you will not get:
A fake “73% legally compliant” score. The output is an applicability matrix with evidence, uncertainties, engineering actions and explicit specialist-review flags.
Build the audit
Answer once here. The generated prompt carries your context into Claude Code, Codex, Cursor or another coding agent, tells it to inspect the repository and asks it to challenge your answers when the code says something different.
Magic Form / Legal Preflight
Build a repository-audit prompt from jurisdiction, business model, data, AI decision intensity and sensitive use cases. The generated prompt tells the coding agent what to inspect, what not to assume and where specialist review is mandatory.
Generated prompt
The form composes your case-specific inputs with the reusable master prompt. Copy it into ChatGPT or another AI workflow.
Optional bonus · not legal compliance
Semantic HTML, metadata, sitemap, robots controls, structured data and an optionalllms.txt can help machines understand a site. The preflight labels these separately so an emerging discoverability convention never masquerades as a legal obligation.
LEGAL ≠ SEO ≠ AI DISCOVERABILITY
They can be audited in the same repository, but they answer different questions. Keeping the layers separate makes the final report much easier to trust.
Source discipline
Legal rules change. The prompt tells the coding agent to prefer legislation, regulators and government guidance, and to record what it checked rather than relying on an undated template.
Pack verification: 20 September 2026
Credit & evolution
Starting point: 0xloucash's French “Legal — la checklist pour vibe coder sans amende”. This version restructures the idea into a reusable engine, separates legal compliance from AI discoverability, adds Germany / USA / multi-country triage and introduces sensitive-use and AI-decision layers.