From skills-for-humanity
Reviews UX flows, data practices, and communication patterns to verify user consent is informed, voluntary, and meaningful. Use during design or implementation of checkout, onboarding, notifications, permissions, or ToS.
How this skill is triggered — by the user, by Claude, or both
Slash command
/skills-for-humanity:s4h-ethics-consent-reviewThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Consent is not a checkbox. It is a meaningful act by a person who understands what they're agreeing to, genuinely has the option to decline, and isn't being manipulated into compliance.
Consent is not a checkbox. It is a meaningful act by a person who understands what they're agreeing to, genuinely has the option to decline, and isn't being manipulated into compliance.
Most consent failures aren't malicious — they're the accumulated result of copy-paste terms, optimised conversion flows, and defaults set by people who never questioned them. This review surfaces those failures before they become patterns users resent or regulators flag.
Every consent decision must pass three tests:
Informed — Does the person genuinely understand what they're agreeing to? Not technically (buried in ToS), but practically. If you explained it plainly in conversation, would they be surprised?
Voluntary — Does the person genuinely have the ability to decline? Is declining as easy as accepting? Are there consequences for declining that make the choice effectively coerced?
Meaningful — Does the person's choice actually matter? Is there genuine optionality, or is the "choice" cosmetic — the default is set to the outcome the business wants and the friction to change it is high?
Step 1: Map the consent moment What specifically is the user being asked to consent to? When in the flow does this happen? What is the default? What happens if they decline?
Framing check: Confirm the ethical situation and the parties affected before continuing. State what you've identified — the specific consent moment, the UX or data practice under review, and who is giving consent — in one sentence, then use AskUserQuestion:
Step 2: Apply the Informed test
Step 3: Apply the Voluntary test
Step 4: Apply the Meaningful test Review for dark patterns — design choices that steer users toward a specific outcome regardless of their preference:
Step 5: Assess the power dynamic Is this a context where users have genuine alternatives? Can they use a competing product without this consent? Are any users in a particularly vulnerable position (under duress, time pressure, low digital literacy) where their ability to exercise real choice is diminished?
Before proceeding, use the AskUserQuestion tool. State your interpretation of the situation in 1–2 sentences — what is being analyzed and what the core question is — then ask:
Proceed based on their selection. If the user reframes, incorporate the correction before running any analysis.
Flow Being Reviewed: [What UX, what consent moment, what the default is]
Informed Test
Voluntary Test
Meaningful Test Dark patterns detected:
Power Dynamic [1–2 sentences: do users have genuine alternatives; any vulnerability concerns]
Verdict [Is this consent genuine? What are the specific problems if any?]
Recommended Changes
The standard is not "legally defensible consent." It is "consent a reasonable person would consider genuine." Those are not the same standard, and in the long run, the second one matters more for user trust.
Where dark patterns are found, name them specifically. Vague concerns are easy to dismiss; named patterns with clear examples are not.
After delivering this output, use AskUserQuestion to offer the next move:
/s4h-ethics-empathy-circle — Apply empathy to those whose consent is in question/s4h-communication-audience-modeling — Model how to communicate consent requirements/s4h-ethics-impact-scan — Scan for impact on those whose consent was not obtainednpx claudepluginhub human-avatar/skills-for-humanityReviews marketing conversion flows (sign-up, upsell, free-trial, cancellation) for dark patterns violating FTC Section 5, Negative Option Rule, and state privacy laws.
Audits e-commerce, subscription, and consent flows for deceptive UX patterns (Brignull taxonomy) and redesigns to eliminate manipulation while preserving conversion goals.
Guides designing informed consent, opt-out options, and human override mechanisms for AI products using data or taking actions.