didit-biometric-age-estimationEstimates a person's age from a facial image via the Didit standalone API. Use when implementing age gating, checking if someone is over 18 or 21, performing...
Install via ClawdBot CLI:
clawdbot install rosasalberto/didit-biometric-age-estimationGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Sends data to undocumented external endpoint (potential exfiltration)
POST → https://apx.didit.me/auth/v2/programmatic/register/`Calls external URL not in known-safe list
https://docs.didit.meAI Analysis
The external API calls are consistent with the skill's stated purpose of biometric age estimation and are documented for authentication and billing. There is no evidence of credential harvesting, hidden instructions, or obfuscation. The primary risk is the standard privacy consideration of sending biometric data to a third-party service.
Audited Apr 16, 2026 · audit v1.0
Generated Mar 21, 2026
Online platforms like streaming services or gaming sites use this skill to verify users are over 18 before granting access to mature content. It provides a low-friction alternative to ID uploads, with passive liveness preventing spoofing and adaptive fallback for borderline cases.
Retailers selling age-restricted products like alcohol or tobacco implement this skill at checkout to confirm buyers meet legal age requirements. The per-country restrictions ensure compliance with local laws, while configurable thresholds adapt to different products.
Banks and fintech apps use this skill during account creation to verify customers are over 18 for regulatory compliance. The high-accuracy under-18 detection helps prevent underage sign-ups, and the liveness check reduces fraud risk in digital onboarding.
Social networks deploy this skill to detect and restrict underage users from accessing platforms with age limits, such as those requiring users to be 13+. The passive liveness ensures real faces are used, and warnings like AGE_BELOW_MINIMUM trigger review workflows.
Healthcare providers integrate this skill to verify patient ages for accessing sensitive medical records or telemedicine services, ensuring compliance with privacy laws like HIPAA. The adaptive mode with ID fallback handles uncertain cases securely.
Charge customers based on the number of age estimation API calls made, with tiered pricing for high-volume users. Revenue comes from direct API usage fees, supplemented by credits purchased via top-up endpoints.
Offer monthly or annual subscriptions that include a set number of API calls, with overage charges. This model provides predictable revenue and encourages long-term partnerships with businesses needing regular age verification.
Sell custom licenses to large enterprises for unlimited usage, with added features like dedicated support and custom thresholds. Revenue is generated through upfront or annual licensing fees tailored to client needs.
💬 Integration Tip
Start by testing with sample images to validate API responses, and ensure proper error handling for cases like insufficient credits or invalid formats to maintain user experience.
Scored Jun 19, 2026
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