Security audit
Security checks for vulnerabilities and agentic risk
This is a Chinese-language business-model design skill with no executable code, but users should add privacy safeguards before applying its data-commercialization examples.
Install only if you want Chinese-language guidance for service-dominant business-model design. When using its examples involving user, location, education, or smart-home data, add explicit privacy, consent, anonymization, retention, access-control, and legal-review requirements before turning the model into a real product plan.
The description says the skill is used 'when needing to design a service-centered, multi-party value co-creation business model for a specific domain and product,' but it does not define explicit trigger phrases, boundaries, or exclusion cases. This makes invocation scope ambiguous because many ordinary strategy or product-design requests could plausibly match the description.
The natural-language instructions and examples are all in Chinese, which effectively forces a specific language for users of the skill. The file does not state that the skill is region-specific or that users may choose another language, so it may violate language/locale policy requirements.
The example explicitly presents user data as a monetizable asset and describes providing data analysis to governments and research institutions without any accompanying privacy, consent, minimization, anonymization, or lawful-use safeguards. In a business-model design skill, this can normalize privacy-invasive practices and lead users to implement data commercialization patterns that violate data protection requirements or user expectations.
The smart-home scenario discusses household data authorization, analysis, and feedback to hardware manufacturers, but omits critical safeguards for highly sensitive in-home behavioral data. Because smart-home data can reveal occupancy, routines, and intimate household patterns, presenting commercialization and partner-sharing flows without strong privacy constraints increases the risk of intrusive surveillance, secondary misuse, and harmful downstream implementations.
No suspicious patterns detected.
