> For the complete documentation index, see [llms.txt](https://solyx.gitbook.io/solyx-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://solyx.gitbook.io/solyx-docs/disclaimer/limitations-and-ethical-considerations.md). # Limitations & Ethical Considerations No system designed to model trust is immune from error, and Solyx is no exception. Despite its technical precision and behavioral focus, there are fundamental limitations and ethical boundaries that must be acknowledged. *** ## False Positives / False Negatives Machine learning models and heuristics are inherently probabilistic. This means that sometimes a legitimate wallet may be flagged as sybil-like due to anomalous behavior, or a manipulative actor may temporarily appear trustworthy by mimicking real users. Solyx addresses this by continuously iterating its models and supplementing them with community annotations. These user-submitted insights help correct mistakes, add nuance, and surface early warnings for edge cases the system might overlook. *** ## Over-Reliance on Scores A wallet’s behavior is complex and dynamic, and reducing its reputation to a single score risks oversimplification. Solyx is not meant to be a gatekeeper, it is a signaling tool. Protocols are encouraged to combine trust scores with other factors like annotations, historical contribution, or token ownership when making access or eligibility decisions. Relying solely on the score can lead to coordination failure or unfair exclusion. *** ## Privacy vs. Public Accountability Solyx does not collect or infer personal identities. However, it does create behavioral memory—a persistent fingerprint of what a wallet has done. This memory is pseudonymous but public. While this helps defend against sybils and scammers, it also introduces the risk of social labeling or misinterpretation. To balance this, all annotations are pseudonymous, scores are transparently generated, and users have the ability to contest, clarify, or annotate their own reputation. *** ## Anti-Gaming Commitments As with any reputation system, there’s always the risk of gaming. Bad actors may attempt to spoof high-trust behavior or farm scores through shallow engagement. Solyx is built with this reality in mind. The scoring engine decays trust over time, prioritizes long-term patterns over short bursts, and is continuously adapted to new gaming tactics. By treating adversarial pressure as a feature, not a bug, Solyx aims to remain resilient and responsive. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://solyx.gitbook.io/solyx-docs/disclaimer/limitations-and-ethical-considerations.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.