> For the complete documentation index, see [llms.txt](https://docs.sweep.finance/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.sweep.finance/ecosystem-components/platform/cases.md). # Cases #### **What is Cases** Cases is a value-based reward game where users open digital cases to receive predefined rewards with different values. Each case contains a structured set of possible outcomes, designed to provide a range of results rather than a binary win or lose experience. When a case is opened, users always receive a reward, and the outcome is generated instantly based on the case configuration. The experience focuses on variability in value rather than the absence of rewards, allowing users to engage with different risk and reward levels across cases. *** #### **How it works** Users begin by selecting a case based on its price and potential reward structure. After selecting a case: * The user confirms the case opening * The system processes the interaction instantly * A reward is generated based on predefined probabilities * The result is displayed immediately Each case is designed with a defined reward range, meaning users receive an outcome every time a case is opened. Different cases offer different levels of variability, allowing users to choose between more stable or more dynamic reward profiles. *** #### **Key mechanics** Cases operate on a predefined distribution model where each possible reward has a fixed probability and value range. * Each case includes multiple reward outcomes * Rewards vary in value rather than existing as win/lose states * Users always receive a result for every interaction * Higher-value outcomes occur less frequently, while lower-value outcomes occur more often This creates a system where outcomes are consistent with the case design and transparent in structure. At the same time, each case opening contributes to the platform’s overall system: * Every interaction generates transaction volume * A fixed **5% protocol fee** is applied * **2.5% is burned** and **2.5% is distributed in USDT** This ensures that gameplay remains connected to the broader ecosystem while maintaining a consistent reward-based structure. --- # 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://docs.sweep.finance/ecosystem-components/platform/cases.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.