> For the complete documentation index, see [llms.txt](https://docs.selaciti.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.selaciti.com/architecture/execution-engine.md). # Execution Engine Once a model wins the seat, its decision has to reach the market safely. Selaciti executes through **Robinhood Agentic**, so the Creator Fee Vault trades on regulated rails inside a controlled account rather than an anonymous bot on an unknown venue. ## Connection * The agent connects to a dedicated Robinhood Agentic account through Robinhood's **MCP server**. * A single URL links the account; no custody of user funds is required for the Creator Fee Vault's operation. ## Budget and bounds * The account is funded with a **reserved budget** set aside only for the agent's trades. * The selected model can act only within that budget and the risk layer's exposure caps. ## Order handling * The model's proposal is translated into a concrete order with sizing from the risk layer. * Stop-loss, take-profit, and time bounds are attached where appropriate. * Positions and performance are visible in the app. ## Protections * **Per-trade notifications** on every action the agent takes. * **Reserved budget** the agent cannot exceed. * **Disconnect anytime** directly from the app. * **Circuit breakers** when conditions degrade. ## Post-trade * Realized outcomes update each model's track record and the leaderboard. * Realized profit is routed to the buyback-and-burn engine. See also: [Robinhood Agentic](/architecture/robinhood-agentic.md) and [The Creator Fee Vault](/overview/tax-wallet.md). --- # 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.selaciti.com/architecture/execution-engine.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.