> For the complete documentation index, see [llms.txt](https://prismnetwork.gitbook.io/prismnetwork-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://prismnetwork.gitbook.io/prismnetwork-docs/5.-risk-management-system/5.4-audit-logs-feedback-loops-and-trustworthy-iteration.md). # 5.4 Audit Logs, Feedback Loops, and Trustworthy Iteration Prism Network's trust model features traceability and post-mortem capabilities. The system maintains complete logs for user authorization, data calls, signal generation, strategy outputs, order executions, failure handling, and result settlements. Every execution records event information, market source, strategy source, execution path, order parameters, filled price, slippage costs, fees, position changes, exception reasons, settlement status, and final outcomes. These audit logs serve user-side queries, system-side post-mortem analysis, and risk event tracking. Users can review historical orders, strategy execution records, pending profits, settled profits, withdrawable assets, and historical settlement records. The system, in turn, reviews previous signal judgments, market selection, position allocation, execution costs, and risk parameters against actual execution results. Because prediction markets have clear event settlement outcomes, Prism Network can compare pre-execution judgments with final results. The system evaluates whether probability judgments were reasonable, signal weights were effective, market selection was correct, position allocation was overly concentrated, execution costs impacted returns, and whether risk conditions required adjustment. For signal sources, market paths, or strategy types that demonstrate repeated instability, the system reduces their weighting and restricts them from entering automated execution workflows. For signal combinations, market paths, and strategy structures that have been repeatedly validated as effective, the system codifies them into the strategy library and experience repository, providing references for subsequent similar events. --- # 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://prismnetwork.gitbook.io/prismnetwork-docs/5.-risk-management-system/5.4-audit-logs-feedback-loops-and-trustworthy-iteration.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.