> For the complete documentation index, see [llms.txt](https://docs.concurrence.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.concurrence.com/agent.md). # Agent - [Agent Core](https://docs.concurrence.com/agent/agents.md): Versioned agent identity, background, behavioral guidance, communication patterns, and voice configuration. - [Reasoning Engine](https://docs.concurrence.com/agent/reasoning-engine.md): How agent guidance, Context Graphs, tools, and channel controls coordinate reasoning, ongoing work, and responses across supported interactions. - [Universal Reasoning and the Liquid World Model](https://docs.concurrence.com/agent/universal-reasoning.md): How problem definitions, source-linked world-model views, exact programs, fast decisions, and deliberative models compose into a reasoning system. - [Context Graphs](https://docs.concurrence.com/agent/context-graphs.md): Structured state machines that define conversation flow, decision points, and safety boundaries for agent workflows. - [Dynamic Behaviors](https://docs.concurrence.com/agent/context-graphs/dynamic-behaviors.md): Classic API dynamic behavior sets, including semantic triggers, instruction injection, tool changes, versioning, and Platform API alternatives. - [Memory](https://docs.concurrence.com/agent/memory.md): How source-linked observations and bounded models preserve useful context, with scoped recall when an agent needs detail from earlier interactions. - [Clinical Tools](https://docs.concurrence.com/agent/clinical-tools.md): Current built-in world tools for patient lookup, scheduling, clinical reads, and source-attributed writes. - [Platform Functions](https://docs.concurrence.com/agent/platform-functions.md): Workspace-registered SQL, AI, Python, and table-valued functions for governed data retrieval and computation. - [Continuous Improvement](https://docs.concurrence.com/agent/pattern-discovery-and-reuse.md): Turn feedback into a reviewed workflow, test changes against clear criteria, and use production results to guide the next release. --- # 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 by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.concurrence.com/agent.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. 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.