> For the complete documentation index, see [llms.txt](https://whitepaper.virtuals.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://whitepaper.virtuals.io/about-virtuals-1/the-protocol/ai-agent-co-contribution-and-provenance/modular-consensus-framework-for-ai-agent-governance/decentralized-ai-agent-contributions-and-nfts/future-ai-agent-cores-and-functional-agents.md). # Future AI Agent Cores and Functional Agents Explore future Virtuals Protocol AI agent cores for image recognition, image generation, multilingual responses, and modular agent capabilities. Future Cores extend VIRTUAL agents with modular AI skills and specialized capabilities. Skillset Cores can add image recognition, image generation, multilingual responses, and other functional AI agent abilities. ### Modular skills for functional AI agents Functional agents combine core AI intelligence with specialized skills for specific tasks. Future Cores enable VIRTUAL agents to expand their capabilities as new models and tools become available. --- # 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://whitepaper.virtuals.io/about-virtuals-1/the-protocol/ai-agent-co-contribution-and-provenance/modular-consensus-framework-for-ai-agent-governance/decentralized-ai-agent-contributions-and-nfts/future-ai-agent-cores-and-functional-agents.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.