> For the complete documentation index, see [llms.txt](https://shoebillh.gitbook.io/shoebill-h/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://shoebillh.gitbook.io/shoebill-h/roadmap.md). # Roadmap The roadmap is an evolving entity and will be updated as such. ### Current state A beta version of an AI Agent with following capabilities * Finding and storing of documentation in vector store for semantic search. * Finding communities building on hyperliquid though vector search, twitter profile analysis. * Initial TG chat integration using RAG allowing you to ask questions about hyperliquid and projects. * Limited relationship storing in knowledge graph , 'BUILD\_ON" relation. * Initial Twitter integration which analyses and scores tweets, quote tweet and reply. * Not yet autonomous. ### Next up * Improve twitter interaction, integration. Improve what and how H tweets * Share insights using twitter posts * Increase relationship detection to improve overall knowledge of the HyperLiquid ecosystem context overall. * Improve autonomy * Add integrations enhancing capabilities and knowledge , like market price analysis and other market indicators. * Open Source the HAI framework --- # 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: ``` GET https://shoebillh.gitbook.io/shoebill-h/roadmap.md?ask= ``` The question should be specific, self-contained, and written in natural language. 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.