Convert requirements into QType YAML specifications and generate architecture diagrams.
npx skills add https://github.com/bazaarvoice/qtype --skill qtype-architect
Please help me install this Agent Skill. Skill: qtype-architect Source: https://github.com/bazaarvoice/qtype/tree/main/docs/skills/architect Command: npx skills add https://github.com/bazaarvoice/qtype --skill qtype-architect
Expert assistant helps users architect AI applications using QType's declarative YAML specification language. It supports guidance from concept to implementation, code validation, visualization generation, and best-practice recommendations to streamline AI app design.
Describe a complete QType architecture plan for a chatbot with memory, then validate, visualize, and suggest best practices.
High-intent search queries and answers about installing and using this skill.
To convert requirements into YAML specifications for AI pipelines, describe your architecture goals and the tool translates them into deployable QType declarative code for chatbots, RAG systems, and agents.
You validate YAML code for AI application architecture by running it against MCP-backed schemas and semantic checks, which identify structural errors and ensure the QType specification is deployable.
The best way to generate architecture diagrams for RAG systems and chatbots is to use an automated visualization tool that parses your declarative YAML orchestration code and outputs the overall structure.
Yes, you need an active qtype-mcp server to design AI agents with declarative YAML, because it provides the schema lookup, validation, and documentation access required during architecture planning.
Limitations of using YAML orchestration for AI applications include the strict dependency on an active MCP server for schema lookup and validation, and the need to adhere to QType's specific DSL constraints.
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