From adk
Explains ADK bot architecture, flow, components, or specific concepts via query. Analyzes project config, source files, runs adk status for tailored explanations and issue flags.
How this command is triggered — by the user, by Claude, or both
Slash command
/adk:adk-explain [component or question about the bot]The summary Claude sees in its command listing — used to decide when to auto-load this command
Load the `adk` skill, then answer the user's question about **$ARGUMENTS** immediately. Resolve shorthand first: "kbs" = knowledge bases, "convos" = conversations, "wf" = workflows, "int" = integrations, "config" = agent.config.ts. If the user named a specific ADK concept or primitive, look it up in the `adk` skill's references and explain it. Match depth to the question — a one-word topic like "kbs" is a conceptual question: give a one-sentence explanation and a short code example from the references, then stop. If the user is in an ADK project (check for `agent.config.ts`), also check ...
Load the adk skill, then answer the user's question about $ARGUMENTS immediately.
Resolve shorthand first: "kbs" = knowledge bases, "convos" = conversations, "wf" = workflows, "int" = integrations, "config" = agent.config.ts.
If the user named a specific ADK concept or primitive, look it up in the adk skill's references and explain it. Match depth to the question — a one-word topic like "kbs" is a conceptual question: give a one-sentence explanation and a short code example from the references, then stop.
If the user is in an ADK project (check for agent.config.ts), also check whether their project uses the component they asked about. If it does, read the relevant source files in src/ and explain their specific setup — not just the generic concept.
If the user asks a broad question ("explain my bot", "what does this do?", or no arguments):
adk status --format json.agent.config.ts and relevant source files in src/.adk skill.npx claudepluginhub botpress/skills --plugin adk/ai-assistantDesigns production-ready AI assistant architecture with NLU, dialog management, context handling, integrations, data flow, and deployment for specified <assistant-type> and options.