Scaffolds a Pydantic v2 output schema and attaches it to an Agent for structured JSON output. Covers provider-specific paths (OpenAI json_schema, Anthropic tool-use, Gemini response_schema, fallback parsing). Invoke when the user says "create a structured output schema", "make my agent return JSON", "define a Pydantic output model", "get structured data from the agent", "add output schema", or "validate agent output".
Diagnoses failing or misbehaving django-ai-sdk agents using a structured debug checklist and extended thinking. Invoke when the user says "my agent is not working", "debug my agent", "agent returns empty response", "tool is not being called", "agent loop not terminating", "agent is ignoring the system prompt", "why is my agent failing", or "trace an agent run".
Scaffolds calls to the embeddings, audio (transcription/synthesis), and image generation modules. Invoke when the user says "generate an image", "transcribe audio", "generate speech", "use the images module", "add image generation to my agent", "process audio with the SDK", or "embed a document".
Migrates existing AI code (raw OpenAI/Anthropic SDK calls, LangChain chains, LlamaIndex pipelines) to django-ai-sdk patterns. Produces side-by-side before/after code with a migration checklist. Invoke when the user says "migrate from OpenAI SDK", "migrate from LangChain", "convert my existing agent", "replace openai.ChatCompletion", or "port to django-ai-sdk".
Scaffolds EpisodicMemory (DB-backed ordered recall) or SemanticMemory (pgvector embedding search) backends and attaches them to an Agent. Invoke when the user says "add memory to my agent", "set up episodic memory", "set up semantic memory", "give my agent long-term memory", "use BaseMemory", "store and retrieve memories", or "make my agent remember things".
Scaffolds multi-agent orchestration patterns (pipeline, parallel, handoff/router) from the djangosdk.orchestration module. Invoke when the user says "create a multi-agent pipeline", "set up agent orchestration", "build a supervisor agent", "create an evaluator agent", "chain agents together", "fan out to parallel agents", or "build a router agent".
Scaffolds an MCP (Model Context Protocol) server and client using djangosdk.mcp. Invoke when the user says "set up MCP", "create an MCP server", "connect to an MCP client", "expose tools via MCP", "use MCP decorators", "integrate MCP", or "add MCP support".
Configures observability backends (LangSmith, Langfuse, OpenTelemetry) by generating the correct AI_SDK settings block, environment variables, and Django signal receivers. Invoke when the user says "add observability", "set up LangSmith", "configure Langfuse", "add OpenTelemetry tracing", "how do I trace my agents", "enable tracing", or "monitor my agent".