Guide for building, designing, reviewing, evaluating, and troubleshooting applications that use Zep — agent memory built on temporal Context Graphs, for use cases needing low-latency retrieval, one or many users and agents, multi-source ingestion, and governance. Use whenever you write or design code that integrates Zep — adding memory or long-term context to an agent or chatbot, ingesting chat/business/document/JSON data into a Context Graph, retrieving a Context Block or searching the graph, choosing between user graphs and standalone graphs, scoping graphs, defining a custom ontology or custom instructions, or deciding how to evaluate and tune Zep for a use case. Triggers on requests like "add memory to my agent", "integrate Zep", "store this in Zep", "search the Zep graph", "set up a Zep ontology", "how should I structure my Zep graphs", "why is Zep not returning the right context", "help me evaluate Zep", or "make my agent remember users".
Run and manage the Zep eval harness pipeline — document chunking, user ingestion, document ingestion, evaluation, graph inspection, and results analysis. Use when the user asks to run eval harness scripts, use the Zep eval harness, get terminal commands for eval harness operations, chunk documents, ingest users or documents into Zep, run evaluations, inspect graphs, compare evaluation runs, analyze completeness/accuracy metrics, or work with the eval harness data/config/runs directories. Also triggers on "run the harness", "start ingestion", "run evaluation", "chunk the documents", "compare runs", "analyze results", or any reference to the eval harness pipeline.