analyzing-mlflow-session
Analyzes an MLflow session — a sequence of traces from a multi-turn chat conversation or interaction. Use when the user asks to debug a chat conversation, review session or chat history, find where a multi-turn chat went wrong, or analyze patterns across turns. Triggers on "analyze this session", "what happened in this conversation", "debug session", "review chat history", "where did this chat go wrong", "session traces", "analyze chat", "debug this chat".
Install
With your agent
Install OMGSkills skill "mlflow/skills:analyze-mlflow-chat-session" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
git clone https://github.com/mlflow/skills /tmp/skills && ln -s /tmp/skills/analyze-mlflow-chat-session ~/.claude/skills/analyzing-mlflow-sessionFrom README
Analyzing an MLflow Chat Session What is a Session? A session groups multiple traces that belong to the same chat conversation or user interaction. Each trace in the session represents one turn: the user's input and the system's response. Traces within a session are linked by a shared session ID stored in trace metadata. The session ID is stored in trace metadata under the key mlflow.trace.session. This key contains dots, which affects filter syntax (see below). All traces sharing the same value for this key belong to the same session. Reconstructing the Conversation Reconstructing a session's conversation is a multi-step process: discover the input/output schema from the first trace, extract those fields efficiently across all session traces, then inspect specific turns as needed. Do NOT fetch full traces for every turn — use --extract-fields on the search command instead. Step 1: Discover the schema.
More from this repo
agent-evaluation
Use this when you need to EVALUATE OR IMPROVE or OPTIMIZE an existing LLM agent's output quality - including improving...
analyzing-mlflow-trace
Analyzes a single MLflow trace to answer a user query about it.
build-a-scorer
Help the user choose, create, iterate, or align MLflow judges and scorers for an agent, RAG app, LLM app, or GenAI...