// Retrieves MLflow traces using CLI or Python API. Use when the user asks to get a trace by ID, find traces, filter traces by status/tags/metadata/execution time, query traces, or debug failed traces. Triggers on "get trace", "search traces", "find failed traces", "filter traces by", "traces slower than", "query MLflow traces".
Use this when you need to EVALUATE OR IMPROVE or OPTIMIZE an existing LLM agent's output quality - including improving tool selection accuracy, answer quality, reducing costs, or fixing issues where the agent gives wrong/incomplete responses. Evaluates agents systematically using MLflow evaluation with datasets, scorers, and tracing. IMPORTANT - Always also load the instrumenting-with-mlflow-tracing skill before starting any work. Covers end-to-end evaluation workflow or individual components (tracing setup, dataset creation, scorer definition, evaluation execution).
Instruments Python and TypeScript code with MLflow Tracing for observability. Must be loaded when setting up tracing as part of any workflow including agent evaluation. Triggers on adding tracing, instrumenting agents/LLM apps, getting started with MLflow tracing, tracing specific frameworks (LangGraph, LangChain, OpenAI, DSPy, CrewAI, AutoGen), or when another skill references tracing setup. Examples - "How do I add tracing?", "Instrument my agent", "Trace my LangChain app", "Set up tracing for evaluation"
Master dispatcher for all MLflow workflows. Use this skill when the user wants to do anything with MLflow — tracing, evaluating, debugging, or improving an agent. Routes to the right MLflow sub-skill automatically. Triggers on: "use mlflow", "help with mlflow", "mlflow agent", "add mlflow to my project", "trace my agent", "evaluate my agent", or any MLflow task without a specific skill in mind.
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".
Analyzes a single MLflow trace to answer a user query about it. Use when the user provides a trace ID and asks to debug, investigate, find issues, root-cause errors, understand behavior, or analyze quality. Triggers on "analyze this trace", "what went wrong with this trace", "debug trace", "investigate trace", "why did this trace fail", "root cause this trace".
Onboards users to MLflow by determining their use case (GenAI agents/apps or traditional ML/deep learning) and guiding them through relevant quickstart tutorials and initial integration. If an experiment ID is available, it should be supplied as input to help determine the use case. Use when the user asks to get started with MLflow, set up tracking, add observability, or integrate MLflow into their project. Triggers on "get started with MLflow", "set up MLflow", "onboard to MLflow", "add MLflow to my project", "how do I use MLflow".
| name | retrieving-mlflow-traces |
| description | Retrieves MLflow traces using CLI or Python API. Use when the user asks to get a trace by ID, find traces, filter traces by status/tags/metadata/execution time, query traces, or debug failed traces. Triggers on "get trace", "search traces", "find failed traces", "filter traces by", "traces slower than", "query MLflow traces". |
Choose the right approach based on what you have:
| You have... | Use | Command |
|---|---|---|
| Trace ID | Single fetch | mlflow traces get --trace-id <id> |
| Session/user/filters | Search | mlflow traces search --experiment-id <id> --filter-string "..." |
Single fetch - Use when you have a specific trace ID (e.g., from UI, logs, or API response):
mlflow traces get --trace-id tr-69f72a3772570019f2f91b75b8b5ded9
Search - Use when you need to find traces by criteria (session, user, status, time range, etc.):
mlflow traces search --experiment-id 1 --filter-string "metadata.\`mlflow.trace.session\` = 'session_abc'"
trace_id, status (OK/ERROR), timestamp_ms, execution_time_ms, tags, metadata, assessments (human feedback, evaluation results)name, type, attributes, start_time, end_timemlflow traces search --helpmlflow traces search --help
Always run this first to get accurate flags for the installed MLflow version.
The mlflow traces search command is used to search for traces in an MLflow experiment.
Filter traces associated with a specific MLflow run:
# All traces for a run
mlflow traces search --run-id <run_id>
# Failed traces for a run
mlflow traces search --run-id <run_id> --filter-string "trace.status = 'ERROR'"
# Can combine with experiment-id
mlflow traces search --experiment-id 1 --run-id <run_id>
When debugging an issue from the MLflow UI, filter by session or user ID to get all related traces:
# All traces for a specific session (use backticks for special characters in key)
mlflow traces search --experiment-id 1 --filter-string "metadata.\`mlflow.trace.session\` = 'session_abc123'"
# All traces for a specific user
mlflow traces search --experiment-id 1 --filter-string "metadata.\`mlflow.trace.user\` = 'user_456'"
# Failed traces in a session (for root cause analysis)
mlflow traces search --experiment-id 1 --filter-string "metadata.\`mlflow.trace.session\` = 'session_abc123' AND trace.status = 'ERROR'"
# Session traces ordered by time (to see sequence of events)
mlflow traces search --experiment-id 1 --filter-string "metadata.\`mlflow.trace.session\` = 'session_abc123'" --order-by "timestamp_ms ASC"
mlflow traces search --experiment-id 1 --filter-string "trace.status = 'ERROR'"
mlflow traces search --experiment-id 1 --filter-string "trace.status = 'OK'"
# Timestamps are in milliseconds since epoch
# Get current time in ms: $(date +%s)000
# Last hour: $(( $(date +%s)000 - 3600000 ))
mlflow traces search --experiment-id 1 --filter-string "trace.timestamp_ms > $(( $(date +%s)000 - 3600000 ))"
# Traces slower than 1 second
mlflow traces search --experiment-id 1 --filter-string "trace.execution_time_ms > 1000"
# By tag
mlflow traces search --experiment-id 1 --filter-string "tag.environment = 'production'"
# By metadata
mlflow traces search --experiment-id 1 --filter-string "metadata.user_id = 'user_123'"
# Escape special characters in key names with backticks
mlflow traces search --experiment-id 1 --filter-string "tag.\`model-name\` = 'gpt-4'"
mlflow traces search --experiment-id 1 --filter-string "metadata.\`user.id\` = 'abc'"
mlflow traces search --experiment-id 1 --filter-string "feedback.rating = 'positive'"
mlflow traces search --experiment-id 1 --filter-string "trace.text LIKE '%error%'"
Control result count and iterate through pages:
# Limit results per page
mlflow traces search --experiment-id 1 --max-results 50
# Output includes "Next page token: <token>" if more results exist
# Use --page-token to fetch next page
mlflow traces search --experiment-id 1 --max-results 50 --page-token "eyJvZmZzZXQiOiA1MH0="
# Output format (table or json)
mlflow traces search --experiment-id 1 --output json
# Include span details in output
mlflow traces search --experiment-id 1 --include-spans
# Order results
mlflow traces search --experiment-id 1 --order-by "timestamp_ms DESC"
When you need to retrieve details about a specific trace, use the mlflow traces get command.
mlflow traces get --trace-id <trace_id>
For detailed syntax, fetch from documentation:
WebFetch(
url: "https://mlflow.org/docs/latest/genai/tracing/search-traces.md",
prompt: "Extract the filter syntax table showing supported fields, operators, and examples."
)
Common filters:
trace.status: OK, ERROR, IN_PROGRESStrace.execution_time_ms, trace.timestamp_ms: numeric comparisonmetadata.\mlflow.trace.session`, metadata.`mlflow.trace.user``: session/user filteringtag.<key>, metadata.<key>: exact match or patternspan.name, span.type: exact match or patternfeedback.<name>, expectation.<name>: assessmentsPattern operators: LIKE, ILIKE (case-insensitive), RLIKE (regex)
For mlflow.search_traces(), see: https://mlflow.org/docs/latest/genai/tracing/search-traces.md