·querying-mlflow-metrics
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querying-mlflow-metrics

mlflow/skills

Fetches aggregated trace metrics (token usage, latency, trace counts, quality evaluations) from MLflow tracking servers. Triggers on requests to show metrics, analyze token usage, view LLM costs, check usage trends, or query trace statistics.

6Installs·1Trend·@mlflow

Installation

$npx skills add https://github.com/mlflow/skills --skill querying-mlflow-metrics

SKILL.md

Run scripts/fetchmetrics.py to query metrics from an MLflow tracking server.

Output: Average and median scores for each evaluator (e.g., correctness, relevance)

| -s, --server | Yes | MLflow server URL | | -x, --experiment-ids | Yes | Experiment IDs (comma-separated) | | -m, --metric | Yes | tracecount, latency, inputtokens, outputtokens, totaltokens | | -a, --aggregations | Yes | COUNT, SUM, AVG, MIN, MAX, P50, P95, P99 | | -d, --dimensions | No | Group by: tracename, tracestatus |

Fetches aggregated trace metrics (token usage, latency, trace counts, quality evaluations) from MLflow tracking servers. Triggers on requests to show metrics, analyze token usage, view LLM costs, check usage trends, or query trace statistics. Source: mlflow/skills.

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Install command
npx skills add https://github.com/mlflow/skills --skill querying-mlflow-metrics
Category
</>Dev Tools
Verified
First Seen
2026-02-11
Updated
2026-02-18

Quick answers

What is querying-mlflow-metrics?

Fetches aggregated trace metrics (token usage, latency, trace counts, quality evaluations) from MLflow tracking servers. Triggers on requests to show metrics, analyze token usage, view LLM costs, check usage trends, or query trace statistics. Source: mlflow/skills.

How do I install querying-mlflow-metrics?

Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/mlflow/skills --skill querying-mlflow-metrics Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code or Cursor

Where is the source repository?

https://github.com/mlflow/skills