querying-mlflow-metrics

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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.

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Sourcemlflow/skills
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NPX Install

npx skill4agent add mlflow/skills querying-mlflow-metrics

Tags

Translated version includes tags in frontmatter
mlflow-metricstoken-usage-trackingllm-cost-analysistrace-statisticsmetric-aggregation

SKILL.md Content

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MLflow Metrics

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

Examples

Token usage summary:
bash
python scripts/fetch_metrics.py -s http://localhost:5000 -x 1 -m total_tokens -a SUM,AVG
Output: 
AVG: 223.91  SUM: 7613
Hourly token trend (last 24h):
bash
python scripts/fetch_metrics.py -s http://localhost:5000 -x 1 -m total_tokens -a SUM \
    -t 3600 --start-time="-24h" --end-time=now
Output: Time-bucketed token sums per hour
Latency percentiles by trace:
bash
python scripts/fetch_metrics.py -s http://localhost:5000 -x 1 -m latency -a AVG,P95 -d trace_name
Error rate by status:
bash
python scripts/fetch_metrics.py -s http://localhost:5000 -x 1 -m trace_count -a COUNT -d trace_status
Quality scores by evaluator (assessments):
bash
python scripts/fetch_metrics.py -s http://localhost:5000 -x 1 -v ASSESSMENTS \
    -m assessment_value -a AVG,P50 -d assessment_name
Output: Average and median scores for each evaluator (e.g., correctness, relevance)
Assessment count by name:
bash
python scripts/fetch_metrics.py -s http://localhost:5000 -x 1 -v ASSESSMENTS \
    -m assessment_count -a COUNT -d assessment_name
JSON output: Add 
-o json
to any command.

Arguments

ArgRequiredDescription
-s, --server
YesMLflow server URL
-x, --experiment-ids
YesExperiment IDs (comma-separated)
-m, --metric
Yes
trace_count
, 
latency
, 
input_tokens
, 
output_tokens
, 
total_tokens
-a, --aggregations
Yes
COUNT
, 
SUM
, 
AVG
, 
MIN
, 
MAX
, 
P50
, 
P95
, 
P99
-d, --dimensions
NoGroup by: 
trace_name
, 
trace_status
-t, --time-interval
NoBucket size in seconds (3600=hourly, 86400=daily)
--start-time
No
-24h
, 
-7d
, 
now
, ISO 8601, or epoch ms
--end-time
NoSame formats as start-time
-o, --output
No
table
(default) or 
json
For SPANS metrics (
span_count
, 
latency
), add 
-v SPANS
. For ASSESSMENTS metrics, add 
-v ASSESSMENTS
.
See references/api_reference.md for filter syntax and full API details.