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erwinv2k-TKG
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victoriametrics-metrics

Query and analyze time-series metrics in VictoriaMetrics using MetricsQL.

Updated Mar 26, 2026
Search Tags:#monitoring#time-series#sre#promql#metrics analysis#victoriametrics#metricsql
One-click install
npx skills add https://github.com/erwinv2k-TKG/AgentesVSC --skill victoriametrics-metrics-erwinv2k-tkg
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: victoriametrics-metrics
Source: https://github.com/erwinv2k-TKG/AgentesVSC/tree/main/packs/incidentfox/sre-agent/.claude/skills/metrics-victoriametrics
Command: npx skills add https://github.com/erwinv2k-TKG/AgentesVSC --skill victoriametrics-metrics-erwinv2k-tkg

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires httpx, and includes scripts (resource) components.

What problem does it solve? Investigating production issues requires querying time-series metrics, but unbounded queries against high-cardinality data flood the context and slow down analysis. This Skill enforces a context-efficient workflow for exploring VictoriaMetrics data safely. ## Core Features & Use Cases - Cardinality Discovery: Run get_statistics.py first to see active series counts, top metric names, and top jobs before querying. - Targeted MetricsQL Queries: Execute instant or range queries with output limits, supporting full PromQL plus MetricsQL extensions like WITH templates, rollup functions, and label manipulation. - Label Exploration: Discover available label names and values scoped to specific series selectors. - Use Case: During an incident, check the error rate for a service by running statistics first, then querying topk(5, sum by (service) (rate(http_requests_total{status=~"5.."}[5m]))) to find the worst offenders without dumping thousands of series. ## Quick Start Ask the agent to investigate the current error rate for the api job in VictoriaMetrics, starting with metric statistics.

Frequently Asked Questions about victoriametrics-metrics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I query metrics in VictoriaMetrics with MetricsQL?▼

Run query_metrics.py with a MetricsQL expression such as rate(http_requests_total[5m]). Instant queries return one value per series by default; add --type range for trends, and use topk() to cap output size.

What is the difference between MetricsQL and PromQL?▼

MetricsQL is fully PromQL-compatible and adds extensions like WITH templates for reusable filters, rollup functions for counter-reset-safe rates, and label manipulation functions such as label_set and label_join.

How do I check metric cardinality before querying VictoriaMetrics?▼

Run get_statistics.py with a series selector to see active series count, top metric names, and top jobs. This mandatory first step prevents unbounded queries against high-cardinality data.

Does VictoriaMetrics support PromQL histogram quantile queries?▼

Yes, histogram_quantile works with rate() over bucket series, for example histogram_quantile(0.95, sum by (le) (rate(http_request_duration_seconds_bucket[5m]))) for latency investigation.

Why should I avoid unbounded range queries in VictoriaMetrics?▼

Unbounded range queries can return thousands of series and flood the context window. Always filter with specific labels or wrap queries in topk() and use a step at least twice the scrape interval.

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