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ivanshamaev
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aiops-observability-copilot

Translate infrastructure questions into PromQL and LogQL queries.

14|1|Updated May 5, 2026
Search Tags:#observability#on-call#promql#logql#aiops#alert explanation#grafana dashboard
One-click install
npx skills add https://github.com/ivanshamaev/de-agent-skills --skill aiops-observability-copilot
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: aiops-observability-copilot
Source: https://github.com/ivanshamaev/de-agent-skills/tree/main/group_skills/infra_dataops_group_skills/aiops_observability_copilot
Command: npx skills add https://github.com/ivanshamaev/de-agent-skills --skill aiops-observability-copilot

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It reduces time-to-understanding during incidents by turning infrastructure questions into actionable PromQL/LogQL, and by converting firing alerts into plain-English explanations with contextual incident enrichment.

Core Features & Use Cases

  • Natural language to PromQL/LogQL translation: Converts user questions into Prometheus and Grafana Loki queries for metrics and log exploration.
  • Plain-English alert explanation: Explains what fired, why it matters, the most likely causes, and the immediate next action to take.
  • Context-rich incident summaries: Enriches on-call narratives using recent deployments, related firing alerts, and runbook links.
  • Noisy log reduction via error clustering: Normalizes and clusters similar error log lines to surface unique failure patterns.
  • Grafana dashboard auto-generation: Produces a Grafana dashboard JSON based on service topology and desired metrics.
  • Weekly observability health digests: Summarizes alert trends and SLO risk into a short improvement-focused report.

Quick Start

Ask the AI to translate your question into PromQL or LogQL, then request an alert explanation with incident context for the firing alert using your current metric value and alert labels.

Frequently Asked Questions about aiops-observability-copilot

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

FAQPage Schema
How do I convert natural language questions into PromQL and LogQL queries for Grafana?▼

Natural language to PromQL and LogQL translation converts infrastructure questions directly into Prometheus and Grafana Loki queries. This allows you to explore metrics and logs without manually writing complex query syntax.

How do I explain firing alerts in plain English during on-call incident response?▼

Plain-English alert explanation analyzes firing alerts to describe what fired, why it matters, likely causes, and immediate next actions. This context-rich incident summary reduces time-to-understanding during on-call response.

Can I generate a Grafana dashboard automatically from service topology and desired metrics?▼

Grafana dashboard auto-generation produces dashboard JSON based on your service topology and desired metrics. This allows you to visualize observability data without manually constructing each panel.

How do I reduce noisy logs and surface unique failure patterns in Loki?▼

Noisy log reduction normalizes and clusters similar error log lines to surface unique failure patterns. This process requires log normalization for clustering to help you identify distinct issues during analysis.

What is the best way to summarize alert trends and SLO risk into an observability health report?▼

Weekly observability health digests summarize alert trends and SLO risk into a short improvement-focused report. This provides an anomaly narrative and SLO status summary for ongoing system analysis.

Does alert explanation require specific context like recent deployments or runbook links?▼

Context-rich incident summaries enrich on-call narratives using recent deployments, related firing alerts, and runbook links. This contextual enrichment requires correct query formulation for Prometheus counters and scoping via labels.

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