dashboard-builder

Build operator-question-driven monitoring dashboards for Grafana and SigNoz.

Updated Sep 13, 2025
One-click install
npx skills add https://github.com/llmh333/employee_management_spring --skill dashboard-builder-llmh333
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: dashboard-builder
Source: https://github.com/llmh333/employee_management_spring/tree/main/.gemini/skills/dashboard-builder
Command: npx skills add https://github.com/llmh333/employee_management_spring --skill dashboard-builder-llmh333

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

It prevents teams from wasting time on vanity dashboards by guiding the creation of monitoring boards that directly answer the questions operators need to keep systems healthy, fast, and stable.

Core Features & Use Cases

  • Operator-question-first design: structures dashboards around health/availability, latency/performance, throughput/volume, saturation/resources, and service-specific risk rather than building from a visual layout or an exhaustive metric list.
  • Platform-aware dashboard construction: inspects and follows the target dashboard schema (e.g., JSON structure, query language, variables, threshold styling, and section layout) to ensure the result works in Grafana/SigNoz-style tooling.
  • Actionable panel quality: enforces guardrails so panels have titles, units, and meaningful thresholds, and removes panels that don’t answer a real operational question.

Quick Start

Tell the AI: “Create a Grafana dashboard for my Kafka cluster that answers health, bottlenecks, and what action to take, using the existing dashboard patterns and including only operator-relevant panels.”

Frequently Asked Questions about dashboard-builder

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

FAQPage Schema
How do I build a Grafana dashboard for Kafka monitoring that operators can actually use?

Build a Kafka monitoring dashboard by structuring panels around operator questions like health, bottlenecks, and required actions. Apply question-driven panel scoping to include only operator-relevant metrics, removing vanity panels that don't answer real operational needs.

What is the best way to structure operational metrics for an Elasticsearch cluster?

Structure Elasticsearch operational metrics by scoping panels to health, latency, throughput, saturation, and service-specific risks. This question-driven approach ensures dashboards answer real operator questions instead of presenting exhaustive vanity metric collections.

Does dashboard building work with SigNoz for API gateway observability?

Yes, dashboard building works with SigNoz by applying platform-aware schema inspection. It follows target dashboard JSON structures, query languages, and threshold styling to ensure constructed API gateway observability boards function correctly in SigNoz-style tooling.

How to create monitoring dashboards with meaningful thresholds and units?

Create monitoring dashboards with meaningful thresholds and units by applying quality guardrails. Enforce actionable panel quality by ensuring every panel has a title, proper units, sane thresholds, variables, and sensible defaults to answer real operational questions.

Why do my operational dashboards end up with useless vanity metrics?

Operational dashboards contain vanity metrics when built from visual layouts or exhaustive metric lists instead of operator questions. Prevent this by applying question-driven panel scoping focused on health, availability, performance, and saturation.

Can dashboard builder generate panels for API gateways and ingress controllers?

Yes, dashboard builder generates panels for API gateways and ingress controllers by applying minimum useful board structuring. It scopes panels to service-specific risks and operational questions, ensuring the resulting dashboards are operator-ready.