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dashboard-builder

Create monitoring dashboards for Grafana, SigNoz, and similar platforms. Choose metrics around operational questions, organize panels by purpose, and define clear titles, units, filters, and thresholds to help operators assess health and bottlenecks.

OriginalShow the original description

Build monitoring dashboards that answer real operator questions for Grafana, SigNoz, and similar platforms. Use when turning metrics into a working dashboard instead of a vanity board.

affaan-m/ECC
AI rating90/ 100See how to install

Good for

  • Build a Kafka monitoring dashboard
  • Monitor Elasticsearch health and performance
  • Track API gateway latency and errors
  • Turn a metrics list into an operational dashboard

Overview

What it does

Build monitoring dashboards that help operators assess a service and decide what to do next. Start by defining questions such as “Is it working normally?”, “Where is processing backing up?”, and “What changed?” Then select metrics that answer those questions. Panels are organized into overview, performance, resources, and service-specific sections. The review also checks panel titles, units, and the thresholds and colors used to indicate status.

When it helps

Use it when preparing a monitoring dashboard in Grafana or SigNoz, or when metrics are already collected but you have not decided what to display. It organizes Kafka processing delays, Elasticsearch search performance, and API gateway response times and error rates into a dashboard operators can use.

Example requests

  • “Build a dashboard for checking Kafka health and processing delays.”
  • “Turn this metrics list into a dashboard showing service health and bottlenecks.”
  • “Organize Elasticsearch monitoring panels to match the structure of our existing Grafana dashboard.”

Notes

Work begins by consulting existing dashboards on the target platform to check their JSON structure and query syntax. Filters, the default time range, and the refresh interval are also reviewed.

This overview was written by AI (OpenAI Codex) from the public SKILL.md. Check the original below for the exact behavior.

Objective evaluation

AI rated this skill on four points using only the contents of its SKILL.md. Stars and popularity are not taken into account.

Clear instructionsIs it clear when to use it and what it does?
AGoodIt defines dashboards as answers to operational questions and gives use cases including Kafka monitoring.
Concrete stepsAre steps, inputs, outputs, and examples spelled out?
AGoodIt provides four workflow steps, service-specific metric examples, and checks for JSON validity and thresholds.
SafetyAre sending data, deleting files, and running commands disclosed?
AGoodThe workflow centers on existing dashboards and JSON creation, with no instructions for external transmission, deletion, or command execution.
Easy setupDoes it need few tools or API keys, and are they documented?
BPartly lackingIt assumes Grafana or SigNoz and access to existing dashboards, but gives no connection setup steps.

The total counts each point as A = 25, B = 15, C = 5. Rated by AI (OpenAI Codex) as of Oct 19, 2026. Treat it as a guide and read the original before installing.

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Files included (1)

  • SKILL.md2.3 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Dashboard Builder

Use this when the task is to build a dashboard people can operate from.

The goal is not "show every metric." The goal is to answer:

  • is it healthy?
  • where is the bottleneck?
  • what changed?
  • what action should someone take?

When to Use

  • "Build a Kafka monitoring dashboard"
  • "Create a Grafana dashboard for Elasticsearch"
  • "Make a SigNoz dashboard for this service"
  • "Turn this metrics list into a real operational dashboard"

Guardrails

  • do not start from visual layout; start from operator questions
  • do not include every available metric just because it exists
  • do not mix health, throughput, and resource panels without structure
  • do not ship panels without titles, units, and sane thresholds

Workflow

1. Define the operating questions

Organize around:

  • health / availability
  • latency / performance
  • throughput / volume
  • saturation / resources
  • service-specific risk

2. Study the target platform schema

Inspect existing dashboards first:

  • JSON structure
  • query language
  • variables
  • threshold styling
  • section layout

3. Build the minimum useful board

Recommended structure:

  1. overview
  2. performance
  3. resources
  4. service-specific section

4. Cut vanity panels

Every panel should answer a real question. If it does not, remove it.

Example Panel Sets

Elasticsearch

  • cluster health
  • shard allocation
  • search latency
  • indexing rate
  • JVM heap / GC

Kafka

  • broker count
  • under-replicated partitions
  • messages in / out
  • consumer lag
  • disk and network pressure

API gateway / ingress

  • request rate
  • p50 / p95 / p99 latency
  • error rate
  • upstream health
  • active connections

Quality Checklist

  • valid dashboard JSON
  • clear section grouping
  • titles and units are present
  • thresholds/status colors are meaningful
  • variables exist for common filters
  • default time range and refresh are sensible
  • no vanity panels with no operator value

Related Skills

  • research-ops
  • backend-patterns
  • terminal-ops

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