dashboard-builder

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.

144,923 stars

Best use case

dashboard-builder is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

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.

Teams using dashboard-builder should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/dashboard-builder/SKILL.md --create-dirs "https://raw.githubusercontent.com/affaan-m/everything-claude-code/main/skills/dashboard-builder/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/dashboard-builder/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How dashboard-builder Compares

Feature / Agentdashboard-builderStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# 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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