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.
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
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/dashboard-builder/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How dashboard-builder Compares
| Feature / Agent | dashboard-builder | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/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.
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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