Dashboard Builder
SkillMonitoring & opsThis skill lets your AI build monitoring dashboards for Grafana, SigNoz, and similar platforms. It organizes your metrics around the real questions the people running your systems need answered, so you get a working dashboard instead of a vanity board.
Available today. Use it from your connected AI after setup.
No other account needed.
After adding the skill, tell your AI what you monitor and which questions you want the dashboard to answer. It will build the dashboard on your chosen platform.
Then ask your AI: use the Dashboard Builder skill
What your AI can do with it
- Build monitoring dashboards for Grafana
- Build monitoring dashboards for SigNoz
- Organize metrics around the questions operators actually need answered
- Turn raw metrics into a dashboard people actually use
- Support other monitoring platforms similar to Grafana and SigNoz
What this skill tells your AI
The instructions your AI receives, as published by affaan-m/ecc in skills/dashboard-builder/SKILL.md and read by ahel’s review.
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:
- overview
- performance
- resources
- 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-opsbackend-patternsterminal-ops
Signals
- GitHub stars
- 256k
- Forks
- 38k
- Last commit
- Sep 2026
Others that do the same job
Advanced
- Catalog kind
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dashboard-builder-affaan-m- Source
- github.com/affaan-m/ecc