Dashboard builder

Skill aAAaqwq/AGI-Super-Team/skills/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.From its SKILL.md

Install

npx -y skills add aAAaqwq/AGI-Super-Team --skill dashboard-builder

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

SKILL.md

2.3 KB, 474 tokens by cl100k_base, as published. Nobody here has run it

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:

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-ops
backend-patterns
terminal-ops

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Gives 3 of the 12 instructions most monitoring observability skills give in 474 tokens

Counted across 530 of the 532 authors here whose files we hold, read 2026-09-06

Use structured JSON loggingin 40 of 530, across 36 files
Link every alert to a runbookin 29 of 530, across 27 files
Attach correlation IDs to every log linein 19 of 530, across 16 files
Alert on symptoms rather than causesin 19 of 530, across 17 files
Use OpenTelemetry for distributed tracingin 15 of 530, across 14 files
Alert on symptoms users feelin 15 of 530, across 13 files
Implement health check endpointsin 14 of 530, across 10 files
Inspect existing dashboards firsthere, and in 12 of 530, across 4 files
Build the minimum useful boardhere, and in 12 of 530, across 4 files
Start from operator questionshere, and in 12 of 530, across 4 files
Propagate trace context across boundariesin 11 of 530, across 10 files
Include trace id in all log entriesin 10 of 530, across 9 files

Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.