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affaan-m/dashboard-builder

affaan-m

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.

NewUpdated Sep 9, 2026

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
  • research-ops
  • backend-patterns
  • terminal-ops
Files1
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Overall Score

79/100

Grade

B

Good

Grades are signals, not a certification. Always review a skill yourself before use.

Safety

92

Quality

76

Clarity

84

Completeness

71

Summary

This skill guides agents to build operational monitoring dashboards for platforms like Grafana and SigNoz by starting with real operator questions rather than visual metrics collections. It provides a structured workflow that prioritizes actionable health, performance, and resource visibility over vanity metrics.

Detected Capabilities

dashboard configuration reviewJSON schema inspectionthreshold and alert strategy documentationpanel design guidanceoperational metrics selection

Trigger Keywords

Phrases that agents use to match this skill to user intent.

dashboard design questionsturn metrics operationalgrafana dashboardsigNoz dashboardmonitoring setupkafka dashboardelasticsearch dashboardlatency percentiles

Use Cases

  • Build a Kafka monitoring dashboard that tracks broker health and consumer lag
  • Create a Grafana dashboard for Elasticsearch cluster operations and indexing performance
  • Design an API gateway dashboard focused on latency percentiles and error rates
  • Convert a metrics checklist into an operational dashboard with meaningful thresholds
  • Establish multi-service dashboards with role-based variable filters and refresh policies

Quality Notes

  • Strong emphasis on operator-centric design removes ambiguity about when a panel is justified
  • Workflow progression (questions → schema → MVP → refinement) is practical and prevents scope creep
  • Guardrails section explicitly states common anti-patterns (mixing concerns without structure, missing units/thresholds)
  • Example panel sets for three major platforms (Elasticsearch, Kafka, API gateway) provide concrete guidance
  • Quality checklist is comprehensive but implementation-agnostic — works across dashboard platforms
  • Related skills section appropriately references `research-ops` and `backend-patterns`, positioning this as a downstream skill
  • Does not assume familiarity with any single dashboard platform; guidance translates across Grafana, SigNoz, and others
  • Missing: no guidance on dashboard variables, templating, or dynamic filter construction — a common gap in real-world dashboards
  • Missing: no error handling or troubleshooting section for dashboard query failures or data unavailability
  • Lacks specific query language examples (PromQL, Datadog query, etc.) — intentionally platform-agnostic but could show at least one concrete example
Model: claude-haiku-4-5-20251001Analyzed: Sep 9, 2026

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Version History

  1. v1.3

    Content updated

    ✦ AINo behavioral changes detected.

    2026-09-09

    LATEST
  2. v1.2

    Content updated

    ✦ AINo behavioral changes detected in this version.

    2026-07-14

    View This Version
  3. v1.1

    Content updated

    ✦ AIAdds LICENSE file.

    2026-04-20

    View This Version
  4. v1.0

    2026-04-12

    View This VersionInitial version

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