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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.

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来源信息

仓库
affaan-m/ECC
最近来源活动
2026年8月12日 03:58
检测到的 SKILL.md 语言
英语
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264,820
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39,570

安装方式

默认使用会先检查来源的 Prompt;你也可以切换为直接命令,或下载本地副本。

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决定是否安装前,请先阅读 SKILL.md,以及 SkillsMP 当前展示的配套文件。

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SKILL.md
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name
dashboard-builder
description
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.
metadata
{"version":"1.0.0","origin":"ECC direct-port adaptation"}
# 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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