Best for
- "Build a Kafka monitoring dashboard"
- "Create a Grafana dashboard for Elasticsearch"
- "Make a SigNoz dashboard for this service"
Source profileQuality 77/100
affaan-m/ECC/skills/dashboard-builder/SKILL.md
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.
- Source repository stars
- 234,327
- Declared platforms
- 0
- Static risk flags
- 0
- Last source update
- 2026-07-27
- Source checked
- 2026-07-28
Decision brief
What it does—and where it fits
Use this when the task is to build a dashboard people can operate from.
Not for
- Tasks that require unconfirmed production actions or broad system permissions.
- Environments where the pinned source and install steps cannot be inspected.
Compatibility matrix
Platform support, with evidence labels
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
Inspect first. Install second.
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
Source-detected install commandSource
npx skills add https://github.com/affaan-m/ECC --skill "skills/dashboard-builder"Safe inspection promptEditorial
Inspect the Agent Skill "dashboard-builder" from https://github.com/affaan-m/ECC/blob/4e973d3eaf92d97f8d2e2d8abb39d8bdc8711b38/skills/dashboard-builder/SKILL.md at commit 4e973d3eaf92d97f8d2e2d8abb39d8bdc8711b38. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
What the source asks the agent to do
- 01
Workflow
Inspect existing dashboards first:
health / availabilitylatency / performancethroughput / volume - 02
When to Use
"Build a Kafka monitoring dashboard"
"Build a Kafka monitoring dashboard""Create a Grafana dashboard for Elasticsearch""Make a SigNoz dashboard for this service" - 03
Guardrails
do not start from visual layout; start from operator questions
do not start from visual layout; start from operator questionsdo not include every available metric just because it existsdo not mix health, throughput, and resource panels without structure - 04
1. Define the operating questions
health / availability
health / availabilitylatency / performancethroughput / volume
Permission review
Static risk signals and limitations
No configured static risk pattern was detected
This is not proof of safety. Runtime behavior, indirect dependencies, and hidden external systems are outside the static scan.
Evidence record
Why each signal appears
EvidenceSourceComputedTestedEditorial
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 77/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 234,327 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Provenance and original SKILL.md
- Repository
- affaan-m/ECC
- Skill path
- skills/dashboard-builder/SKILL.md
- Commit
- 4e973d3eaf92d97f8d2e2d8abb39d8bdc8711b38
- License
- MIT
- Collected
- 2026-07-28
- Default branch
- main
View the original SKILL.md
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-opsbackend-patternsterminal-ops
Alternatives
Compare before choosing
Computed 56234,327
affaan-m/ECC
dashboard-builder
Use it for engineering tasks; the detail page covers purpose, installation, and practical steps.
Computed 53234,327
affaan-m/ECC
dashboard-builder
Review dashboard-builder's use cases, installation, workflow, and original source instructions.
Computed 997
event4u-app/agent-config
design-review
Use when the user says "review the design", "check the UI", or wants a comprehensive UI/UX review. Uses a 7-phase methodology covering interaction, responsiveness, accessibility, and more.
Computed 9831,966
K-Dense-AI/scientific-agent-skills
dask
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.