Agent skill

Grafana Dashboards

by davila7 in davila7/claude-code-templates

Create and manage production-ready Grafana dashboards for comprehensive system observability.

MITAuto-check passedDevOps & Cloud

Install Grafana Dashboards

skills CLI
$ npx skills add davila7/claude-code-templates --skill grafana-dashboards -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install davila7/claude-code-templates grafana-dashboards --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/davila7/claude-code-templates.git skills-src && mkdir -p .claude/skills && cp -r skills-src/cli-tool/components/skills/development/grafana-dashboards .claude/skills/grafana-dashboards && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
grafana-dashboards
GitHub stars
33k
Used in
14 other repos
Token cost
~2.1k tokens
SKILL.md length
336 words
Files
1
Skills in repo
479
Repo updated
First seen
Licence
MIT

At a glance

Create and manage production-ready Grafana dashboards for comprehensive system observability.

  • Works in 7 steps: Hierarchy of Information → RED Method (Services) → USE Method (Resources) → …
  • Tasks that involve Monitoring and alerting
  • SKILL.md covers Do not use this skill when, Instructions, Purpose and Use this skill when, plus 10 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Grafana Dashboards is an agent skill from davila7/claude-code-templates. Create and manage production-ready Grafana dashboards for comprehensive system observability.

Its SKILL.md is about 2.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in DevOps & Cloud, covering Monitoring and alerting. It works with Grafana. The repository describes itself as: CLI tool for configuring and monitoring Claude Code. The licence is MIT.

When your agent uses it

  • Tasks that involve Monitoring and alerting

Example prompts

  • “/grafana-dashboards”

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Hierarchy of Information
  2. RED Method (Services)
  3. USE Method (Resources)
  4. Stat Panel (Single Value)
  5. Time Series Graph
  6. Table Panel
  7. Heatmap

What it can do on your machine

Read from SKILL.md and the folder at commit 79182c5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are json, yaml and hcl).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Grafana Dashboards loads about 2.1k tokens when it runs. Until then it costs about 28 tokens; SKILL.md has 336 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~28
When it runs · the whole SKILL.md, loaded when a task matches
~2.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from davila7/claude-code-templates at commit 79182c5, republished under its MIT licence (© davila7). 336 words, ~2,084 tokens.

Download SKILL.mdSave it as .claude/skills/grafana-dashboards/SKILL.md (or your agent's skills folder).
name
grafana-dashboards
description
Create and manage production-ready Grafana dashboards for comprehensive system observability.
risk
unknown
source
community
date_added
2026-02-27

Grafana Dashboards

Create and manage production-ready Grafana dashboards for comprehensive system observability.

Do not use this skill when

  • The task is unrelated to grafana dashboards
  • You need a different domain or tool outside this scope

Instructions

  • Clarify goals, constraints, and required inputs.
  • Apply relevant best practices and validate outcomes.
  • Provide actionable steps and verification.
  • If detailed examples are required, open resources/implementation-playbook.md.

Purpose

Design effective Grafana dashboards for monitoring applications, infrastructure, and business metrics.

Use this skill when

  • Visualize Prometheus metrics
  • Create custom dashboards
  • Implement SLO dashboards
  • Monitor infrastructure
  • Track business KPIs

Dashboard Design Principles

1. Hierarchy of Information
┌─────────────────────────────────────┐
│  Critical Metrics (Big Numbers)     │
├─────────────────────────────────────┤
│  Key Trends (Time Series)           │
├─────────────────────────────────────┤
│  Detailed Metrics (Tables/Heatmaps) │
└─────────────────────────────────────┘
2. RED Method (Services)
  • Rate - Requests per second
  • Errors - Error rate
  • Duration - Latency/response time
3. USE Method (Resources)
  • Utilization - % time resource is busy
  • Saturation - Queue length/wait time
  • Errors - Error count

Dashboard Structure

API Monitoring Dashboard
json
{
  "dashboard": {
    "title": "API Monitoring",
    "tags": ["api", "production"],
    "timezone": "browser",
    "refresh": "30s",
    "panels": [
      {
        "title": "Request Rate",
        "type": "graph",
        "targets": [
          {
            "expr": "sum(rate(http_requests_total[5m])) by (service)",
            "legendFormat": "{{service}}"
          }
        ],
        "gridPos": {"x": 0, "y": 0, "w": 12, "h": 8}
      },
      {
        "title": "Error Rate %",
        "type": "graph",
        "targets": [
          {
            "expr": "(sum(rate(http_requests_total{status=~\"5..\"}[5m])) / sum(rate(http_requests_total[5m]))) * 100",
            "legendFormat": "Error Rate"
          }
        ],
        "alert": {
          "conditions": [
            {
              "evaluator": {"params": [5], "type": "gt"},
              "operator": {"type": "and"},
              "query": {"params": ["A", "5m", "now"]},
              "type": "query"
            }
          ]
        },
        "gridPos": {"x": 12, "y": 0, "w": 12, "h": 8}
      },
      {
        "title": "P95 Latency",
        "type": "graph",
        "targets": [
          {
            "expr": "histogram_quantile(0.95, sum(rate(http_request_duration_seconds_bucket[5m])) by (le, service))",
            "legendFormat": "{{service}}"
          }
        ],
        "gridPos": {"x": 0, "y": 8, "w": 24, "h": 8}
      }
    ]
  }
}

Reference: See assets/api-dashboard.json

Panel Types

1. Stat Panel (Single Value)
json
{
  "type": "stat",
  "title": "Total Requests",
  "targets": [{
    "expr": "sum(http_requests_total)"
  }],
  "options": {
    "reduceOptions": {
      "values": false,
      "calcs": ["lastNotNull"]
    },
    "orientation": "auto",
    "textMode": "auto",
    "colorMode": "value"
  },
  "fieldConfig": {
    "defaults": {
      "thresholds": {
        "mode": "absolute",
        "steps": [
          {"value": 0, "color": "green"},
          {"value": 80, "color": "yellow"},
          {"value": 90, "color": "red"}
        ]
      }
    }
  }
}
2. Time Series Graph
json
{
  "type": "graph",
  "title": "CPU Usage",
  "targets": [{
    "expr": "100 - (avg by (instance) (rate(node_cpu_seconds_total{mode=\"idle\"}[5m])) * 100)"
  }],
  "yaxes": [
    {"format": "percent", "max": 100, "min": 0},
    {"format": "short"}
  ]
}
3. Table Panel
json
{
  "type": "table",
  "title": "Service Status",
  "targets": [{
    "expr": "up",
    "format": "table",
    "instant": true
  }],
  "transformations": [
    {
      "id": "organize",
      "options": {
        "excludeByName": {"Time": true},
        "indexByName": {},
        "renameByName": {
          "instance": "Instance",
          "job": "Service",
          "Value": "Status"
        }
      }
    }
  ]
}
4. Heatmap
json
{
  "type": "heatmap",
  "title": "Latency Heatmap",
  "targets": [{
    "expr": "sum(rate(http_request_duration_seconds_bucket[5m])) by (le)",
    "format": "heatmap"
  }],
  "dataFormat": "tsbuckets",
  "yAxis": {
    "format": "s"
  }
}

Variables

Query Variables
json
{
  "templating": {
    "list": [
      {
        "name": "namespace",
        "type": "query",
        "datasource": "Prometheus",
        "query": "label_values(kube_pod_info, namespace)",
        "refresh": 1,
        "multi": false
      },
      {
        "name": "service",
        "type": "query",
        "datasource": "Prometheus",
        "query": "label_values(kube_service_info{namespace=\"$namespace\"}, service)",
        "refresh": 1,
        "multi": true
      }
    ]
  }
}
Use Variables in Queries
sum(rate(http_requests_total{namespace="$namespace", service=~"$service"}[5m]))

Alerts in Dashboards

json
{
  "alert": {
    "name": "High Error Rate",
    "conditions": [
      {
        "evaluator": {
          "params": [5],
          "type": "gt"
        },
        "operator": {"type": "and"},
        "query": {
          "params": ["A", "5m", "now"]
        },
        "reducer": {"type": "avg"},
        "type": "query"
      }
    ],
    "executionErrorState": "alerting",
    "for": "5m",
    "frequency": "1m",
    "message": "Error rate is above 5%",
    "noDataState": "no_data",
    "notifications": [
      {"uid": "slack-channel"}
    ]
  }
}

Dashboard Provisioning

dashboards.yml:

yaml
apiVersion: 1

providers:
  - name: 'default'
    orgId: 1
    folder: 'General'
    type: file
    disableDeletion: false
    updateIntervalSeconds: 10
    allowUiUpdates: true
    options:
      path: /etc/grafana/dashboards

Common Dashboard Patterns

Infrastructure Dashboard

Key Panels:

  • CPU utilization per node
  • Memory usage per node
  • Disk I/O
  • Network traffic
  • Pod count by namespace
  • Node status

Reference: See assets/infrastructure-dashboard.json

Database Dashboard

Key Panels:

  • Queries per second
  • Connection pool usage
  • Query latency (P50, P95, P99)
  • Active connections
  • Database size
  • Replication lag
  • Slow queries

Reference: See assets/database-dashboard.json

Application Dashboard

Key Panels:

  • Request rate
  • Error rate
  • Response time (percentiles)
  • Active users/sessions
  • Cache hit rate
  • Queue length

Best Practices

  1. Start with templates (Grafana community dashboards)
  2. Use consistent naming for panels and variables
  3. Group related metrics in rows
  4. Set appropriate time ranges (default: Last 6 hours)
  5. Use variables for flexibility
  6. Add panel descriptions for context
  7. Configure units correctly
  8. Set meaningful thresholds for colors
  9. Use consistent colors across dashboards
  10. Test with different time ranges

Dashboard as Code

Terraform Provisioning
hcl
resource "grafana_dashboard" "api_monitoring" {
  config_json = file("${path.module}/dashboards/api-monitoring.json")
  folder      = grafana_folder.monitoring.id
}

resource "grafana_folder" "monitoring" {
  title = "Production Monitoring"
}
Ansible Provisioning
yaml
- name: Deploy Grafana dashboards
  copy:
    src: "{{ item }}"
    dest: /etc/grafana/dashboards/
  with_fileglob:
    - "dashboards/*.json"
  notify: restart grafana

Reference Files

  • assets/api-dashboard.json - API monitoring dashboard
  • assets/infrastructure-dashboard.json - Infrastructure dashboard
  • assets/database-dashboard.json - Database monitoring dashboard
  • references/dashboard-design.md - Dashboard design guide
  • prometheus-configuration - For metric collection
  • slo-implementation - For SLO dashboards

© davila7, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in cli-tool/components/skills/development/grafana-dashboards of davila7/claude-code-templates.

Open the folder on GitHubat commit 79182c5

Used in 14 other repositories

We found 34 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 14 other GitHub owners. This page covers the copy in davila7/claude-code-templates, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Grafana Dashboards next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Grafana Dashboards compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Grafana Dashboards this skilldavila7/claude-code-templates33k14 repos~2.1kAutomated safety check: PassMIT
Mz Release SignoffMaterializeInc/materialize6.4k—~7.2kAutomated safety check: PassCustom licence
Axiom Dashboard Builderopenclaw/clawhub9.5k—~4.9kAutomated safety check: PassMIT
Happy Infra Metrics and Grafanaslopus/happy24k—~2kAutomated safety check: NotesMIT
Syncmetapawurb/hotpath-rs1.9k—~1.2kAutomated safety check: NotesMIT
Optimize Slurm TopologyNVlabs/alpasim1.3k—~1.6kAutomated safety check: PassApache-2.0

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Works with

Categories

Questions about Grafana Dashboards

What does Grafana Dashboards do?

Create and manage production-ready Grafana dashboards for comprehensive system observability. Grafana Dashboards is an agent skill from davila7/claude-code-templates. Create and manage production-ready Grafana dashboards for comprehensive system observability.

When should I use Grafana Dashboards?

Grafana Dashboards fits situations like: tasks that involve Monitoring and alerting.

How do I install Grafana Dashboards in Claude Code?

Run `npx skills add davila7/claude-code-templates --skill grafana-dashboards -a claude-code`. Or copy the skill folder (cli-tool/components/skills/development/grafana-dashboards in davila7/claude-code-templates) into .claude/skills/grafana-dashboards in your project. Claude Code loads it when a task matches its description.

How do I install Grafana Dashboards in Codex?

Run `npx skills add davila7/claude-code-templates --skill grafana-dashboards -a codex`. Or copy the skill folder (cli-tool/components/skills/development/grafana-dashboards in davila7/claude-code-templates) into .agents/skills/grafana-dashboards in your project. Codex loads it when a task matches its description.

Can I use Grafana Dashboards in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add davila7/claude-code-templates --skill grafana-dashboards -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/grafana-dashboards, .gemini/skills/grafana-dashboards, .github/skills/grafana-dashboards and .opencode/skills/grafana-dashboards in your project.

What does Grafana Dashboards need to run?

SKILL.md names no scripts, command-line tools or credentials: Grafana Dashboards is instructions for the agent only.

Does Grafana Dashboards access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Grafana Dashboards safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Grafana Dashboards use?

Grafana Dashboards is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Grafana Dashboards use?

About 2.1k tokens (SKILL.md is roughly 8.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Grafana Dashboards?

Skills that share tags, products or a category with Grafana Dashboards: Mz Release Signoff (MaterializeInc/materialize, 6.4k stars), Axiom Dashboard Builder (openclaw/clawhub, 9.5k stars), Happy Infra Metrics and Grafana (slopus/happy, 24k stars) and Syncmeta (pawurb/hotpath-rs, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Grafana Dashboards?

davila7 (a GitHub user) maintains it in davila7/claude-code-templates, which has 32,552 GitHub stars. The repository holds 479 skills in this directory. The repository was last updated on October 11, 2026.

Source: davila7/claude-code-templates on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.