Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add alivirgo/Major-AI-Skills --skill grafanagit clone --depth 1 https://github.com/alivirgo/Major-AI-SkillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/alivirgo/major-ai-skills/grafana)<a href="https://agentmods.dev/skills/alivirgo/major-ai-skills/grafana"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/grafana/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/alivirgo/major-ai-skills/grafana"><img src="https://agentmods.dev/badge/skills/alivirgo/major-ai-skills/grafana.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00023 | $0.00641 |
| Opus 5 | $0.00012 | $0.00320 |
| Sonnet 5 | $0.00005 | $0.00128 |
| Haiku 4.5 | $0.00002 | $0.00064 |
Grade A, and why
grafana scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Grafana Dashboards & Alerts AI Skill Guide
Overview & Engine Architecture
Grafana visualizes metrics, logs, and traces from pluggable data sources (Prometheus, Loki, Tempo, CloudWatch, etc.). Dashboards are graphs of panels with template variables; unified alerting evaluates rules and routes notifications. Agents design readable operational dashboards (RED/USE), keep variables consistent, and attach runbook links to alerts.
Data sources (Prometheus/Loki/...)
-> Grafana
|- Dashboards / folders
|- Explore
|- Unified alerting -> contact points
When to use this skill
- Building service or infrastructure dashboards
- Wiring Prometheus/Loki datasources
- Migrating UI dashboards to provisioning JSON/YAML
- Creating alert rules that page humans
Operational directives
- One dashboard purpose per audience (oncall service view vs executive KPI).
- Use template variables for
env,service,namespace- do not hardcode. - Prefer rate/error/duration panels near the top for services.
- Alerts need severity labels and runbook URLs.
- Provision dashboards as code for critical views so they are reviewable.
Panel query example (Prometheus)
sum(rate(http_requests_total{service="$service",env="$env"}[5m])) by (status)
Dashboard variables
| Variable | Type | Example |
|---|---|---|
env |
custom/datasource | dev, prod |
service |
query label_values | label_values(http_requests_total, service) |
namespace |
query | Kubernetes namespace |
Alerting sketch
- Condition: error ratio > 5% for 10 minutes
- Labels:
severity=page,service=api - Annotation: summary +
runbook_url - Contact point: PagerDuty/Slack with severity routing
Best practices
- Keep units explicit (seconds, bytes, percent).
- Avoid dozens of high-cardinality legend series on one panel.
- Use repeat panels sparingly; they can explode load.
- Version-control provisioning under
grafana/dashboards/.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday Changed · -5 tokens per session b3623cd3cb51
- 7d ago First seen · 81 lines · 28 tokens per session scan A 01e953493c39
grafana is a skill published in the GitHub repository alivirgo/Major-AI-Skills (1 stars, last pushed today), licensed MIT. It adds 23 tokens to every session and 641 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-05.
Other skills, from other repositories
monitoring-setup
Set up comprehensive monitoring with Prometheus, Grafana, and alerting. Covers metrics, dashboards, SLOs, and on-call runbooks.
ax-extract-workflow
Reconstruct workflow behind a past coding-agent artifact using local ax sessions/commits/skills/tool traces. Use when asked how X was built.
agenttrace-session-audit
Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.
querying-yandex-cloud
Read Yandex Cloud through its REST API. Applies to any question about VMs, metrics, logs, audit events, Kubernetes, managed databases, serverless, networking or any other Yandex Cloud resource. Never shell out to the yc CLI — it is not how this agent reaches Yandex Cloud and is usually not installed.
grafana-expert
Expert-level Grafana dashboards, visualization, data sources, alerting, and production operations. Use when the user mentions dashboards, visualization, monitoring, observability, or alerting, or when the task involves Grafana Architecture, Installation on Kubernetes, Data Sources, or Dashboard JSON.
kubernetes-operator
Deploy and manage applications on Kubernetes. Covers deployments, services, ingress, HPA, secrets, and production-grade cluster configuration.