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 dallay/agents-skills --skill grafana-dashboardsgit clone --depth 1 https://github.com/dallay/agents-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/dallay/agents-skills/grafana-dashboards)<a href="https://agentmods.dev/skills/dallay/agents-skills/grafana-dashboards"><img src="https://agentmods.dev/badge/skills/dallay/agents-skills/grafana-dashboards/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/dallay/agents-skills/grafana-dashboards"><img src="https://agentmods.dev/badge/skills/dallay/agents-skills/grafana-dashboards.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 | $0.00056 | $0.02219 |
| Opus 5 | $0.00028 | $0.01110 |
| Sonnet 5 | $0.00011 | $0.00444 |
| Haiku 4.5 | $0.00006 | $0.00222 |
Grade A, and why
grafana-dashboards 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 11d ago.
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.
This is a copy
80% identical to grafana-dashboards — 126 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 397 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Grafana Dashboards
Create and manage production-ready Grafana dashboards for comprehensive system observability.
Purpose
Design effective Grafana dashboards for monitoring applications, infrastructure, and business metrics.
When to Use
- 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
{
"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 }
}
]
}
}
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.
- 11d ago First seen · 397 lines · 56 tokens per session scan A 11d315b083e4
grafana-dashboards is a skill published in the GitHub repository dallay/agents-skills (2 stars, last pushed 18d ago), licensed MIT. It adds 56 tokens to every session and 2,219 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 80% identical to grafana-dashboards, differing in 126 lines, and is treated as a copy.
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