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 BagelHole/DevOps-Security-Agent-Skills --skill sre-dashboardsgit clone --depth 1 https://github.com/BagelHole/DevOps-Security-Agent-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/bagelhole/devops-security-agent-skills/sre-dashboards)<a href="https://agentmods.dev/skills/bagelhole/devops-security-agent-skills/sre-dashboards"><img src="https://agentmods.dev/badge/skills/bagelhole/devops-security-agent-skills/sre-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/bagelhole/devops-security-agent-skills/sre-dashboards"><img src="https://agentmods.dev/badge/skills/bagelhole/devops-security-agent-skills/sre-dashboards.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00048 | $0.00872 |
| Opus 5 | $0.00024 | $0.00436 |
| Sonnet 5 | $0.00010 | $0.00174 |
| Haiku 4.5 | $0.00005 | $0.00087 |
Grade A, and why
sre-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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SRE Dashboards
Build dashboards that help teams detect, triage, and prevent reliability incidents.
When to Use This Skill
Use this skill when:
- Defining service-level dashboards for production systems
- Tracking SLO health and error-budget burn
- Creating incident command-center views
- Standardizing dashboard patterns across teams
Prerequisites
- Metrics pipeline (Prometheus, OpenTelemetry, or vendor equivalent)
- Logs/traces linked to services and environments
- Agreed service taxonomy (team, service, tier, environment)
Dashboard Architecture
Structure dashboards in layers:
- Executive Reliability View: SLO attainment, incident counts, MTTR trends.
- Service Health View: RED/USE metrics, dependency health, release markers.
- Deep-Dive View: Per-endpoint latency, resource saturation, error categories.
Keep each view answer-oriented:
- Are customers impacted?
- What changed?
- Where is the bottleneck?
Core SRE Panels
Golden Signals
- Latency: p50/p95/p99 request duration by endpoint
- Traffic: request throughput and queue depth
- Errors: 5xx rate, failed jobs, timeout ratio
- Saturation: CPU, memory, disk I/O, thread/connection pool exhaustion
SLO Panels
- Current SLI value (rolling windows: 5m, 1h, 24h, 30d)
- Error-budget remaining (%)
- Burn-rate panels (fast and slow windows)
- Multi-window burn alert status
Change Correlation
- Deployment markers and config-change annotations
- Feature flag state overlays
- Upstream/downstream dependency error rates
Example PromQL Snippets
# API error rate (%)
100 * sum(rate(http_requests_total{status=~"5.."}[5m]))
/ sum(rate(http_requests_total[5m]))
# p95 latency by route
histogram_quantile(0.95,
sum by (le, route) (rate(http_request_duration_seconds_bucket[5m]))
)
# Fast burn rate (5m / 1h)
(
sum(rate(http_requests_total{status=~"5.."}[5m]))
/ sum(rate(http_requests_total[5m]))
)
/
(
sum(rate(http_requests_total{status=~"5.."}[1h]))
/ sum(rate(http_requests_total[1h]))
)
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.
- 10d ago First seen · 119 lines · 48 tokens per session scan A af924c21a9a9
sre-dashboards is a skill published in the GitHub repository BagelHole/DevOps-Security-Agent-Skills (1,067 stars, last pushed 3mo ago), licensed MIT. It adds 48 tokens to every session and 872 once invoked, about $0.0002 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 2026-08-30.
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