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 atretyak1985/swarmery --skill monitoringgit clone --depth 1 https://github.com/atretyak1985/swarmeryWrote 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/atretyak1985/swarmery/monitoring)<a href="https://agentmods.dev/skills/atretyak1985/swarmery/monitoring"><img src="https://agentmods.dev/badge/skills/atretyak1985/swarmery/monitoring/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/atretyak1985/swarmery/monitoring"><img src="https://agentmods.dev/badge/skills/atretyak1985/swarmery/monitoring.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 | $0.00041 | $0.00763 |
| Opus 5.5 | $0.00016 | $0.00305 |
| Sonnet 5.5 | $0.00008 | $0.00153 |
| Haiku 4.5 | $0.00004 | $0.00076 |
Grade A, and why
monitoring scanned grade A with 1 finding 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 1mo 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
You get a `Histogram` with explicit buckets and bounded labels, a ServiceMonitor pointing at the metrics path, an alert with `expr: histogram_quantile(0.95, ...) > 0.5` and a `for: 5m` guard, one Grafana latency panel, p How it starts
The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Purpose
Define, instrument, and verify Prometheus metrics, Grafana dashboards, and alert rules across the project's platform. Produce metric definitions, dashboard JSON, alert rule YAML, and ServiceMonitor resources that connect instrumentation to Prometheus scraping. Placeholders <mainApp>, <device>, and <project> (metric prefix) resolve from project.json.
Rules
- Metric names follow
<project>_{subsystem}_{unit}_{suffix}(e.g.myproject_telemetry_latency_seconds). - Never hardcode label values like
device_id— labels use runtime variables only. - Every alert rule MUST carry a
for:duration, or it fires on single-sample spikes. - Label cardinality stays bounded — never request paths, user IDs, or trace IDs as labels.
- Metrics without ServiceMonitor/scrape wiring are never collected — always wire the scrape path and run
helm linton chart changes. - Metrics, dashboards, and alerts only: "add logging/tracing" belongs to
observability; Helm health probes belong to the project's infra pack skills.
Resources
- Read
resources/instrumentation-procedure.mdwhen instrumenting a service — environment, inputs/outputs, and the six-step procedure with TypeScript/Python code, ServiceMonitor YAML, alert rules, and verification checkpoints. - Read
resources/promql-and-alerts-reference.mdwhen writing panels or alerts, or when something misbehaves — golden-signals PromQL, self-check, common mistakes, escalation, examples, failure modes.
How to use
What it does
Covers Prometheus metrics work end to end: picking metric type and name, instrumenting service code in TypeScript or Python, wiring the scrape path so Prometheus actually collects the series, writing alert rules that survive transient spikes, building Grafana panels, and verifying the metric exists before calling the work done.
When to use it
- Adding a counter, histogram, or gauge and wanting naming and label rules right the first time.
- A metric is defined in code but never shows up in Prometheus — suspect scrape wiring.
- New alert rules with consistent thresholds,
for:durations, and severities; or golden-signal PromQL for a dashboard. - Investigation starting from a Prometheus alert (log/trace-first investigations start with
observability).
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 61 lines · 41 tokens per session scan A 478f05f72e22
monitoring is a skill published in the GitHub repository atretyak1985/swarmery (7 stars, last pushed today), licensed Apache-2.0. It adds 41 tokens to every session and 763 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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