Monitoring ObservabilitySAFE
The most comprehensive toolkit for Claude Code -- 135 agents, 35 curated skills, 42 commands, 176+ plugins, 20 hooks, 15 rules, 7 templates, 14 MCP configs, 26 companion apps, 52 ecosystem entries, and more.
Overview
The most comprehensive toolkit for Claude Code -- 135 agents, 35 curated skills, 42 commands, 176+ plugins, 20 hooks, 15 rules, 7 templates, 14 MCP configs, 26 companion apps, 52 ecosystem entries, and more.
f03e77eaf446OBSERVED · 2026-10-11What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
---
name: monitoring-observability
description: Monitoring and observability with OpenTelemetry, Prometheus, Grafana dashboards, and structured logging
---
# Monitoring & Observability
## OpenTelemetry Setup
```typescript
import { NodeSDK } from "@opentelemetry/sdk-node";
import { OTLPTraceExporter } from "@opentelemetry/exporter-trace-otlp-http";
import { OTLPMetricExporter } from "@opentelemetry/exporter-metrics-otlp-http";
import { HttpInstrumentation } from "@opentelemetry/instrumentation-http";
import { PgInstrumentation } from "@opentelemetry/instrumentation-pg";
import { PeriodicExportingMetricReader } from "@opentelemetry/sdk-metrics";
const sdk = new NodeSDK({
serviceName: "order-service",
traceExporter: new OTLPTraceExporter({
url: "http://otel-collector:4318/v1/traces",
}),
metricReader: new PeriodicExportingMetricReader({
exporter: new OTLPMetricExporter({
url: "http://otel-collector:4318/v1/metrics",
}),
exportIntervalMillis: 15000,
}),
instrumentations: [
new HttpInstrumentation(),
new PgInstrumentation(),
],
});
sdk.start();
process.on("SIGTERM", () => sdk.shutdown());
```
## Custom Spans and Metrics
```typescript
import { trace, metrics, SpanStatusCode } from "@opentelemetry/api";
const tracer = trace.getTracer("order-service");
const meter = metrics.getMeter("order-service");
const orderCounter = meter.createCounter("orders.created", {
description: "Number of orders created",
});
const orderDuration = meter.createHistogram("orders.processing_duration_ms", {
description: "Order processing duration in milliseconds",
unit: "ms",
});
async function createOrder(input: CreateOrderInput) {
return tracer.startActiveSpan("createOrder", async (span) => {
try {
span.setAttributes({
"order.customer_id": input.customerId,
"order.item_count": input.items.length,
});
const start = performance.now();
const order = await db.order.create({ data: input });
orderCounter.add(1, { status: "success" });
orderDuration.record(performance.now() - start);
span.setStatus({ code: SpanStatusCode.OK });
return order;
} catch (error) {
span.setStatus({ code: SpanStatusCode.ERROR, message: error.message });
orderCounter.add(1, { status: "error" });
throw error;
} finally {
span.end();
}
});
}
```
## Prometheus Metrics
```yaml
# prometheus.yml
global:
scrape_interval: 15s
scrape_configs:
- job_name: "api-servers"
static_configs:
- targets: ["api-1:9090", "api-2:9090"]
metrics_path: /metrics
- job_name: "node-exporter"
static_configs:
- targets: ["node-exporter:9100"]
```
```typescript
import { collectDefaultMetrics, Counter, Histogram, Registry } from "prom-client";
const registry = new Registry();
collectDefaultMetrics({ register: registry });
const httpRequestDuration = new Histogram({
name: "http_request_duration_seconds",
help: "HTTP request duration in seconds",
labelNames: ["method", "route", "status"],
buckets: [0.01, 0.05, 0.1, 0.5, 1, 5],
registers: [registry],
});
app.use((req, res, next) => {
const end = httpRequestDuration.startTimer();
res.on("finish", () => {
end({ method: req.method, route: req.route?.path ?? req.path, status: res.statusCode });
});
next();
});
app.get("/metrics", async (req, res) => {
res.set("Content-Type", registry.contentType);
res.end(await registry.metrics());
});
```
## Structured Logging
```typescript
import pino from "pino";
const logger = pino({
level: process.env.LOG_LEVEL ?? "info",
formatters: {
level: (label) => ({ level: label }),
},
redact: ["req.headers.authorization", "password", "token"],
});
function requestLogger(req, res, next) {
const start = Date.now();
res.on("finish", () => {
logger.info({
method: req.method,
url: req.url,
status: res.statusCode,
duration_ms: Date.now() - start,
trace_id: req.headers["x-trace-id"],
});
});
next();
}
```
## Alerting Rules
```yaml
groups:
- name: api-alerts
rules:
- alert: HighErrorRate
expr: rate(http_request_duration_seconds_count{status=~"5.."}[5m]) / rate(http_request_duration_seconds_count[5m]) > 0.05
for: 5m
labels:
severity: critical
annotations:
summary: "Error rate above 5% for {{ $labels.route }}"
- alert: HighLatency
expr: histogram_quantile(0.99, rate(http_request_duration_seconds_bucket[5m])) > 2
for: 10m
labels:
severity: warning
```
## Anti-Patterns
- Logging sensitive data (passwords, tokens, PII) without redaction
- Using string interpolation in log messages instead of structured fields
- Creating unbounded cardinality in metric labels (e.g., user IDs as labels)
- Not correlating logs and traces with a shared trace ID
- Alerting on symptoms (high CPU) without understanding root cause
- Missing SLO definitions before building dashboards
## Checklist
- [ ] OpenTelemetry SDK initialized with auto-instrumentation for HTTP, DB, and messaging
- [ ] Custom spans added for business-critical operations
- [ ] Metrics use bounded label cardinality
- [ ] Structured logging with JSON output and secret redaction
- [ ] Trace context propagated across service boundaries
- [ ] Alerting rules based on SLOs (error rate, latency percentiles)
- [ ] Dashboards show RED metrics (Rate, Errors, Duration) per service
- [ ] Log retention and rotation policies configuredTrust audit
SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (0)
No findings outside the package's declared scope.
Gates applied: no_behavioural_pass.
f03e77eaf446full audit observations/trust-audit/skill/rohitg00__monitoring-observability.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-11 | f03e77eaf446 | SAFE | B | 89 | first audit |
Questions
What does the Monitoring Observability skill do?
The most comprehensive toolkit for Claude Code -- 135 agents, 35 curated skills, 42 commands, 176+ plugins, 20 hooks, 15 rules, 7 templates, 14 MCP configs, 26 companion apps, 52 ecosystem entries, and more.
Is Monitoring Observability safe to install?
The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.
What can Monitoring Observability access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
How current is this page?
The grade is for one exact copy of the source (f03e77eaf446), read on 2026-10-11. The repository is watched, and a new audit runs when it changes — this is the first audit.