claude-skills is a collection of specialized skills that extends Claude Code for full-stack development. Developers use it for programming languages, frameworks, infrastructure, APIs, testing, DevOps, security, data and machine learning, platform tasks, and project workflows.
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 Jeffallan/claude-skills --skill monitoring-expertgit clone --depth 1 https://github.com/Jeffallan/claude-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/jeffallan/claude-skills/monitoring-expert)<a href="https://agentmods.dev/skills/jeffallan/claude-skills/monitoring-expert"><img src="https://agentmods.dev/badge/skills/jeffallan/claude-skills/monitoring-expert/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/jeffallan/claude-skills/monitoring-expert"><img src="https://agentmods.dev/badge/skills/jeffallan/claude-skills/monitoring-expert.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 141 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00100 | $0.01521 |
| Opus 5 | $0.00050 | $0.00760 |
| Sonnet 5 | $0.00020 | $0.00304 |
| Haiku 4.5 | $0.00010 | $0.00152 |
Grade A, and why
monitoring-expert 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- monitoring-expert — 92% identical, 2 lines differ
How it starts
The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Monitoring Expert
Observability and performance specialist implementing comprehensive monitoring, alerting, tracing, and performance testing systems.
Core Workflow
- Assess — Identify what needs monitoring (SLIs, critical paths, business metrics)
- Instrument — Add logging, metrics, and traces to the application (see examples below)
- Collect — Configure aggregation and storage (Prometheus scrape, log shipper, OTLP endpoint); verify data arrives before proceeding
- Visualize — Build dashboards using RED (Rate/Errors/Duration) or USE (Utilization/Saturation/Errors) methods
- Alert — Define threshold and anomaly alerts on critical paths; validate no false-positive flood before shipping
Quick-Start Examples
Structured Logging (Node.js / Pino)
import pino from 'pino';
const logger = pino({ level: 'info' });
// Good — structured fields, includes correlation ID
logger.info({ requestId: req.id, userId: req.user.id, durationMs: elapsed }, 'order.created');
// Bad — string interpolation, no correlation
console.log(`Order created for user ${userId}`);
Prometheus Metrics (Node.js)
import { Counter, Histogram, register } from 'prom-client';
const httpRequests = new Counter({
name: 'http_requests_total',
help: 'Total HTTP requests',
labelNames: ['method', 'route', 'status'],
});
const httpDuration = new Histogram({
name: 'http_request_duration_seconds',
help: 'HTTP request latency',
labelNames: ['method', 'route'],
buckets: [0.05, 0.1, 0.3, 0.5, 1, 2, 5],
});
// Instrument a route
app.use((req, res, next) => {
const end = httpDuration.startTimer({ method: req.method, route: req.path });
res.on('finish', () => {
httpRequests.inc({ method: req.method, route: req.path, status: res.statusCode });
end();
});
next();
});
// Expose scrape endpoint
app.get('/metrics', async (req, res) => {
res.set('Content-Type', register.contentType);
res.end(await register.metrics());
});
OpenTelemetry Tracing (Node.js)
import { NodeSDK } from '@opentelemetry/sdk-node';
import { OTLPTraceExporter } from '@opentelemetry/exporter-trace-otlp-http';
import { trace } from '@opentelemetry/api';
const sdk = new NodeSDK({
traceExporter: new OTLPTraceExporter({ url: 'http://jaeger:4318/v1/traces' }),
});
sdk.start();
// Manual span around a critical operation
const tracer = trace.getTracer('order-service');
async function processOrder(orderId) {
const span = tracer.startSpan('order.process');
span.setAttribute('order.id', orderId);
try {
const result = await db.saveOrder(orderId);
span.setStatus({ code: SpanStatusCode.OK });
return result;
} catch (err) {
span.recordException(err);
span.setStatus({ code: SpanStatusCode.ERROR });
throw err;
} finally {
span.end();
}
}
What ships with it
8 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.
- references/alerting-rules.md 3.4 KB
- references/application-profiling.md 6.2 KB
- references/capacity-planning.md 8.1 KB
- references/dashboards.md 3.7 KB
- references/opentelemetry.md 3.3 KB
- references/performance-testing.md 5.8 KB
- references/prometheus-metrics.md 3.0 KB
- references/structured-logging.md 2.8 KB
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 · 179 lines · 100 tokens per session scan A dc69392186b8
monitoring-expert is a skill published in the GitHub repository Jeffallan/claude-skills (11,401 stars, last pushed 1mo ago), licensed MIT. It adds 100 tokens to every session and 1,521 once invoked, about $0.0005 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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