Agent skill

Monitoring Observability

by rohitg00 in rohitg00/awesome-claude-code-toolkit

Monitoring and observability with OpenTelemetry, Prometheus, Grafana dashboards, and structured logging

Apache-2.0Auto-check passedDevOps & Cloud

Install Monitoring Observability

skills CLI
$ npx skills add rohitg00/awesome-claude-code-toolkit --skill monitoring-observability -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install rohitg00/awesome-claude-code-toolkit monitoring-observability --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/rohitg00/awesome-claude-code-toolkit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/monitoring-observability .claude/skills/monitoring-observability && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
monitoring-observability
GitHub stars
2.7k
Token cost
~1.4k tokens
SKILL.md length
129 words
Files
1
Skills in repo
37
Repo updated
First seen
Licence
Apache-2.0

At a glance

Monitoring and observability with OpenTelemetry, Prometheus, Grafana dashboards, and structured logging

  • Tasks that involve Observability
  • SKILL.md covers OpenTelemetry Setup, Custom Spans and Metrics, Prometheus Metrics and Structured Logging, plus 3 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Tasks that involve Monitoring and alerting

What it does

Monitoring Observability is an agent skill from rohitg00/awesome-claude-code-toolkit. Monitoring and observability with OpenTelemetry, Prometheus, Grafana dashboards, and structured logging

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in DevOps & Cloud, covering Observability and Monitoring and alerting. It works with OpenTelemetry, Prometheus and Grafana. The repository describes itself as: 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… The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Observability
  • Tasks that involve Monitoring and alerting

Example prompts

  • “/monitoring-observability”

What it can do on your machine

Read from SKILL.md and the folder at commit ebdf1d5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are typescript and yaml).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Monitoring Observability loads about 1.4k tokens when it runs. Until then it costs about 32 tokens; SKILL.md has 129 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~32
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from rohitg00/awesome-claude-code-toolkit at commit ebdf1d5, republished under its Apache-2.0 licence (© rohitg00). 129 words, ~1,385 tokens.

Download SKILL.mdSave it as .claude/skills/monitoring-observability/SKILL.md (or your agent's skills folder).
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 configured

© rohitg00, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/monitoring-observability of rohitg00/awesome-claude-code-toolkit.

Open the folder on GitHubat commit ebdf1d5

Compare with similar skills

Monitoring Observability next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Monitoring Observability compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Monitoring Observability this skillrohitg00/awesome-claude-code-toolkit2.7k—~1.4kAutomated safety check: PassApache-2.0
Archestra Dev Observabilityarchestra-ai/archestra4.4k—~1.2kAutomated safety check: PassCustom licence
Frontmcp Observabilityagentfront/frontmcp146—~4.6kAutomated safety check: PassApache-2.0
Monitoring Observabilityahmedasmar/devops-claude-skills203—~3.9kAutomated safety check: PassNone
Monitoring ExpertJeffallan/claude-skills12k—~1.6kAutomated safety check: PassMIT
Alloygrafana/skills279—~1.3kAutomated safety check: PassApache-2.0

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Categories

Questions about Monitoring Observability

What does Monitoring Observability do?

Monitoring and observability with OpenTelemetry, Prometheus, Grafana dashboards, and structured logging. Monitoring Observability is an agent skill from rohitg00/awesome-claude-code-toolkit.

When should I use Monitoring Observability?

Monitoring Observability fits situations like: tasks that involve Observability; tasks that involve Monitoring and alerting.

How do I install Monitoring Observability in Claude Code?

Run `npx skills add rohitg00/awesome-claude-code-toolkit --skill monitoring-observability -a claude-code`. Or copy the skill folder (skills/monitoring-observability in rohitg00/awesome-claude-code-toolkit) into .claude/skills/monitoring-observability in your project. Claude Code loads it when a task matches its description.

How do I install Monitoring Observability in Codex?

Run `npx skills add rohitg00/awesome-claude-code-toolkit --skill monitoring-observability -a codex`. Or copy the skill folder (skills/monitoring-observability in rohitg00/awesome-claude-code-toolkit) into .agents/skills/monitoring-observability in your project. Codex loads it when a task matches its description.

Can I use Monitoring Observability in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add rohitg00/awesome-claude-code-toolkit --skill monitoring-observability -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/monitoring-observability, .gemini/skills/monitoring-observability, .github/skills/monitoring-observability and .opencode/skills/monitoring-observability in your project.

What does Monitoring Observability need to run?

SKILL.md names no scripts, command-line tools or credentials: Monitoring Observability is instructions for the agent only.

Does Monitoring Observability access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Monitoring Observability safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Monitoring Observability use?

Monitoring Observability is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Monitoring Observability use?

About 1.4k tokens (SKILL.md is roughly 5.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Monitoring Observability?

Skills that share tags, products or a category with Monitoring Observability: Archestra Dev Observability (archestra-ai/archestra, 4.4k stars), Frontmcp Observability (agentfront/frontmcp, 146 stars), Monitoring Observability (ahmedasmar/devops-claude-skills, 203 stars) and Monitoring Expert (Jeffallan/claude-skills, 12k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Monitoring Observability?

rohitg00 (a GitHub user) maintains it in rohitg00/awesome-claude-code-toolkit, which has 2,685 GitHub stars. The repository holds 37 skills in this directory. The repository was last updated on May 12, 2026.

Source: rohitg00/awesome-claude-code-toolkit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.