monitoring-expert

monitoring-expert is a skill for Claude Code, Codex from Threat-Vector-Security/guardian-agent. It costs 0 tokens per session (1,281 once invoked), scanned A, original, Apache-2.0.

A guide for setting up application monitoring: logs record events, metrics measure values over time, traces follow requests through services, and alerts signal possible problems.

In plain words
What is it for?
Adding structured logs, Prometheus metrics, request traces, dashboards, threshold or anomaly alerts, and performance tests for important application paths.
Why use it?
It helps teams see whether software is working, investigate failures, and notice performance changes before users report them.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Adding structured logs, Prometheus metrics, request traces, dashboards, threshold or anomaly alerts, and performance tests for important application paths.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/threat-vector-security/guardian-agent/monitoring-expert
Install

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.

Any agent
npx skills add Threat-Vector-Security/guardian-agent --skill monitoring-expert
Clone the repo
git clone --depth 1 https://github.com/Threat-Vector-Security/guardian-agent

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for monitoring-expert

README.md
[![agentmods](https://agentmods.dev/badge/skills/threat-vector-security/guardian-agent/monitoring-expert.svg)](https://agentmods.dev/skills/threat-vector-security/guardian-agent/monitoring-expert)
Your own site
<a href="https://agentmods.dev/skills/threat-vector-security/guardian-agent/monitoring-expert"><img src="https://agentmods.dev/badge/skills/threat-vector-security/guardian-agent/monitoring-expert.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,281 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector warn 7 Sept 2026
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 126
    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.
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00000 $0.01281
Opus 5 $0.00000 $0.00641
Sonnet 5 $0.00000 $0.00256
Haiku 4.5 $0.00000 $0.00128

Measured 7d ago against content hash 00e96ef74a08, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

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 7d 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.

skills/monitoring-expert/SKILL.md · 162 lines

How it starts

The opening of the file, as written. The whole thing — 162 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

  1. Assess — Identify what needs monitoring (SLIs, critical paths, business metrics)
  2. Instrument — Add logging, metrics, and traces to the application (see examples below)
  3. Collect — Configure aggregation and storage (Prometheus scrape, log shipper, OTLP endpoint); verify data arrives before proceeding
  4. Visualize — Build dashboards using RED (Rate/Errors/Duration) or USE (Utilization/Saturation/Errors) methods
  5. 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();
  }
}

Read the full file on GitHub · 162 lines

Changes

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.

  1. 7d ago First seen · 162 lines · 0 tokens per session scan A 00e96ef74a08

Subscribe to this mod's changes

monitoring-expert is a skill published in the GitHub repository Threat-Vector-Security/guardian-agent (11 stars, last pushed yesterday), licensed Apache-2.0. It costs nothing until one of its globs matches a file; then it loads 1,281 tokens. 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.

Related

Other skills, from other repositories

continuum-tools-mcp

Connect MCP servers (Stdio/SSE/StreamableHTTP) to a Continuum agent, configure tool filtering, set up tool-context capture/injection (e.g. sessionid), and read run artifacts (UI widgets, structured tool data). Invoke when the user asks "connect MCP", "filesystem tool", "remote API tool", "auto-capture sessionid"…

shyftlabs/continuum · 94 tokens

continuum-handoffs

Build agent-to-agent transitions with Continuum's Handoff system — triage routing, history summarization modes (FULL/SUMMARY/RECENTN/HYBRID), cycle detection, depth tracking, return-to-parent. Invoke when the user asks "route customer requests to specialists", "agent that can transfer to another", "summarize history…

shyftlabs/continuum · 98 tokens

continuum-llm-providers

Pick the right LLM provider, configure structured outputs, control context-window compression, and use the LLMClient directly. Provider routing is by model-string prefix; LiteLLM has been removed. Also covers Smart Gateway integration for multi-provider routing. Invoke when the user asks about "switch to Claude"…

shyftlabs/continuum · 105 tokens

continuum-evaluation

Evaluate agent quality with the EvaluatorAgent, generate golden datasets from a corpus, and run DeepEval/RAGAS metrics over conversations. Invoke when the user asks "test agent quality", "evaluate output", "RAG metrics", "DeepEval", "RAGAS", or "regression-test my agent".

shyftlabs/continuum · 68 tokens

continuum-streaming

Stream tokens, tool calls, handoffs, and memory events out of a Continuum agent in real time using runner.runstream() and the EventType enum. Invoke when the user asks "stream tokens to UI", "websocket chat", "live progress", "see tool execution as it happens", or anything that needs token-by-token output.

shyftlabs/continuum · 77 tokens

continuum-temporal

Build durable agent workflows with Temporal — sequential/parallel/loop/conditional steps, human-in-the-loop approval gates, custom workflows and activities. Invoke when the user asks "long-running workflow", "approval gate", "human in the loop", "retry on failure", "workflow survives restart", or anything…

shyftlabs/continuum · 68 tokens