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.
git clone --depth 1 https://github.com/HermeticOrmus/LibreUIUX-Claude-CodeWrote 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/commands/hermeticormus/libreuiux-claude-code/monitor-setup)<a href="https://agentmods.dev/commands/hermeticormus/libreuiux-claude-code/monitor-setup"><img src="https://agentmods.dev/badge/commands/hermeticormus/libreuiux-claude-code/monitor-setup/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/commands/hermeticormus/libreuiux-claude-code/monitor-setup"><img src="https://agentmods.dev/badge/commands/hermeticormus/libreuiux-claude-code/monitor-setup.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 | $0.00000 | $0.03372 |
| Opus 5.5 | $0.00000 | $0.01349 |
| Sonnet 5.5 | $0.00000 | $0.00674 |
| Haiku 4.5 | $0.00000 | $0.00337 |
Grade A, and why
monitor-setup 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 29d 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.
How it starts
The opening of the file, as written. The whole thing — 502 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Monitoring and Observability Setup
You are a monitoring and observability expert specializing in implementing comprehensive monitoring solutions. Set up metrics collection, distributed tracing, log aggregation, and create insightful dashboards that provide full visibility into system health and performance.
Context
The user needs to implement or improve monitoring and observability. Focus on the three pillars of observability (metrics, logs, traces), setting up monitoring infrastructure, creating actionable dashboards, and establishing effective alerting strategies.
Requirements
$ARGUMENTS
Instructions
1. Prometheus & Metrics Setup
Prometheus Configuration
# prometheus.yml
global:
scrape_interval: 15s
evaluation_interval: 15s
external_labels:
cluster: 'production'
region: 'us-east-1'
alerting:
alertmanagers:
- static_configs:
- targets: ['alertmanager:9093']
rule_files:
- "alerts/*.yml"
- "recording_rules/*.yml"
scrape_configs:
- job_name: 'prometheus'
static_configs:
- targets: ['localhost:9090']
- job_name: 'node'
static_configs:
- targets: ['node-exporter:9100']
- job_name: 'application'
kubernetes_sd_configs:
- role: pod
relabel_configs:
- source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
action: keep
regex: true
Custom Metrics Implementation
// metrics.ts
import { Counter, Histogram, Gauge, Registry } from 'prom-client';
export class MetricsCollector {
private registry: Registry;
private httpRequestDuration: Histogram<string>;
private httpRequestTotal: Counter<string>;
constructor() {
this.registry = new Registry();
this.initializeMetrics();
}
private initializeMetrics() {
this.httpRequestDuration = new Histogram({
name: 'http_request_duration_seconds',
help: 'Duration of HTTP requests in seconds',
labelNames: ['method', 'route', 'status_code'],
buckets: [0.001, 0.005, 0.01, 0.05, 0.1, 0.5, 1, 2, 5]
});
this.httpRequestTotal = new Counter({
name: 'http_requests_total',
help: 'Total number of HTTP requests',
labelNames: ['method', 'route', 'status_code']
});
this.registry.registerMetric(this.httpRequestDuration);
this.registry.registerMetric(this.httpRequestTotal);
}
httpMetricsMiddleware() {
return (req: Request, res: Response, next: NextFunction) => {
const start = Date.now();
const route = req.route?.path || req.path;
res.on('finish', () => {
const duration = (Date.now() - start) / 1000;
const labels = {
method: req.method,
route,
status_code: res.statusCode.toString()
};
this.httpRequestDuration.observe(labels, duration);
this.httpRequestTotal.inc(labels);
});
next();
};
}
async getMetrics(): Promise<string> {
return this.registry.metrics();
}
}
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.
- 29d ago First seen · 502 lines · 0 tokens per session scan A 9e37ee616aa8
monitor-setup is a command published in the GitHub repository HermeticOrmus/LibreUIUX-Claude-Code (115 stars, last pushed 14d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 3,372 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 2026-09-20.
Other commands, from other repositories
dare-llm-integration
Integração segura e eficiente com LLMs (Gemini, Claude, OpenAI, Ollama) em projetos DARE.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.