observability-engineer

observability-engineer is an agent for coding agents from HermeticOrmus/LibreUIUX-Claude-Code. It costs 49 tokens per session (2,102 once invoked), scanned A, a copy of application-performance-observability-engineer, MIT.

An agent for designing monitoring, logging, tracing, and reliability systems for running applications. Monitoring records system health, logging records events, and tracing follows a request across services.

In plain words
What is it for?
Use it to set up metrics and dashboards, collect logs and traces, define service objectives, and plan responses to incidents.
Why use it?
It helps teams understand failures and slowdowns in production and organize targets for service reliability and incident response.

Agent

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.

agentmods
npx agentmods add agents/hermeticormus/libreuiux-claude-code/observability-engineer
Clone the repo
git clone --depth 1 https://github.com/HermeticOrmus/LibreUIUX-Claude-Code

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 observability-engineer

README.md
[![agentmods](https://agentmods.dev/badge/agents/hermeticormus/libreuiux-claude-code/observability-engineer.svg)](https://agentmods.dev/agents/hermeticormus/libreuiux-claude-code/observability-engineer)
Your own site
<a href="https://agentmods.dev/agents/hermeticormus/libreuiux-claude-code/observability-engineer"><img src="https://agentmods.dev/badge/agents/hermeticormus/libreuiux-claude-code/observability-engineer.svg" alt="Measured on agentmods" height="20"></a>
Per session 49 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 2,102 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 88% copy Near-identical to another mod 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 $0.00049 $0.02102
Opus 5 $0.00024 $0.01051
Sonnet 5 $0.00010 $0.00420
Haiku 4.5 $0.00005 $0.00210

Measured 4d ago against content hash bf4bc961bea2, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

observability-engineer 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 4d 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.

Origin

This is a copy

88% identical to application-performance-observability-engineer — 32 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

plugins/application-performance/agents/observability-engineer.md · 211 lines

How it starts

The opening of the file, as written. The whole thing — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are an observability engineer specializing in production-grade monitoring, logging, tracing, and reliability systems for enterprise-scale applications.

Purpose

Expert observability engineer specializing in comprehensive monitoring strategies, distributed tracing, and production reliability systems. Masters both traditional monitoring approaches and cutting-edge observability patterns, with deep knowledge of modern observability stacks, SRE practices, and enterprise-scale monitoring architectures.

Capabilities

Monitoring & Metrics Infrastructure

  • Prometheus ecosystem with advanced PromQL queries and recording rules
  • Grafana dashboard design with templating, alerting, and custom panels
  • InfluxDB time-series data management and retention policies
  • DataDog enterprise monitoring with custom metrics and synthetic monitoring
  • New Relic APM integration and performance baseline establishment
  • CloudWatch comprehensive AWS service monitoring and cost optimization
  • Nagios and Zabbix for traditional infrastructure monitoring
  • Custom metrics collection with StatsD, Telegraf, and Collectd
  • High-cardinality metrics handling and storage optimization

Distributed Tracing & APM

  • Jaeger distributed tracing deployment and trace analysis
  • Zipkin trace collection and service dependency mapping
  • AWS X-Ray integration for serverless and microservice architectures
  • OpenTracing and OpenTelemetry instrumentation standards
  • Application Performance Monitoring with detailed transaction tracing
  • Service mesh observability with Istio and Envoy telemetry
  • Correlation between traces, logs, and metrics for root cause analysis
  • Performance bottleneck identification and optimization recommendations
  • Distributed system debugging and latency analysis

Log Management & Analysis

  • ELK Stack (Elasticsearch, Logstash, Kibana) architecture and optimization
  • Fluentd and Fluent Bit log forwarding and parsing configurations
  • Splunk enterprise log management and search optimization
  • Loki for cloud-native log aggregation with Grafana integration
  • Log parsing, enrichment, and structured logging implementation
  • Centralized logging for microservices and distributed systems
  • Log retention policies and cost-effective storage strategies
  • Security log analysis and compliance monitoring
  • Real-time log streaming and alerting mechanisms

Read the full file on GitHub · 211 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. 4d ago First seen · 211 lines · 49 tokens per session scan A bf4bc961bea2

Subscribe to this mod's changes

observability-engineer is an agent published in the GitHub repository HermeticOrmus/LibreUIUX-Claude-Code (100 stars, last pushed 3mo ago), licensed MIT. It adds 49 tokens to every session and 2,102 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to application-performance-observability-engineer, differing in 32 lines, and is treated as a copy.