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AI System Observability & SRE

About AI System Observability & SRE

This domain provides skills to ensure the stability and efficiency of AI systems, backend services, and general IT infrastructure. It covers performance bottleneck diagnosis, website loading optimization, system monitoring, log analysis, and distributed tracing for comprehensive observability. Furthermore, it includes troubleshooting and debugging for Linux systems, microservice architectures, and AI applications like LLMs, alongside core SRE practices such as SLO implementation and resilience design. These skills are essential for SRE engineers, DevOps specialists, backend developers, and IT administrators to quickly identify and resolve system issues, enhancing overall reliability and user experience.

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All AI System Observability & SRE Skills

50 / 148 skills
azure-monitor

azure-diagnostics

by @microsoft

Provides diagnostic support for applications and infrastructure in the Azure cloud environment, helping users identify, analyze, and resolve performance issues and failures, ensuring stable system operation.

4.8(2.0K)
296.6K
azure-application-insights

appinsights-instrumentation

by @microsoft

Focuses on integrating Azure Application Insights for applications, enabling performance monitoring, fault diagnosis, and user behavior analysis to comprehensively improve application quality and user experience.

4.8(2.0K)
141.9K
azure-data-explorer

azure-kusto

by @microsoft

Focuses on large-scale data analysis using Azure Kusto Query Language (KQL), quickly querying and gaining insights from logs and telemetry data, supporting real-time monitoring and troubleshooting.

4.8(2.0K)
141.8K
debugging

diagnose

by @mattpocock

This skill provides a rigorous diagnostic loop methodology for tackling hard bugs and performance regressions. It emphasizes building fast feedback loops, systematically identifying and resolving issues through reproduction, minimization, hypothesis, instrumentation, fixing, and regression testing, ensuring stable and efficient system operation.

4.8(120)
121.7K
azure-monitor

azure-observability

by @microsoft

GitHub Copilot designed for the Azure cloud platform, aimed at enhancing Azure infrastructure observability, helping developers more intelligently monitor and manage cloud resources.

4.7(2.0K)
98.1K
performance-mode

overdrive

by @pbakaus

Enter "Overdrive mode" to accelerate task execution and response speed, improving work efficiency for scenarios requiring rapid task completion.

4.7(1.1K)
63.0K
convex-performance

convex-performance-audit

by @get-convex

Diagnose and resolve performance issues in Convex applications, optimizing database queries and operations to improve system response speed and efficiency.

4.7(604)
51.5K
stats

caveman-stats

by @juliusbrussee

This skill provides immediate access to formatted statistics, allowing users to instantly view their AI usage. It requires no additional model processing, directly presenting key figures to help users quickly understand and analyze AI interaction patterns.

4.7(120)
48.5K
it-administration

persona-it-admin

by @googleworkspace

IT Administrator, responsible for managing information technology systems, monitoring network security, configuring and maintaining enterprise applications like Google Workspace, and ensuring stable operation of IT infrastructure.

4.5(144)
14.5K
web-performance-optimization

performance

by @addyosmani

Optimize website performance for faster loading speeds and better user experience, addressing slow loading issues.

4.5(177)
13.1K
latency-reduction

performance-optimization

by @supercent-io

This skill aims to resolve performance issues such as slow page loading, rendering delays, excessive bundle size, high resource consumption, and database bottlenecks, optimizing system response speed and efficiency.

4.5(458)
11.5K
prometheus

monitoring-observability

by @supercent-io

This skill is used for monitoring and observability, including system setup before production deployment, performance issue identification, incident resolution, capacity planning, and security audits, ensuring stable system operation.

4.5(440)
11.0K
debuggers

debugging

by @supercent-io

This skill is used for debugging, resolving runtime errors, unexpected output, performance degradation, intermittent or hard-to-reproduce bugs, helping developers quickly pinpoint and fix issues.

4.5(433)
10.8K
debian-linux

debian-linux-triage

by @github

Diagnose and resolve Debian Linux issues, providing guidance related to apt, systemd, and AppArmor.

4.5(292)
8.6K
arch-linux

arch-linux-triage

by @github

Diagnose and resolve Arch Linux issues, providing best practice guidance for pacman, systemd, and rolling releases.

4.5(290)
8.6K
observability

google-agents-cli-observability

by @google

Configure ADK Agent observability, integrating Cloud Trace, logging, and BigQuery analysis to monitor production environment performance.

4.5(25)
8.6K
github-copilot-analytics

copilot-usage-metrics

by @github

Retrieve and display GitHub Copilot usage metrics for organizations and enterprises using GitHub CLI and REST API.

4.5(291)
8.5K
fedora-linux

fedora-linux-triage

by @github

Triage and resolve Fedora Linux system issues using dnf, systemd, and SELinux-aware guidance.

4.5(289)
8.4K
centos-linux

centos-linux-triage

by @github

Triage and resolve CentOS Linux system issues using RHEL-compatible tools, SELinux-aware practices, and firewalld.

4.5(289)
8.4K
llm-monitoring

llm-monitoring-dashboard

by @supercent-io

This skill uses Tokuin CLI to track LLM API costs, tokens, and latency, and automatically generates data-driven management dashboards, providing project management insights.

4.5(274)
6.8K
python

python-observability

by @wshobson

Focuses on observability for Python backend systems, offering intelligent automation and multi-agent orchestration capabilities to help developers monitor, debug, and optimize application performance.

4.5(74)
6.6K
python

python-resilience

by @wshobson

Specializes in the resilient design and implementation of Python backend systems, ensuring applications remain stable and reliable even when facing failures.

4.5(95)
6.4K
service-mesh

service-mesh-observability

by @wshobson

Focuses on service mesh observability, combining intelligent automation and multi-agent orchestration to gain deep insights into microservice architecture operational status and quickly pinpoint issues.

4.4(55)
6.3K
slo-(service-level-objectives)

slo-implementation

by @wshobson

Master the implementation of Service Level Objectives (SLO), ensuring system reliability and meeting user expectations through intelligent automation and multi-agent orchestration.

4.4(69)
6.3K
debugging

insforge-debug

by @insforge

Diagnose InsForge project issues, from frontend SDK errors to backend infrastructure failures, running commands to locate problems and output logs.

4.4(20)
6.1K
debugging

parallel-debugging

by @wshobson

Focuses on DevOps parallel debugging, efficiently identifying and resolving complex system issues using intelligent automation and multi-agent orchestration, improving development efficiency.

4.4(20)
5.7K
ai-audit

health

by @tw93

Runs a budget-aware audit of the Claude Code config stack when Claude ignores instructions, behaves inconsistently, hooks malfunction, MCP servers need auditing, or users ask why /health used many tokens. Flags issues by severity. Not for debugging code or reviewing PRs.

4.4(120)
5.3K
audit-log

okx-audit-log

by @okx

Provides structured audit log file paths, supporting developers in offline troubleshooting of Agent runtime issues, stored in JSON Lines format.

4.4(20)
4.1K
agent-monitoring

openclaw-control-center

by @aradotso

Transforms OpenClaw from a black box into a locally auditable control center, comprehensively monitoring Agent activities, token consumption, and cross-session collaboration.

4.4(62)
4.0K
ai-agent-operations

enterprise-agent-ops

by @affaan-m

Manages and operates long-running AI agent workloads, ensuring their observability, security, and reliability for enterprise-grade AI applications.

4.4(20)
3.8K
alerting

alert-manager

by @aaron-he-zhu

Focuses on providing SEO and geolocation-related alert management for AI coding tools like Claude Code, Cursor, and Codex, ensuring performance monitoring and timely issue detection.

4.4(41)
3.5K
n8n

n8n-validation-expert

by @czlonkowski

Helps users interpret n8n validation errors and provides detailed repair guides, ensuring smooth workflow operation and reduced downtime.

4.4(48)
3.4K
debugging

debugging-and-error-recovery

by @addyosmani

Systematic debugging and structured triage, preserving evidence and following checklists to find root causes, avoiding time wasted on guesswork.

4.4(20)
3.4K
logging

logging-best-practices

by @boristane

Focuses on logging best practices for wide events (canonical log lines) to enable powerful analysis.

4.4(62)
3.2K
golang

golang-error-handling

by @samber

Go reliability engineer persona: every error must be handled or passed with context; silent failures and duplicate logs are equally unacceptable.

4.4(20)
3.2K
monitoring

canary-watch

by @affaan-m

Continuously monitor Web application health after deployment, automatically detecting performance anomalies, error rates, and functional degradation, supporting alert notifications and root cause analysis.

4.4(20)
2.9K
debugging

golang-troubleshooting

by @samber

Systematically troubleshoot Go application failures, locating root causes through logs, tracing, and performance analysis, avoiding guesswork and trial-and-error.

4.4(20)
2.8K
observability

golang-observability

by @samber

Automatically integrate OpenTelemetry metrics, tracing, and structured logs for Go services, establishing observability at the code level for diagnosable production issues.

4.4(26)
2.8K
monitoring

monitoring-expert

by @jeffallan

Configures monitoring systems and implements structured logging to ensure stable system operation and rapid fault localization.

4.4(37)
2.6K
adk

adk-observability-guide

by @google

A guide that must be read before setting up observability for ADK agents. Covers configuration and practices for logs, metrics, and tracing, ensuring transparent system status for monitoring and troubleshooting.

4.4(20)
2.6K
incident-response

incident-response

by @anthropics

Manage the full incident lifecycle, from detection to response and post-mortem, establishing standardized emergency handling procedures.

4.4(48)
2.6K
ai-engineering

agent-introspection-debugging

by @affaan-m

Agent introspection debugging workflow, systematically self-diagnosing when an agent repeatedly fails, consumes tokens without progress, or cyclically calls the same tool.

4.4(3)
2.6K
error-handling

golang-samber-oops

by @samber

Use samber/oops to convert Go errors into structured data with context, making error messages self-explanatory and simplifying online problem diagnosis.

4.3(20)
2.5K
logging

golang-samber-slog

by @samber

Go structured logging architecture design, automatically configuring sampling, sensitive information anonymization, and routing distribution. Error logs sent to Sentry, info logs stored in Loki.

4.3(34)
2.5K
security

ecc-tools-cost-audit

by @affaan-m

Automatically detect anomalous usage patterns of the ECC Tools GitHub App, preventing cost overruns and privilege abuse, and identifying out-of-limit requests.

4.3(9)
2.5K
monitoring

unified-notifications-ops

by @affaan-m

Integrate dispersed notification channels into a unified operations platform, providing clear incident prioritization and response processes.

4.3(9)
2.5K
site-reliability-engineering

sre-engineer

by @jeffallan

Focus on SRE (Site Reliability Engineering) practices, defining Service Level Objectives (SLO) and error budget strategies.

4.3(37)
2.4K
xcode

xcode-build-benchmark

by @avdlee

This open-source AI Agent skill focuses on Xcode build performance optimization. It benchmarks and analyzes Xcode projects for clean builds, incremental builds, compile hotspots, project settings, and Swift Package Manager overhead. By identifying "easy wins" in build settings, script phases, and compiler flags, it generates an optimization plan and can automatically apply approved changes, significantly boosting development efficiency.

4.3(20)
2.1K
langchain

langsmith-fetch

by @ComposioHQ

Fetches execution traces from LangSmith Studio to debug LangChain and LangGraph agents, analyzing behavior and errors.

4.3(30)
2.0K
langsmith

langsmith-trace

by @langchain-ai

Configures LangSmith tracing for AI/ML projects, requiring an API key and supporting project and workspace IDs.

4.3(45)
2.0K