Observability skills

This skill helps you implement Spring Boot patterns for scalable REST APIs, layering, caching, async, and logging in Java backend services.

This skill helps you gather basic system information and directory listings using simple Python scripts.

This skill automates Openweather API tasks via Composio Rube MCP, enabling tool discovery, connection management, and workflow execution.

This skill helps maintain service reliability through monitoring, incident response, and automation, enabling efficient IT operations and continuous

This skill analyzes the past day's GitHub Actions workflow runs to detect actionable failures and open issues for remediation.

This skill guides you to instrument a web app with Azure App Insights for comprehensive telemetry and improved observability.

This skill analyzes Azure resource groups and generates detailed Mermaid diagrams showing resource relationships to help you understand architecture quickly.

This skill helps you debug tursodb by guiding bytecode comparison, logging, threading sanitizer, deterministic simulation, and corruption analysis.

This skill models agent beliefs, desires, and intentions from RDF context, enabling explainable BDI reasoning and coherent multi-agent coordination.

This skill helps you stream real-time cryptocurrency data from 40+ exchanges using cryptofeed, normalizing feeds for backends and algorithmic trading.

This skill explains how the Personal AI Infrastructure operates, details system configuration, security, workflows, and how to use the PAI at session start.

This skill guides unified setup, diagnostics, and MCP configuration for Claude Code orchestration, streamlining installation and environment readiness.

This skill helps configure and optimize the HUD display in Claude Code to reflect status, presets, and elements for your workflow.

This skill displays the agent flow trace timeline and summary, helping you diagnose interactions among hooks, keywords, skills, agents, and tools.

This skill inspects Sentry issues and events, summarizes recent production errors, and fetches health data via the Sentry API using a read-only token.

This skill helps you instrument LLM workflows with OpenInference tracing in Phoenix, enabling custom spans, production readiness, and trace analysis.

This skill helps you debug LLM applications with the Phoenix CLI by fetching traces, identifying errors, and analyzing performance.

This skill helps you design immersive game audio systems and adaptive music workflows that enhance player immersion and feedback.

This skill helps you accelerate RL-based LLM post-training with slime's Megatron-LM and SGLang for scalable data generation and rollout.

This skill helps you integrate PyTorch FSDP2 into training scripts with correct initialization, sharding, mixed precision, and DTensor-based checkpointing.

This skill enforces runtime safety for LLMs with configurable jailbreaking, toxicity, PII, and fact-checking rails to improve reliability.