k8s-troubleshooter
Systematic Kubernetes troubleshooting, pod diagnostics, cluster health monitoring, and incident response playbooks.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
145 skills found
Systematic Kubernetes troubleshooting, pod diagnostics, cluster health monitoring, and incident response playbooks.
Troubleshoot and manage the GCP e2-micro VM running the eth-realtime-collector. Handle systemd failures, network connectivity issues, and real-time data stream monitoring for Ethereum network data.
Identify, categorize, and troubleshoot flaky tests by analyzing CI history, execution patterns, and code structure to improve test suite reliability.
Analyze AppWorld task failures to extract specific API patterns and generate actionable playbook bullets with concrete code examples.
Implement the 'Engineering as Marketing' growth strategy: build free SEO-driven utility tools to drive organic traffic, capture leads, and convert visitors into customers without ad spend.
Build production-grade AI agents using LangGraph, Anthropic/OpenAI/vLLM, and structured outputs. Features streaming, A2A protocol, Pydantic validation, vector memory, and guardrails for resilient, multi-agent workflows.
Implement robust backend error handling with custom classes, middleware, structured logging, and recovery patterns.
Autonomous multi-agent orchestration framework for Claude Code with memory-driven workflows, parallel-first task execution, Aristotle-based deconstruction, and multi-stage quality gates.
Framework for automated n8n integration testing including API contract validation, authentication flows, rate limit handling, and error scenario coverage.
World-class senior data engineering skill for building scalable data pipelines, ETL/ELT systems, and modern data infrastructure using Python, Spark, dbt, and Kafka.
NestJS 11+ expert assistant for enterprise Node.js development, including dependency injection, DTO validation, authentication, ORMs, testing, microservices, and architectural best practices.
Validate test suite effectiveness and uncover weak assertions by introducing code mutations and measuring kill rates. Essential for proving tests genuinely catch bugs rather than just satisfying coverage metrics.