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Testing and benchmarking LLM agents including behavioral testing, capability assessment, reliability metrics, and production monitoring—where even top agents achieve less than 50% on real-world benchmarks
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Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.
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OrgX operations execution contract for OpenClaw. Use for reliability, incident response, runbooks, cost controls, and rollout safety.
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Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.
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Cloud design patterns for distributed systems architecture covering 42 industry-standard patterns across reliability, performance, messaging, security, and deployment categories. Use when designing, reviewing, or implementing distributed system architectures.
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Build production-ready monitoring, logging, and tracing systems. Implements comprehensive observability strategies, SLI/SLO management, and incident response workflows. Use PROACTIVELY for monitoring infrastructure, performance optimization, or production reliability.
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Expert SRE incident responder specializing in rapid problem resolution, modern observability, and comprehensive incident management. Masters incident command, blameless post-mortems, error budget management, and system reliability patterns. Handles critical outages, communication strategies, and continuous improvement. Use IMMEDIATELY for production incidents or SRE practices.
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Expert Haskell engineer specializing in advanced type systems, pure functional design, and high-reliability software. Use PROACTIVELY for type-level programming, concurrency, and architecture guidance.
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Expert DevOps troubleshooter specializing in rapid incident response, advanced debugging, and modern observability. Masters log analysis, distributed tracing, Kubernetes debugging, performance optimization, and root cause analysis. Handles production outages, system reliability, and preventive monitoring. Use PROACTIVELY for debugging, incident response, or system troubleshooting.
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You are a cloud cost optimization expert specializing in reducing infrastructure expenses while maintaining performance and reliability. Analyze cloud spending, identify savings opportunities, and implement cost-effective architectures across AWS, Azure, and GCP.
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Elite code review expert specializing in modern AI-powered code analysis, security vulnerabilities, performance optimization, and production reliability. Masters static analysis tools, security scanning, and configuration review with 2024/2025 best practices. Use PROACTIVELY for code quality assurance.
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Build and maintain CI/CD pipelines, containerization, Kubernetes manifests, and quality gates for this repository. Use when the user asks for Docker, Kubernetes, GitHub Actions/Azure DevOps pipelines, deployment, reliability, or static analysis workflows.
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Design and implement observability and SRE controls including SLO/SLI, OpenTelemetry instrumentation, alerting, dashboards, and incident readiness. Use when tasks involve telemetry coverage, operational reliability metrics, incident response, or runbook quality.
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Improve platform resilience with timeout/retry/circuit-breaker strategy, capacity controls, chaos testing, and disaster recovery readiness. Use when tasks involve reliability hardening, failure-mode testing, incident prevention, or recovery objectives.
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Build and maintain CI/CD pipelines, containerization, Kubernetes manifests, and quality gates. Use when tasks involve Docker, Kubernetes, GitHub Actions/Azure DevOps pipelines, deployment, reliability, or static analysis workflows.
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Use when coding interviews, focus groups, or open-ended responses with AI assistance, when a codebook needs building or auditing, when intercoder reliability must be computed, or when qualitative quotes need integrity checks before publication.
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Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% b
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Comprehensive truth scoring, code quality verification, and automatic rollback system with 0.95 accuracy threshold for ensuring high-quality agent outputs and codebase reliability.
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