improve-agent
FreeSystematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.
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2.7K skills · sorted by relevance
Systematic improvement of existing agents through performance analysis, prompt engineering, and continuous iteration.
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Expert Kubernetes architect specializing in cloud-native infrastructure, advanced GitOps workflows (ArgoCD/Flux), and enterprise container orchestration. Masters EKS/AKS/GKE, service mesh (Istio/Linkerd), progressive delivery, multi-tenancy, and platform engineering. Handles security, observability, cost optimization, and developer experience. Use PROACTIVELY for K8s architecture, GitOps implementation, or cloud-native platform design.
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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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Build comprehensive ML pipelines, experiment tracking, and model registries with MLflow, Kubeflow, and modern MLOps tools. Implements automated training, deployment, and monitoring across cloud platforms. Use PROACTIVELY for ML infrastructure, experiment management, or pipeline automation.
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Expert firmware analyst specializing in embedded systems, IoT security, and hardware reverse engineering. Masters firmware extraction, analysis, and vulnerability research for routers, IoT devices, automotive systems, and industrial controllers. Use PROACTIVELY for firmware security audits, IoT penetration testing, or embedded systems research.
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Build scalable data pipelines, modern data warehouses, and real-time streaming architectures. Implements Apache Spark, dbt, Airflow, and cloud-native data platforms. Use PROACTIVELY for data pipeline design, analytics infrastructure, or modern data stack implementation.
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Build production-ready LLM applications, advanced RAG systems, and intelligent agents. Implements vector search, multimodal AI, agent orchestration, and enterprise AI integrations. Use PROACTIVELY for LLM features, chatbots, AI agents, or AI-powered applications.
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Elite AI context engineering specialist mastering dynamic context management, vector databases, knowledge graphs, and intelligent memory systems. Orchestrates context across multi-agent workflows, enterprise AI systems, and long-running projects with 2024/2025 best practices. Use PROACTIVELY for complex AI orchestration.
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Senior embedded software engineer specializing in firmware and driver development for ARM Cortex-M microcontrollers (Teensy, STM32, nRF52, SAMD). Decades of experience writing reliable, optimized, and maintainable embedded code with deep expertise in memory barriers, DMA/cache coherency, interrupt-driven I/O, and peripheral drivers.
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Base implementation skill for this repository across .NET/C#, backend APIs, database/ORM, frontend Vue/Quasar, and Rust with Clean Architecture rules. Use when the user asks to build features, fix bugs, refactor modules, or improve code-level performance, and use specialized skills as inheritance layers when available.
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Base implementation skill. Use for code changes, bug fixes, refactors, and script work across .NET/C#, backend APIs, database/ORM, Vue/Quasar frontend, Rust, PowerShell, Docker, K8s, CI/CD, security, observability, and SRE domains. Specialized skills extend this as a base.
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Build and harden high-performance APIs with strong security controls, endpoint budgets, rate limiting, and resilience patterns. Use when tasks involve API latency/throughput tuning, abuse resistance, authz hardening, or API release gates.
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Audit and remediate dependency/package vulnerabilities across .NET backend, frontend (npm/pnpm/yarn), and Rust projects with severity-based quality gates. Use when the user asks for SCA checks, dependency hardening, or release security gates.
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Close out a completed workstream by updating README artifacts when needed, producing a commit message, and applying changelog-ready content when the work is ready for commit. Use after review when a stable checkpoint is ready.
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Design, implement, and stabilize automated tests (unit, integration, E2E) for .NET/C#, Rust, APIs, and frontend flows. Use when the user asks to create tests, increase coverage, fix flaky tests, or validate behavior changes.
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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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Create safe, deterministic git worktrees for large or risky workstreams. Use when tasks are complex enough to warrant isolation from the main working tree.
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Mandatory final risk-focused review for any repository change. Checks security, architecture boundaries, test coverage, and release readiness before closeout.
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Close out a completed workstream by updating README artifacts when needed, producing a commit message, and applying changelog-ready content when the work is ready for commit. Use after review when a stable checkpoint is reached.
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Design and enforce privacy and data protection controls across application, API, and database layers. Use when tasks involve PII handling, retention/deletion policies, consent, data minimization, auditability, or compliance-oriented architecture changes.
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Perform repository-aware code reviews focused on bugs, regressions, architectural violations, missing tests, and operational risks. Use when the user asks for review of diffs, pull requests, patches, or implementation quality.
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Create safe, deterministic git worktrees for large or risky workstreams using the repository-owned runtime helper and Windows-safe defaults.
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Audit and remediate dependency/package vulnerabilities across .NET backend, frontend (npm/pnpm/yarn), and Rust projects with severity-based quality gates. Use when the user asks for SCA checks, dependency hardening, or release security gates before build/package.
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Design, implement, and stabilize automated tests in this repository (unit, integration, and E2E) for .NET/C#, Rust, APIs, and frontend flows. Use when the user asks to create tests, increase coverage, fix flaky tests, or validate behavior changes.
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