480건 · 관련도순
Botnet architecture taxonomy, detection techniques, and defensive analysis. Covers C2 topologies, DGA analysis, fast-flux detection, P2P overlay mapping, blockchain C2, and ML-based traffic fingerprinting. Defensive research for understanding and countering distributed malicious infrastructure.
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Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.
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Attiya-Bar-Noy-Dolev atomic register emulation over message-passing. Load when designing quorum-based distributed storage, proving linearizability, or reasoning about fault-tolerant shared memory.
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ABD quorum-based linearizable registers for distributed storage — the canonical crash-tolerant read/write protocol with precise RTT and message complexity.
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Write integration tests using .NET Aspire's testing facilities with xUnit. Covers test fixtures, distributed application setup, endpoint discovery, and patterns for testing ASP.NET Core apps with real dependencies.
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Design stable, compatible public APIs using extend-only design principles. Manage API compatibility, wire compatibility, and versioning for NuGet packages and distributed systems.
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Critical Akka.NET best practices including EventStream vs DistributedPubSub, supervision strategies, error handling, Props vs DependencyResolver, work distribution patterns, and cluster/local mode abstractions for testability.
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Expert error coordinator specializing in distributed error handling, failure recovery, and system resilience. Masters error correlation, cascade prevention, and automated recovery strategies across multi-agent systems with focus on minimizing impact and learning from failures.
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Deploys custom Apify Actors via the Apify API v2 for large-scale web crawling using CrawleeJS. Leverages Apify dataset storage, RequestQueue, and proxy configuration for distributed scraping at scale.
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CTO-level architectural advisor for AI-native development. Use this skill whenever you encounter code design decisions, architecture discussions, system resilience questions, or any work touching: "architecture", "design", "scale", "dependencies", "state", "failure", "blast radius", "refactor", "migrate", "optimize", "resilience", "consistency", "observability", "bottleneck", "coupling", "monolith", "microservices", "distributed", "concurrency", "data flow", "system design", or any prompt suggesting code-first thinking when design-first thinking is needed. This skill integrates with Claude Code to review generated code for architectural soundness, define design systems via design.md, and guide teams toward CTO-level thinking. Trigger aggressively on architectural questions—this is where AI adds the most leverage.
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Orchestrate end-to-end machine learning pipelines using Prefect or Airflow with DAG construction, task dependencies, retry logic, scheduling, monitoring, and integration with MLflow, DVC, and feature stores for production ML workflows. Use when automating multi-step ML workflows from data ingestion to deployment, scheduling periodic model retraining, coordinating distributed training tasks, or managing retry logic and failure recovery across pipeline stages.
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Apply ant colony optimization and foraging theory to resource search, exploration-exploitation tradeoffs, and distributed discovery. Covers scout deployment, trail reinforcement, diminishing returns detection, and adaptive foraging strategy selection. Use when searching a large solution space where brute-force enumeration is impractical, balancing investment between exploring new approaches and deepening known good ones, optimizing resource allocation across uncertain opportunities, or diagnosing premature convergence on local optima.
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Implement layered collective defense using alarm signaling, role mobilization, and proportional response. Covers threat detection, alert propagation, immune response patterns, escalation tiers, and post-incident recovery for distributed systems and organizations. Use when designing defense-in-depth where no single guardian covers all threats, building incident response that scales with severity, or when current defense is over-reactive to every alert or under-reactive to genuine threats.
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Unify metrics, logs, and traces for cohesive debugging. Implement exemplars for log-to-trace linking, build unified dashboards using RED/USE methods, and enable rapid root cause analysis across observability signals. Use when investigating complex incidents spanning multiple systems, reducing mean time to resolution, implementing distributed tracing, or moving from siloed tools to a unified observability platform.
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Applies general coding standards and best practices for Kafka development with Scala.
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Guide for testing code built on Simba 5 (leader election and distributed locks). Use when writing or reviewing tests for LeadershipListener callbacks, runWhileLeader / schedule work, partition groups, locks, @SimbaScheduled / @SimbaPartitioned beans, fencing-token resources (FencingSpec), LeaseBackend implementations (LeaseBackendSpec), or deterministic failover tests with InMemoryLeaseBackend and VirtualScheduler.
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Use when the user asks about NixOS, Nix language, flakes, nixpkgs, configuration.nix, nixos-rebuild, modules, options, overlays, derivations, mkDerivation, callPackage, home-manager, nix-darwin, devenv, packaging, cross-compilation, binary caches, garbage collection, NixOS containers, networking, firewall, systemd services, filesystems, LUKS, Wayland, X11, kernel, profiles, NixOS testing or VM tests, ISO images, Docker images, Raspberry Pi, Terraform, distributed builds, remote machines, pinning nixpkgs, rollback, generations, Nix Pills, or any topic related to configuring, packaging, deploying, or troubleshooting NixOS and the Nix ecosystem.
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Build or review distributed .NET applications with Orleans grains, silos, persistence, streaming, reminders, placement, transactions, serialization, event sourcing, testing, and cloud-native hosting.
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Use ManagedCode.Orleans.SignalR when a distributed .NET application needs Orleans-based coordination of SignalR real-time messaging, hub delivery, and grain-driven push flows.
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Integrate ManagedCode.Orleans.Graph into an Orleans-based .NET application for graph-oriented relationships, edge management, and traversal logic on top of Orleans grains. Use when the application models graph structures in a distributed Orleans system.
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Jaeger provider for obz. Covers trace search, trace retrieval by ID, and extension commands for service and operation discovery. This skill should be used when the user mentions "Jaeger", "obz trace -p jg", or needs to search distributed traces from a Jaeger backend.
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VictoriaTraces provider for obz. Covers trace search, trace retrieval by ID, and extension commands for service and operation discovery via the Jaeger-compatible HTTP API. This skill should be used when the user mentions "VictoriaTraces", "obz trace -p vt", or needs to search distributed traces from a VT backend.
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Use when coordinating multiple specialized agents for complex distributed tasks. Keywords: multi-agent, orchestrator, subagent, handoff, swarm, supervisor, agent topology, coordination.
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Expert error coordinator specializing in distributed error handling, failure recovery, and system resilience. Masters error correlation, cascade prevention, and automated recovery strategies across multi-agent systems with focus on minimizing impact and learning from failures.
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