Skill UI

A comprehensive workflow bundle covering the entire cloud-native development lifecycle. It guides users through critical phases, including cloud infrastructure setup (AWS, Azure, GCP, Terraform IaC), container orchestration with Kubernetes, robust CI/CD pipeline automation, observability implementation, security hardening, cost optimization, and disaster recovery planning. This ensures best practices across all stages of modern application deployment.

An expert guide for designing, implementing, and optimizing large-scale, secure, and highly available cloud-native infrastructure using Kubernetes. Covers advanced topics including GitOps workflows (ArgoCD/Flux), service mesh architecture (Istio), multi-cluster management, Policy as Code (OPA), and infrastructure automation with Terraform. Ideal for platform engineers building enterprise-grade container orchestration solutions.

Submit and manage autonomous lab protocols on Ginkgo Cloud Lab, leveraging RACs for cell-free protein expression validation/optimization, fluorescent pixel art, EstiMate AI assessments, and guided ordering of sample inputs through the web interface.

This skill guides the comprehensive evaluation and selection of Threat Intelligence Platforms (TIPs). It assesses vendor capabilities, including STIX/TAXII support, workflow automation, SIEM/SOAR integration, and total cost of ownership. It is essential for procurement decisions, migrating between TIP solutions, or assessing whether the current CTI program meets required maturity levels.

This guide details the design and implementation of security zones and conduits for Industrial Automation and Control Systems (IACS) following the stringent standards of IEC 62443-3-2. It enables risk-based network partitioning, assigning Security Level Targets (SL-T), and enforcing granular conduit controls. Use this when retrofitting flat OT networks or designing greenfield facilities to achieve IEC 62443 compliance, validating boundaries against the Purdue Reference Model.

This skill guides the implementation of Security Orchestration, Automation, and Response (SOAR) workflows using platforms like Splunk Phantom. It automates the entire incident lifecycle, including alert triage, IOC enrichment (via VirusTotal, CrowdStrike), containment actions, and ticket creation (ServiceNow). Ideal for SOC teams needing to reduce Mean Time To Respond (MTTR) and standardize complex security procedures across multiple tools.

This guide provides methods for robust monitoring and automation tailored for services deployed on Fly.io. It covers key areas including polling the Machines API to detect state changes, implementing comprehensive health check endpoints, processing structured logs using tools like `jq`, and automating deployment notifications within CI/CD pipelines. Essential for achieving high availability and reliable operations.

This comprehensive checklist guides the safe and reliable deployment of Hootsuite integrations and social media automation tools into a live production environment. It covers critical areas such as API key management, rate limit handling, implementing circuit breakers, error resilience (retries, timezones), and establishing robust monitoring alerts. Use this before any major launch or system upgrade to ensure continuous, fail-safe content publishing.

Provides comprehensive guidelines for authors submitting papers to Acta Automatica Sinica (AAS). It details how to organize and present anonymous, reproducible code, data, and experimental artifacts to enhance the credibility and rigor of research in control, automation, and pattern recognition, supporting the double-blind review process.

This skill guides researchers to determine if their topic fits the scope of Acta Automatica Sinica (AAS). It provides detailed boundaries for control theory, pattern recognition, robotics, and smart systems, helping authors distinguish their contribution from pure algorithms or system software, and advising on appropriate article type (Review/Paper/Short) to avoid initial rejection.

Provides guidelines for creating robust, verifiable, and reusable Electronic Design Automation (EDA) artifacts for submission to academic conferences like DAC. The focus shifts from chasing conference badges to ensuring community trust and scientific reproducibility. Key elements include pinning the toolchain, using standard benchmarks, providing clear setup instructions, and archiving the release in a DOI-issuing repository.

This guide provides a comprehensive checklist for evaluating Electronic Design Automation (EDA) research manuscripts for top-tier conferences like DAC. It emphasizes the necessity of using standard, recognized benchmark suites (e.g., ISPD, EPFL, TAU), comparing results against the true State-of-the-Art (SOTA), reporting full PPA metrics and runtime, and implementing ablation studies to ensure fairness, reproducibility, and generalizability, especially for ML-based methods.