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Audit container images, Dockerfiles, and Kubernetes manifests for misconfigurations, excessive privileges, exposed secrets, and runtime risks. Use when the user mentions 'container security,' 'Docker security,' 'Dockerfile audit,' 'Kubernetes security,' 'K8s security,' 'pod security,' 'container hardening,' 'kubectl audit,' 'image scanning,' 'distroless,' 'rootless containers,' 'pod security policy,' 'pod security standards,' 'PSS,' 'network policy,' 'OPA Gatekeeper,' 'Kyverno,' 'runtime security,' or needs to review container or orchestration security.

日本語の概要は準備中です。原文の説明を表示しています。

Configure Claude Code sandbox network isolation with trusted domains, custom access policies, and environment variables

日本語の概要は準備中です。原文の説明を表示しています。

Create production-ready Kubernetes manifests for Deployments, Services, ConfigMaps, and Secrets following best practices and security standards. Use when generating Kubernetes YAML manifests, creating K8s resources, or implementing production-grade Kubernetes configurations.

日本語の概要は準備中です。原文の説明を表示しています。

Use when attacking a network or moving laterally — L2/L3 poisoning (LLMNR/mDNS, ARP/DHCP, mitm6), coercion + NTLM relay (CVE-2025-33073), TUN pivoting (Ligolo-ng/Chisel), MitM, network-service RCE (CVE-2024-38077), WPA2/WPA3 wireless

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Build, read, validate, modify SBML biological network models via the libSBML Python API. SBML Levels 1–3, reactions/kinetic laws, species, rules, FBC extension for flux balance, conversion. Interoperates with COBRApy, Tellurium/RoadRunner, COPASI. Use when programmatically constructing ODE or constraint-based metabolic/signaling models in SBML.

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Security hardening and best practices for robotic systems, covering SROS2 DDS security, network segmentation, secrets management, secure boot, and the physical-cyber safety intersection. Use this skill when securing ROS2 communications, configuring DDS encryption and access control, hardening robot onboard computers, managing certificates and credentials, setting up network segmentation for robot fleets, or addressing the unique security challenges where cyber vulnerabilities become physical safety risks. Trigger whenever the user mentions SROS2, DDS security, robot security, robot hardening, ROS2 encryption, ROS2 access control, robot network security, secure robot deployment, robot certificates, keystore generation, robot firewall, e-stop security, safety controller isolation, or IEC 62443 for robotics.

日本語の概要は準備中です。原文の説明を表示しています。

Guides Attention-Gated Networks PyTorch medical imaging workflows for ultrasound classification, attention-gated U-Net segmentation, data layout, CUDA setup, and visualization helpers.

日本語の概要は準備中です。原文の説明を表示しています。

Implements email and internet monitoring compliance in the workplace per Barbulescu v Romania (ECHR Grand Chamber), EDPB guidance, and national labour law. Covers acceptable use policies, legitimate expectation of privacy, proportionality testing, and content vs metadata monitoring. Keywords: email monitoring, Barbulescu, workplace privacy, internet monitoring, acceptable use policy, ECHR, proportionality.

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Identifies and classifies GDPR Art. 9 special category data including racial origin, political opinions, religious beliefs, trade union membership, genetic, biometric, health, and sexual orientation data. Covers processing conditions under Art. 9(2)(a)-(j). Keywords: special category, Art 9, sensitive data, biometric, genetic, health data, explicit consent.

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Integrates Records of Processing Activities with privacy management platforms including OneTrust, TrustArc, Collibra, and DataGrail. Covers API-based synchronization, data mapping import, and automated RoPA population from enterprise tools. Activate for RoPA tool setup, OneTrust integration, TrustArc sync, privacy platform configuration.

日本語の概要は準備中です。原文の説明を表示しています。

Guides DPIA for health and medical data processing covering Art. 9(2)(h)-(j) exemptions, HIPAA crosswalk for transatlantic operations, clinical trial data protection under EU CTR 536/2014, and genetic data specifics under Art. 9(1). Activate for healthcare systems, clinical research, health apps, or medical device data. Keywords: health data, DPIA, Art. 9, clinical trial, genetic data, HIPAA, medical records, special category.

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Implements automated PII discovery and classification using tools like Microsoft Purview, BigID, OneTrust DataDiscovery, and AWS Macie. Covers scanning schedules, accuracy tuning, false positive management, and integration patterns. Keywords: data discovery, PII scanning, Purview, BigID, Macie, OneTrust, automated classification, data cataloging.

日本語の概要は準備中です。原文の説明を表示しています。

Design and implement VPCs and networking. Configure subnets, route tables, and security groups. Use when setting up AWS network infrastructure.

日本語の概要は準備中です。原文の説明を表示しています。

Applies the reasoning style of Kaiming He, computer vision pioneer and creator of ResNet. Use this skill whenever you are designing deep learning architectures, debugging neural network optimization, formulating generative AI problems, or bridging AI with other scientific domains. Trigger this skill for discussions on network depth, weight initialization, residual learning, flow matching, or when reframing discriminative tasks as conditional generation. It emphasizes simplicity in complex visual problems, end-to-end optimization, and viewing AI as a universal language for science.

日本語の概要は準備中です。原文の説明を表示しています。

Aruba Networks integration. Manage data, records, and automate workflows. Use when the user wants to interact with Aruba Networks data.

日本語の概要は準備中です。原文の説明を表示しています。

Acunetix integration. Manage data, records, and automate workflows. Use when the user wants to interact with Acunetix data.

日本語の概要は準備中です。原文の説明を表示しています。

Action Network integration. Manage data, records, and automate workflows. Use when the user wants to interact with Action Network data.

日本語の概要は準備中です。原文の説明を表示しています。

Connect to x.ruv.io, read federation channels and claims, or coordinate authorized work across Ruflo hosts with explicit identity and publishing boundaries.

日本語の概要は準備中です。原文の説明を表示しています。

Choose and validate RuVector or AgentDB memory for an agent application, including provenance, isolation, retention and workload-specific retrieval benchmarks.

日本語の概要は準備中です。原文の説明を表示しています。

Generate or evolve a repository-specific CLI, MCP and skills harness using MetaHarness, with bounded evaluation and explicit release authority.

日本語の概要は準備中です。原文の説明を表示しています。

Deploy, manage, and scale applications on Kubernetes clusters using manifests, Helm charts, and autoscaling configurations. Use when the user requests kubernetes deployment or provides relevant inputs for this workflow.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Medical Geneticist. Use when a task calls for Medical Geneticist judgment. Reasons from pedigree priors, HPO phenotype match, and ACMG/ClinGen variant classification; integrates exome/genome, CMA, RNA splicing, NBS ACT pathways, Tier 3 carrier screening, SF v3.3, and CPIC pharmacogenomics while treating VUS overcall, CPM/NIPT discordance, mtDNA heteroplasmy sampling, and SpliceAI-only splicing claims as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Molecular Geneticist. Use when a task calls for Molecular Geneticist judgment. Reasons from sequence-as-hypothesis, reference context (genome build, MANE/RefSeq transcript, HGVS), and allele-level molecular consequence through ACMG/AMP-ClinGen criteria, IGV/VEP/SpliceAI/gnomAD/ClinVar review, MIQE-compliant qPCR/ddPCR, and Sanger/NGS validation while treating allele dropout, pseudogene/paralog misalignment, FFPE deamination, contamination and barcode bleed, and transcript/build mismatch as first-class failure modes.

日本語の概要は準備中です。原文の説明を表示しています。

Think and work like an expert Immunogeneticist. Use when a task calls for Immunogeneticist judgment. Reasons from HLA/KIR/FcγR diversity, haplotype LD, and epitope immunogenicity; adjudicates NGS typing, imputation fine-mapping, eplet/TCE matching, and DSA/crossmatch artifacts.

日本語の概要は準備中です。原文の説明を表示しています。