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MLOps across model deployment, ML pipelines, monitoring, and feature stores. Use when deploying models to production, building training pipelines, setting up drift detection, configuring feature stores, or automating ML CI/CD workflows.
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。
Audit data quality across pipelines, warehouses, and stores. Use when designing a DQ program, defining DQ dimensions, building rule-based checks, detecting schema drift, monitoring freshness SLAs, or responding to a DQ incident.
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。
Scan project dependencies for vulnerabilities, license issues, and upgrade opportunities across Python, Node.js, Go, and Rust. Use when auditing dependencies, checking licenses, planning upgrades, or assessing supply chain 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。
Audit UI/UX designs for quality, AI-generated slop, and accessibility. Use when reviewing designs, detecting slop patterns, validating WCAG compliance, checking design-token adherence, or reviewing responsive design across breakpoints.
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。
Business intelligence across dashboard design, visualization, and reporting automation. Use when designing dashboards, building KPI frameworks, automating reports, creating data stories, or optimizing BI tool performance.
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 AWS serverless architectures for startups with IaC. Use when designing serverless architecture, writing CloudFormation, optimizing AWS costs, setting up CI/CD, or migrating to AWS across Lambda, API Gateway, and DynamoDB.
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。
Build and maintain one coherent company story across employees, investors, customers, candidates, and partners. Use when preparing all-hands meetings, investor updates, board presentations, recruiting narratives, or crisis communications.
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。
Systematically QA test a web application with browser-based bug fixing. Four modes: diff-aware (automatic on feature branches), full (systematic exploration), quick (30-second smoke test), regression (compare against baseline). Atomic bug-fix workflow with regression testing. Health scoring across 8 categories.
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。
Infrastructure-first security audit across 14 phases: attack surface mapping, secrets archaeology (git history), supply chain analysis, CI/CD pipeline security, LLM/AI threat detection, OWASP Top 10, STRIDE threat modeling. Confidence gates, exploit scenarios, parallel verification, trend tracking. Read-only.
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。
Report-only QA — same browser-based testing as qa but documents bugs with screenshots and repro steps only, no code changes. Health score formula weighted across 8 categories. Outputs to .gstack/qa-reports/.
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。
Optimizes SQL queries, designs database schemas, troubleshoots performance with window functions, CTEs, indexing strategies, and query plan analysis across database dialects.
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 infrastructure as code with Terraform across AWS, Azure, or GCP including module development, state management, provider configuration, and multi-environment workflows.
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。
Generates test files, creates mocking strategies, analyzes code coverage, designs test architectures, and produces test plans across functional, performance, and security testing.
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。
Optimizes database queries and improves performance across PostgreSQL and MySQL systems including index design, query rewrites, configuration tuning, and partitioning strategies.
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。
Release coordination across departments
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。
Designs cloud architectures, creates migration plans, generates cost optimization recommendations, and produces disaster recovery strategies across AWS, Azure, and GCP.
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。
Check and compare software component versions on SageMaker HyperPod cluster nodes - NVIDIA drivers, CUDA toolkit, cuDNN, NCCL, EFA, AWS OFI NCCL, GDRCopy, MPI, Neuron SDK (Trainium/Inferentia), Python, and PyTorch. Use when checking component versions, verifying CUDA/driver compatibility, detecting version mismatches across nodes, planning upgrades, documenting cluster configuration, or troubleshooting version-related issues on HyperPod. Triggers on requests about versions, compatibility, component checks, or upgrade planning for HyperPod clusters.
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。
Diagnose NCCL failures and adjacent training-pod failures on HyperPod GPU clusters (EKS or Slurm) — training hangs, AllReduce / collective-op timeouts, EFA or libfabric errors, rendezvous failures, EFA TCP fallback, /dev/shm or memlock issues, NCCL version mismatch across pods, container OOM / exit-137 / OOMKilled, GPU OOM (CUDA out of memory), CrashLoopBackOff / Pending pods, MASTER_ADDR DNS, NetworkPolicy blocking. Not for single-node hardware faults (→ hyperpod-node-debugger § G) or cluster-creation EFA / SSM failures (→ hyperpod-cluster-debugger § A / § F).
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。
Monitor GEO visibility over time across six AI answer engines, with a 0-100 trend. "is ChatGPT mentioning us"
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。
Report on the brand intelligence base: confident learnings, patterns, playbooks, gaps. "what have we learned across campaigns"
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。
Build the agency dashboard across all client brands: health, pacing, risk. "how are all our clients doing"
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。
Audit all campaigns running for a brand across channels, with 4-tier triage. "we just inherited this account"
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。
Analyzes social media campaign performance across platforms with engagement metrics, ROI calculations, and audience insights for data-driven marketing decisions
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 production-ready Claude Code hooks with interactive Q&A, automated installation, and enhanced validation. Supports 10 templates across 7 event types for comprehensive workflow automation.
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。