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概要と使いどころ
Pre-production audit that scans a codebase for security, database, deployment, code quality, AI/LLM, dependency, frontend, and observability issues. Intercepts deploy commands and blocks until critical items pass. Stack-agnostic. Use for "run ship gate", "am I ready to ship", "pre-launch audit", "can I deploy", "push to production", "go live checklist", "preflight check". Not for CI/CD setup or infra provisioning.
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Design production-ready observability strategies combining metrics, logs, and traces. Includes SLI/SLO design, golden-signals monitoring, alert optimization. Use when adding observability to a new service, refactoring alerting that is too noisy, or designing an SLO program before scaling production load.
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。
Makes AI-generated content sound genuinely human — not just cleaned up, but alive. Use when content feels robotic, uses too many AI clichés, lacks personality, or reads like it was written by committee. Triggers: 'this sounds like AI', 'make it more human', 'add personality', 'it feels generic', 'sounds robotic', 'fix AI writing', 'inject our voice'. NOT for initial content creation (use content-production). NOT for SEO optimization (use content-production Mode 3).
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。
Deprecated redirect skill that routes legacy 'content creator' requests to the correct specialist. Use when a user invokes 'content creator', asks to write a blog post, article, guide, or brand voice analysis (routes to content-production), or asks to plan content, build a topic cluster, or create a content calendar (routes to content-strategy). Does not handle requests directly — identifies user intent and redirects to content-production for writing/SEO/brand-voice tasks or content-strategy for planning tasks.
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。
Full content production pipeline — takes a topic from blank page to published-ready piece. Use when you need to execute content: write a blog post, article, or guide end-to-end. Triggers: 'write a post about', 'draft an article', 'create content for', 'help me write', 'I need a blog post'. NOT for content strategy or calendar planning (use content-strategy). NOT for repurposing existing content (use content-repurposing). NOT for social captions 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。
Manage environment-variable hygiene and secrets safety across local development and production. Practical auditing, drift awareness, rotation readiness. Use when auditing .env files for committed secrets, planning a credential rotation, debugging missing-env-var production incidents, or hardening a new project against secrets leakage.
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。
Pre-production validation — end-to-end build to confirm the full loop is achievable before committing to Production. After GDDs, architecture, UX specs.
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。
Provides GKE golden path configuration defaults, production readiness checklists, and cluster default patterns. Use when designing GKE clusters, verifying GKE production readiness, or checking configurations against GKE defaults. Don't use for setting up workload autoscaling specifically (use gke-workload-scaling instead).
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。
How to cut a Kortix production release — the versioning philosophy (when patch vs minor vs major) and the exact flow: promote the newest dev SHA with a green Tests run to staging, let the staging PR's checks be the gate, fix forward on dev until it is green, then run Promote to Production and deploy + verify prod. Load WHENEVER the user wants to release, promote, cut/ship a version, publish a release, bump the version, or asks why a promotion is stuck. Load it too whenever another skill or doc needs to describe the release/promotion flow — this file is the one place it is written out in full.
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。
Root-cause a production error with Sentry's evidence before touching code — pull the issue, read the stack trace and breadcrumbs, and separate the crash from its trigger. Use when the user pastes a Sentry link or issue ID, reports a production error, or asks why something is crashing for users.
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。
LLM observability platform for tracing, evaluation, and monitoring. Use when debugging LLM applications, evaluating model outputs against datasets, monitoring production systems, or building systematic testing pipelines for AI applications.
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。
Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.
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。
Framework for state-of-the-art sentence, text, and image embeddings. Provides 5000+ pre-trained models for semantic similarity, clustering, and retrieval. Supports multilingual, domain-specific, and multimodal models. Use for generating embeddings for RAG, semantic search, or similarity tasks. Best for production embedding generation.
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。
Framework for building LLM-powered applications with agents, chains, and RAG. Supports multiple providers (OpenAI, Anthropic, Google), 500+ integrations, ReAct agents, tool calling, memory management, and vector store retrieval. Use for building chatbots, question-answering systems, autonomous agents, or RAG applications. Best for rapid prototyping and production deployments.
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 LLM inference with NVIDIA TensorRT for maximum throughput and lowest latency. Use for production deployment on NVIDIA GPUs (A100/H100), when you need 10-100x faster inference than PyTorch, or for serving models with quantization (FP8/INT4), in-flight batching, and multi-GPU scaling.
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。
High-performance vector similarity search engine for RAG and semantic search. Use when building production RAG systems requiring fast nearest neighbor search, hybrid search with filtering, or scalable vector storage with Rust-powered 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。
Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies for lean, fast execution.
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。
Trains large language models (2B-462B parameters) using NVIDIA Megatron-Core with advanced parallelism strategies. Use when training models >1B parameters, need maximum GPU efficiency (47% MFU on H100), or require tensor/pipeline/sequence/context/expert parallelism. Production-ready framework used for Nemotron, LLaMA, DeepSeek.
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。
NVIDIA's runtime safety framework for LLM applications. Features jailbreak detection, input/output validation, fact-checking, hallucination detection, PII filtering, toxicity detection. Uses Colang 2.0 DSL for programmable rails. Production-ready, runs on T4 GPU.
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。
Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.
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 or update a chronology from declared document sources and uploads — dated events extracted, de-duped, and tagged by significance per the matter theory. Use when the user asks to build a chronology or timeline from a production or matter file, says "chron from the production" or "what happened when", or needs a working, statement-of-facts, or witness-specific timeline.
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。
End-to-end audio production workflow with stems, effects, archiving, and verification
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 Creative Production is explicitly invoked or mentioned without a concrete request, when the user asks what Creative Production can do, or when the user wants help getting started without enough context to choose a 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。
Audit Claude Code agents, skills, and commands for quality and production readiness. Use when evaluating skill quality, checking production readiness scores, or comparing agents against best-practice templates.
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。