2,615 件 ・ 関連度順
概要と使いどころ
Battle-tested PyTorch training recipes for all domains — LLMs, vision, diffusion, medical imaging, protein/drug discovery, spatial omics, genomics. Covers training loops, optimizer selection (AdamW, Muon), LR scheduling, mixed precision, debugging, and systematic experimentation. Use when training or fine-tuning neural networks, debugging loss spikes or OOM, choosing architectures, or optimizing GPU throughput.
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。
Half-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing calibration datasets, for fast quantization workflows, or when deploying with vLLM or HuggingFace Transformers.
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。
Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research effort.
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。
GGUF format and llama.cpp quantization for efficient CPU/GPU inference. Use when deploying models on consumer hardware, Apple Silicon, or when needing flexible quantization from 2-8 bit without GPU requirements.
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。
Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.
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 building game systems, implementing Unity/Unreal Engine features, or optimizing game performance. Invoke to implement ECS architecture, configure physics systems and colliders, set up multiplayer networking with lag compensation, optimize frame rates to 60+ FPS targets, develop shaders, or apply game design patterns such as object pooling and state machines. Trigger keywords: Unity, Unreal Engine, game development, ECS architecture, game physics, multiplayer networking, game optimization, shader programming, game AI.
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 designing GraphQL schemas, implementing Apollo Federation, or building real-time subscriptions. Invoke for schema design, resolvers with DataLoader, query optimization, federation directives.
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 building React 18+ applications in .jsx or .tsx files, Next.js App Router projects, or create-react-app setups. Creates components, implements custom hooks, debugs rendering issues, migrates class components to functional, and implements state management. Invoke for Server Components, Suspense boundaries, useActionState forms, performance optimization, or React 19 features.
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 deploying or managing Kubernetes workloads. Invoke to create deployment manifests, configure pod security policies, set up service accounts, define network isolation rules, debug pod crashes, analyze resource limits, inspect container logs, or right-size workloads. Use for Helm charts, RBAC policies, NetworkPolicies, storage configuration, performance optimization, GitOps pipelines, and multi-cluster management.
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。
Performs pandas DataFrame operations for data analysis, manipulation, and transformation. Use when working with pandas DataFrames, data cleaning, aggregation, merging, or time series analysis. Invoke for data manipulation tasks such as joining DataFrames on multiple keys, pivoting tables, resampling time series, handling NaN values with interpolation or forward-fill, groupby aggregations, type conversion, or performance optimization of large datasets.
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 developing firmware for microcontrollers, implementing RTOS applications, or optimizing power consumption. Invoke for STM32, ESP32, FreeRTOS, bare-metal, power optimization, real-time systems, configure peripherals, write interrupt handlers, implement DMA transfers, debug timing issues.
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 building cross-platform applications with Flutter 3+ and Dart. Invoke for widget development, Riverpod/Bloc state management, GoRouter navigation, platform-specific implementations, performance optimization.
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。
Rails 7+ specialist that optimizes Active Record queries with includes/eager_load, implements Turbo Frames and Turbo Streams for partial page updates, configures Action Cable for WebSocket connections, sets up Sidekiq workers for background job processing, and writes comprehensive RSpec test suites. Use when building Rails 7+ web applications with Hotwire, real-time features, or background job processing. Invoke for Active Record optimization, Turbo Frames/Streams, Action Cable, Sidekiq, RSpec Rails.
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。
Writes, optimizes, and debugs C++ applications using modern C++20/23 features, template metaprogramming, and high-performance systems techniques. Use when building or refactoring C++ code requiring concepts, ranges, coroutines, SIMD optimization, or careful memory management — or when addressing performance bottlenecks, concurrency issues, and build system configuration with CMake.
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。
AI citability scoring and optimization. Analyzes web page content to determine how likely AI systems (ChatGPT, Claude, Perplexity, Gemini) are to cite or quote passages from the page. Provides a citability score (0-100) with specific rewrite suggestions.
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。
GEO-first SEO analysis tool. Optimizes websites for AI-powered search engines (ChatGPT, Claude, Perplexity, Gemini, Google AI Overviews) while maintaining traditional SEO foundations. Performs full GEO audits, citability scoring, AI crawler analysis, llms.txt generation, brand mention scanning, platform-specific optimization, schema markup, technical SEO, content quality (E-E-A-T), and client-ready GEO report generation. Use when user says "geo", "seo", "audit", "AI search", "AI visibility", "optimize", "citability", "llms.txt", "schema", "brand mentions", "GEO report", or any URL for analysis.
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 website GEO+SEO audit with parallel subagent delegation. Orchestrates a comprehensive Generative Engine Optimization audit across AI citability, platform analysis, technical infrastructure, content quality, and schema markup. Produces a composite GEO Score (0-100) with prioritized action plan.
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。
Frontend development guidelines for React/TypeScript applications. Modern patterns including Suspense, lazy loading, useSuspenseQuery, file organization with features directory, MUI v7 styling, TanStack Router, performance optimization, and TypeScript best practices. Use when creating components, pages, features, fetching data, styling, routing, or working with frontend code.
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 Meta Ads measurement, Pixel and Conversions API, attribution, Facebook and Instagram creative, audiences, placements, automation, budgets, account structure, and policy. Use for Meta Ads, Facebook Ads, Instagram Ads, Advantage+, Pixel, CAPI, Events Manager, creative fatigue, or Meta campaign optimization.
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 Microsoft Advertising measurement, UET, search and audience campaigns, Google imports, syndication, keywords, creative, bidding, budgets, Copilot inventory, and policy. Use for Microsoft Ads, Bing Ads, UET, Microsoft Audience Network, Google Ads import, or Microsoft campaign optimization.
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 Google Ads measurement, Search, Shopping, Performance Max, Demand Gen, YouTube-linked inventory, keywords and search terms, negative-keyword generation or review, creative assets, bidding, budgets, settings, and policy. Use for Google Ads, AdWords, Search campaigns, search terms reports, broad negatives, Shopping, Performance Max, PMax, Demand Gen, GAQL, Google conversion tracking, or Google campaign optimization.
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 Amazon Ads profiles, regions, Sponsored Products, Sponsored Brands, Sponsored Display, DSP, portfolios, targeting, search terms, retail readiness, creative, budgets, ACOS, TACOS, reporting, and policy. Use for Amazon Ads, sponsored ads, Amazon PPC, ACOS, TACOS, ASIN advertising, Amazon DSP, or retail-media optimization.
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 TikTok Ads measurement, Pixel and Events API, mobile-first creative, audiences, Smart+, Shop and commerce campaigns, bidding, budgets, pacing, attribution, and policy. Use for TikTok Ads, TikTok Pixel, Events API, Smart+, TikTok Shop Ads, GMV Max, Spark Ads, or TikTok campaign optimization.
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 YouTube Ads campaign setup, video and Demand Gen inventory, Shorts, in-stream, CTV, creative, audiences, brand safety, bidding, and measurement. Use for YouTube Ads, video ads, pre-roll, bumper ads, skippable in-stream, Shorts ads, Demand Gen, VAC migration, CTV, or YouTube campaign optimization.
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。