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概要と使いどころ
Pricing model design, competitive positioning, value metric selection, price testing, and pricing page optimization. Use when the user asks about pricing strategy, pricing models, price testing, value-based pricing, or competitive pricing 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。
Template-based page generation at scale for SEO. Data-driven content, internal linking architecture, and automated optimization for large-scale content operations. Use when the user asks about programmatic SEO, pSEO, scaled content, template pages, or automated page 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。
Google Ads platform expertise. Audit campaigns, keywords, audiences, bidding, and conversion tracking. Use when the user asks about Google Ads, PPC, search advertising, Performance Max, Shopping ads, display campaigns, YouTube ads, or paid search 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。
DSPy is a Python framework from Stanford NLP that replaces hand-written prompts with code: you declare LLM tasks as typed signatures, compose them into modules, and let optimizers (BootstrapFewShot, MIPROv2, GEPA) tune the prompts and few-shot examples against your metric. Use when the user asks about DSPy, signatures, ChainOfThought, ReAct, teleprompters or optimizers, or wants to stop hand-tuning prompts.
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。
Plans and scripts data migrations between SQL databases: schema mapping, type conversion, batched and resumable loading, validation and cutover. Use when the user mentions "data migration," "database migration," "migrate from MySQL to PostgreSQL," "schema migration," "ETL pipeline," "data transfer," "database consolidation," "legacy migration," or "move data between databases." Covers schema analysis, mapping, transformation, batch processing, validation, and cutover planning. For query optimization during migration, see sql-optimizer.
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。
Finds orphaned, idle, and underutilized cloud resources across AWS, GCP, or Azure accounts. Use when someone needs to audit cloud spending, find unused EBS volumes, stale snapshots, unattached IPs, idle load balancers, or oversized RDS instances. Trigger words: cloud waste, orphaned resources, unused volumes, cloud audit, infrastructure cleanup, cloud bill 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。
ClearML is an open-source MLOps platform that records machine-learning experiments, versions datasets, chains tasks into pipelines and runs them on remote machines through agents and queues. Use when a user asks to "track experiments with ClearML", "log metrics, artifacts and models", "version a dataset", "run training on a remote GPU with clearml-agent", "build a ClearML pipeline", "run hyperparameter optimization", or "self-host ClearML Server". Covers the clearml 2.x Python SDK, clearml-agent 3.x and ClearML Server 2.x.
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 images and videos with Cloudinary. Use when a user asks to optimize images, add image transformations, implement responsive images, upload media, or serve optimized assets from a CDN.
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 caching layers for APIs and web applications using Redis or Memcached. Use when you need to reduce database load, improve response times, or handle traffic spikes. Covers cache-aside, write-through, and write-behind patterns, TTL strategies, cache invalidation, and stampede prevention. Trigger words: cache, Redis, Memcached, TTL, cache invalidation, response time, throughput, rate limiting.
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。
Launch and manage Amazon EC2 instances for scalable compute. Configure AMIs, security groups, key pairs, and EBS volumes. Set up auto-scaling groups for high availability and cost optimization across availability zones.
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。
Store and manage unstructured data with Azure Blob Storage. Create containers, upload and organize blobs, configure access tiers (Hot, Cool, Archive) for cost optimization, generate SAS tokens for secure temporary access, and set lifecycle management policies.
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 algorithmic trading systems — backtesting, strategy development, live execution, and risk management. Use when tasks involve backtesting trading strategies, connecting to exchange APIs (Binance, Alpaca, Interactive Brokers), implementing technical indicators, portfolio optimization, order execution, risk management rules, market data processing, or building trading bots. Covers both crypto and traditional markets.
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。
Expert in meme creation and virality - understanding why certain ideas spread while others die. Covers meme formats, timing, adaptation, meta-commentary, and platform-specific optimization. Knows the difference between forcing a meme and engineering conditions for organic spread. Use when "meme, viral content, make it memeable, shareable, internet culture, template, " mentioned.
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 automating model architecture design, optimizing hyperparameters, or exploring neural network configurations - covers NAS algorithms, search spaces, Bayesian optimization, and AutoML toolsUse when ", " mentioned.
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 space missions, computing launch windows, optimizing trajectories, analyzing payload constraints, or planning mission phases and contingencies. Use when "mission design, launch window, trajectory optimization, mission timeline, mass budget, propellant budget, mission phases, porkchop plot, C3, gravity assist, low thrust, mission architecture, LEO, GEO, interplanetary, " mentioned.
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。
The craft of designing icons that communicate instantly across cultures, contexts, and scales. Icon design bridges semiotics, cognitive psychology, and visual craft to create symbols that users understand without thinking. Great icons are invisible in the best way - they convey meaning so naturally that users never pause to decode them. This skill covers icon grid systems, optical alignment, stroke consistency, metaphor selection, scalability across sizes, SVG optimization, and icon set coherence. The best icon designers understand that icons are a visual language - each icon must speak the same dialect while carrying its own distinct meaning. Use when "icon, iconography, symbol, glyph, icon set, icon library, pictogram, svg icon, icon grid, icon pack, feather icons, lucide, phosphor, heroicons, icon system, icon style, icons, iconography, svg, symbols, glyphs, pictograms, ui-icons, icon-set, visual-design, design-system" mentioned.
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。
Expert in designing engaging learning experiences - completion optimization, multimedia learning, interactivity, gamification, and retention strategies. Covers the science of how people learn and practical techniques to make courses that students actually finish. Use when "learning experience, course engagement, completion rate, make learning fun, gamification, interactive course, learning design, " mentioned.
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。
Expert knowledge for real-time and baked lighting in games - from cinematography fundamentals to engine-specific optimization, covering GI, time-of-day, volumetrics, and platform-aware lighting pipelinesUse when "lighting, light design, baked lighting, realtime lighting, lightmap, lightmapping, light probe, reflection probe, global illumination, GI, ambient occlusion, shadow, shadow cascade, time of day, day night cycle, volumetric fog, volumetric lighting, god rays, HDR, tonemapping, bloom, exposure, emissive, area light, Lumen, Enlighten, ray tracing, RTGI, light baking, lighting, global-illumination, lightmapping, shadows, GI, light-probes, reflection-probes, HDR, tonemapping, volumetric, fog, time-of-day, baked, realtime, mixed-lighting, lumen, enlighten, radiosity, ray-tracing, RTGI" mentioned.
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 application architecture expert for RAG, prompting, agents, and production AI systemsUse when "rag system, prompt engineering, llm application, ai agent, structured output, chain of thought, multi-agent, context window, hallucination, token optimization, llm, rag, prompting, agents, structured-output, anthropic, openai, langchain, ai-architecture" mentioned.
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。
Expert Godot 4 game developer specializing in GDScript, the node/scene system, signals, resources, and engine-native patterns. Provides deep knowledge of Godot's unique architecture, performance optimization, and best practices for building games from simple prototypes to production-ready releases. Use when "godot, gdscript, godot 4, godot engine, build a game with godot, godot scene, godot node, godot signal, godot resource, godot tilemap, godot physics, godot animation, godot ui, godot multiplayer, godot, gdscript, game-engine, game-development, 2d-games, 3d-games, open-source" mentioned.
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。
Specialized skill for building production-ready serverless applications on GCP. Covers Cloud Run services (containerized), Cloud Run Functions (event-driven), cold start optimization, and event-driven architecture with Pub/Sub. Use when ", gcp, cloud-run, serverless, containers, pubsub" mentioned.
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。
GraphQL API specialist for schema design, resolvers, federation, and performance optimizationUse when "graphql, schema design, resolvers, federation, apollo, relay, dataloader, n+1 problem, graphql security, graphql, api, schema, resolvers, federation, subscriptions, apollo, relay, dataloader" mentioned.
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。
Patterns for computer-aided drug discovery including virtual screening, molecular docking, ADMET prediction, lead optimization, and integration with AI/ML methods. Covers both structure-based and ligand-based approaches. Use when ", " mentioned.
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。
Expert at handling file uploads and cloud storage. Covers S3, Cloudflare R2, presigned URLs, multipart uploads, and image optimization. Knows how to handle large files without blocking. Use when "file upload, S3, R2, presigned URL, multipart, image upload, cloud storage, file-upload, s3, r2, storage, presigned, images" mentioned.
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。