「caching」の検索結果

Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).

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 auditing slow page loads, heavy assets, or rendering delays related to Enable browser caching. Verify the actual bottleneck in DevTools, Lighthouse, or field data before recommending changes.

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。

Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).

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 structured generation and serving for LLMs with RadixAttention prefix caching. Use for JSON/regex outputs, constrained decoding, agentic workflows with tool calls, or when you need 5× faster inference than vLLM with prefix sharing. Powers 300,000+ GPUs at xAI, AMD, NVIDIA, and LinkedIn.

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 structured generation and serving for LLMs with RadixAttention prefix caching. Use for JSON/regex outputs, constrained decoding, agentic workflows with tool calls, or when you need 5× faster inference than vLLM with prefix sharing. Powers 300,000+ GPUs at xAI, AMD, NVIDIA, and LinkedIn.

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。

In-memory caching in Golang using samber/hot — eviction algorithms (LRU, LFU, TinyLFU, W-TinyLFU, S3FIFO, ARC, TwoQueue, SIEVE, FIFO), TTL, cache loaders, sharding, stale-while-revalidate, missing key caching, and Prometheus metrics. Apply when using or adopting samber/hot, when the codebase imports github.com/samber/hot, or when the project repeatedly loads the same medium-to-low cardinality resources at high frequency and needs to reduce latency or backend pressure.

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。

Optimize Claude API performance with prompt caching, model selection, streaming, and latency reduction techniques. Use when experiencing slow responses, optimizing token usage, or reducing time-to-first-token in production. Trigger with phrases like "anthropic performance", "claude speed", "optimize claude latency", "anthropic caching", "faster claude responses".

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。

Optimize Anima code generation performance with caching, parallelism, and output tuning. Use when reducing generation latency, optimizing batch component generation, or improving generated code quality for production use. Trigger with: "anima performance", "anima slow", "anima optimization", "anima caching".

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 modern full-stack web applications with Next.js (App Router, Server Components, RSC, PPR, SSR, SSG, ISR), Turborepo (monorepo management, task pipelines, remote caching, parallel execution), and RemixIcon (3100+ SVG icons in outlined/filled styles). Use when creating React applications, implementing server-side rendering, setting up monorepos with multiple packages, optimizing build performance and caching strategies, adding icon libraries, managing shared dependencies, or working with TypeScript full-stack projects.

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。

Replay an LLM inference request trace (Mooncake / vLLM / SGLang hash_ids format) against a block-level KV prefix cache and compute hit statistics. Use when given a request trace plus cache configuration and asked for hit rate, hit tokens, or final cache contents. Covers the longest-contiguous-prefix semantics that distinguishes KV prefix caching from full-prompt prompt caching, the policy-specific residency and eviction rules (LRU, LFU, S3FIFO), and the partial-last-block accounting rule.

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 Redis for caching and data storage. Set up clustering, persistence, and Sentinel. Use when implementing Redis caching or queues.

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。

Reduce LLM API and infrastructure costs through model selection, prompt caching, batching, caching, quantization, and self-hosting strategies. Track spend by team and model, set budgets, and implement cost-aware routing.

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 an image loading pipeline with memory/disk caching, deduplication, and a CachedAsyncImage SwiftUI view. Use when user wants image caching, lazy image loading, or a replacement for AsyncImage.

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 an HTTP caching layer with Cache-Control parsing, ETag/conditional requests, and offline fallback. Use when user wants to add response caching, offline support, or reduce API calls.

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。

Code generator skills that produce production-ready Swift code for common app components. Use when user wants to add logging, analytics, onboarding, review prompts, networking, authentication, paywalls, settings, persistence, error monitoring, CI/CD pipelines, localization, push notifications, deep linking, testing, accessibility, widgets, feature flags, app icons, image caching, pagination, HTTP caching, share cards, social export, subscription lifecycle, referral systems, watermarks, streak tracking, milestone celebrations, what's new screens, lapsed user re-engagement, usage insights, variable rewards, consent flows, account deletion, permission priming, force updates, state restoration, debug menus, offline queues, feedback forms, announcement banners, quick win sessions, Spotlight indexing, App Clips, screenshot automation, background processing, app extensions, data export, or SwiftUI preview sample data and variant matrices.

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 Next.js cache layers, invalidation, and cache-component APIs. Use when choosing `fetch` caching, `use cache`, tags, or stale-data debugging in Next.js.

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。

Redis caching strategies, cache invalidation, write-through/write-behind, TTL management, and cache stampede protection.

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。

Implement caching strategies using @delon/cache. Use this skill when adding memory cache, LocalStorage cache, SessionStorage cache, or cache interceptors for HTTP requests. Supports TTL-based expiration, cache invalidation, cache grouping, and persistent storage. Optimizes performance by reducing redundant API calls and database queries.

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。

Quick reference for RESTful API design patterns, HTTP semantics, caching, and rate limiting. Triggers on: rest api, http methods, status codes, api design, endpoint design, api versioning, rate limiting, caching headers.

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 Next.js performance optimization skill covering Core Web Vitals, image/font optimization, caching strategies, streaming, bundle optimization, and Server Components best practices. Use when optimizing Next.js applications for Core Web Vitals (LCP, INP, CLS), implementing next/image and next/font, configuring caching with unstable_cache and revalidateTag, converting Client Components to Server Components, implementing Suspense streaming, or analyzing and reducing bundle size. Supports Next.js 16 + React 19 patterns.

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 patterns for implementing Spring Boot caching: configures Redis/Caffeine/EhCache providers with TTL and eviction policies, applies @Cacheable/@CacheEvict/@CachePut annotations, validates cache hit/miss behavior, and exposes metrics via Actuator. Use when adding caching to Spring Boot services, configuring cache expiration, evicting stale data, or diagnosing cache misses.

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。

Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a one-liner" — whenever: the prompt names Claude/Anthropic in any form (Claude, Anthropic, Fable, Opus, Sonnet, Haiku, `anthropic`, `@anthropic-ai`, `claude-*`, `us.anthropic.*`, `[1m]`); the user asks about an LLM (pricing/model choice/limits/caching) — never answer from memory; OR the task is LLM-shaped with provider unstated (agent/MCP/tool-definition/multi-agent/RAG/LLM-judge/computer-use; generate/summarize/extract/classify/rewrite/converse over NL; debugging refusals/cutoffs/streaming/tool-calls/tokens). SKIP only when another provider is being worked on (overrides all triggers): OpenAI/GPT/Gemini/Llama/Mistral/Cohere/Ollama named in the query; OR `grep -rE 'openai|langchain_openai|google.generativeai|genai|mistralai|cohere|ollama'` over the project hits (run this grep FIRST if no provider named — don't Read the file).

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。

1.7x faster test execution with intelligent caching and 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。

WordPress performance code review and optimization analysis. Use when reviewing WordPress PHP code for performance issues, auditing themes/plugins for scalability, optimizing WP_Query, analyzing caching strategies, checking code before launch, or detecting anti-patterns, or when user mentions "performance review", "optimization audit", "slow WordPress", "slow queries", "high-traffic", "scale WordPress", "code review", "timeout", "500 error", "out of memory", or "site won't load". Detects anti-patterns in database queries, hooks, object caching, AJAX, and template loading.

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。