'caching' 검색 결과

Deploy and manage cloud infrastructure on Cloudflare (Workers, R2, D1, KV, Pages, Durable Objects, Browser Rendering), Docker containers, and Google Cloud Platform (Compute Engine, GKE, Cloud Run, App Engine, Cloud Storage). Use when deploying serverless functions to the edge, configuring edge computing solutions, managing Docker containers and images, setting up CI/CD pipelines, optimizing cloud infrastructure costs, implementing global caching strategies, working with cloud databases, or building cloud-native applications.

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Master context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.

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Use when optimizing token usage, KV cache efficiency, or context window management for LLM agents. Keywords: context optimization, KV cache, prompt caching, token budget, semantic pruning, lost-in-the-middle.

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Build robust backend systems with modern technologies (Node.js, Python, Go, Rust), frameworks (NestJS, FastAPI, Django), databases (PostgreSQL, MongoDB, Redis), APIs (REST, GraphQL, gRPC), authentication (OAuth 2.1, JWT), testing strategies, security best practices (OWASP Top 10), performance optimization, scalability patterns (microservices, caching, sharding), DevOps practices (Docker, Kubernetes, CI/CD), and monitoring. Use when designing APIs, implementing authentication, optimizing database queries, setting up CI/CD pipelines, handling security vulnerabilities, building microservices, or developing production-ready backend systems.

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Design, run, and review fair performance, token, and cost comparisons across GitHub Copilot CLI, Codex CLI, and direct model APIs. Use for AI CLI benchmark, Copilot vs Codex, prompt-cache diagnosis, cache read/write analysis, fresh-process latency measurement, token-cost comparison, or when a benchmark must separate provider caching from local CLI caches.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

CircleCI guidance — config design, orbs, caching, workflows, contexts, and pipeline optimization.

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Cloudflare guidance — DNS, CDN caching, WAF, Workers, Pages, Zero Trust, and edge performance tuning.

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Anthropic Claude API guidance — messages API, tool use, prompt caching, extended thinking, and production patterns.

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Optimizes Atlassian Forge apps to reduce platform consumption and avoid unnecessary costs using Atlassian's "Optimise Forge platform costs" guidance. Use when the user asks to optimize Forge app costs, reduce Forge invocations, lower GB-seconds, reduce storage or log usage, tune memory, replace polling, improve scheduled triggers, reduce KVS writes, move work to the frontend, use bridge APIs, batch API calls, add caching, or evaluate Forge Remote trade-offs. By default, perform an audit first and offer to make the recommended changes after presenting the audit. Only modify files immediately when the user explicitly asks the agent to implement or apply optimizations.

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React Query server state — query keys and query options, caching policy, error handling, and typed clients generated from an API schema

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URQL GraphQL client patterns — the exchange pipeline, document and normalized caching, queries, mutations, subscriptions, and authentication

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Nx monorepo build system — workspace configuration, project graph, task pipelines, caching, generators, plugins, and release management

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Query optimization, caching, indexing, connection pooling, async patterns

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Turborepo CI pipelines with remote caching and affected detection

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Serverless Redis-compatible key-value store via Upstash REST API -- edge-compatible, automatic JSON serialization, TTL-based caching

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Official Anthropic SDK patterns for TypeScript/Node.js — client setup, Messages API, streaming, tool use, vision, extended thinking, structured outputs, prompt caching, batch API, and production best practices

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Redis in-memory data store patterns with ioredis and node-redis -- caching, sessions, rate limiting, pub/sub, streams, queues, transactions, cluster

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Official TypeScript SDK for Google Gemini — client setup, text generation, multimodal input, function calling, structured output, streaming, embeddings, context caching, and chat sessions

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Use when configuring django-storages for cloud file storage - STORAGES setting, Amazon S3, Google Cloud Storage and Azure backends, signed URLs, CDN and caching, multipart uploads, or storage testing

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Use when building Django REST APIs with TurboDRF - model Meta configuration, role-based and field-level permissions, multi-tenant predicates, router wiring, management commands, settings, or troubleshooting

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform. Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like multimodal inputs, tools, media generation, caching, batch prediction, and Live API.

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Deep research on technical topics using EXA tools with intelligent two-tier caching. Use when user asks to research a topic, investigate best practices, look up information, find patterns, or explore architectures. Also invoked by /research command. Triggers: "research", "look up", "investigate", "deep dive", "find information about", "what are best practices for", "how do others implement".

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Use when Agentforce run costs are climbing, you need to forecast scale, or you want to reduce tokens per conversation without hurting quality. Covers topic (now subagent) design impact on cost, prompt/template reuse, grounding size discipline, caching, and model-tier selection. Triggers: 'agentforce cost', 'tokens per conversation too high', 'reduce agentforce runs spend', 'forecast agentforce scale cost', 'einstein trust layer tokens'. NOT for capping spend per user with a budget gate and fallback — use agentforce/agent-rate-limit-strategy. NOT for org-wide model-tier and BYOLLM platform strategy — use architect/ai-platform-architecture.

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RecordType ID differences across orgs: dynamic lookup via Schema.SObjectType methods, DeveloperName for stable refs, hard-coded ID anti-patterns, record-type caching, deployment impact. NOT for deciding whether to use record types at all — use admin/record-types-and-page-layouts. NOT for layout/profile explosion at scale — use admin/record-type-strategy-at-scale. NOT for hard-coded Profile, Queue or User IDs in Apex — use apex/apex-hardcoded-id-elimination.

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