「cdn」の検索結果

Performance profiling and optimization for web apps — Core Web Vitals (LCP, INP, CLS), Lighthouse audits, bundle analysis, backend profiling (CPU, memory, DB queries), N+1 detection, caching strategies (Redis, CDN, HTTP), and performance budgets. Use when user asks to improve performance, run Lighthouse audit, profile a Node.js app, optimize Core Web Vitals, reduce bundle size, or investigate slow response times. Do NOT use for database schema optimization (use db-sculptor), Docker image optimization (use docker), or CDN configuration.

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。

Servd (servd.host) — Craft-specialised managed hosting for Craft CMS. Covers git push-to-deploy with the optional servd.yaml build config, local → staging → production environments with uni-directional Project Config sync, the servd/craft-asset-storage plugin (S3-backed Flysystem volumes on the svdcdn.com CDN, off-server image transforms, Imager-X/ImageOptimize integrations), Servd's static caching (full vs tag-based purge, {% dynamicInclude %}, CSRF injection, cache-busting) and running Blitz alongside it in reverse-proxy mode, MariaDB/MySQL databases over an SSH tunnel, automatic + manual backups, the Dedicated Queue Runner, environment variables and secrets, the ephemeral load-balanced filesystem (Redis + remote volumes for runtime files), plugin/feature constraints, and Servd-vs-Craft-Cloud differences.

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 guide for file uploads (S3, R2, Supabase Storage), presigned URLs, image/video processing, CDN optimization, and media pipeline architecture / Panduan ahli untuk upload file (S3, R2, Supabase Storage), presigned URL, pemrosesan gambar/video, optimasi CDN, dan arsitektur pipeline media.

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。

Hunt web cache poisoning, CDN cache poisoning, and cache deception attacks. Use when target uses a CDN (Cloudflare, Akamai, Fastly, AWS CloudFront) or has Varnish/nginx caches and you want to identify cache key flaws that let attackers serve malicious content to other 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。

Guides agents through a 6-step discovery process to design and deploy Google Cloud global external Application Load Balancers with Cloud CDN, Cloud Armor, and Service Extensions, mapping workload requirements to best-practice configurations. Use when: - Designing, configuring, or deploying a Google Cloud global external Application Load Balancer, Cloud CDN, Cloud Armor WAF, or Service Extensions. - Discovering existing Google Cloud resources (Cloud Storage, MIGs, GKE, Cloud Run) to use as backends. - Generating production-grade Terraform HCL or gcloud CLI scripts for global external Application Load Balancers. - Actuating deployments via Infrastructure Manager or bash scripts, including IAM pre-checks. - Detecting, analyzing, or reconciling configuration drift on deployed global external Application Load Balancers. Don't use for: - Non-Google Cloud load balancing or security configurations. - Purely regional or internal load balancing setups (unless part of a hybrid/failover global design).

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。

Render a wiki into ONE self-contained HTML snapshot (pages + provenance) that opens offline — no CDN, no remote assets, page content HTML-escaped. Use to share or review accumulated wiki knowledge as a static page. NOT for capturing/approving knowledge (see mk:wiki); NOT for generic code/diagram visuals (see mk:preview).

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。

Detects m6A modifications from Oxford Nanopore direct-RNA-seq (DRS) signal using m6Anet (multiple-instance-learning over DRACH 5-mer signal). Covers the upstream pipeline (Dorado/Guppy basecalling -> minimap2 map-ont -> nanopolish eventalign -> m6anet dataprep -> m6anet inference), per-site vs per-read probability including the mod_ratio stoichiometry column, the DRACH-only constraint, minimum-coverage thresholds (20-50 reads/site), multi-condition comparison via xPore/Nanocompore/ELIGOS, Dorado native modification calling (RNA004, 2024+), and the cDNA-vs-DRS distinction (cDNA Nanopore CANNOT detect modifications). Use when calling m6A from ONT DRS without immunoprecipitation, choosing m6Anet vs xPore vs Nanocompore vs ELIGOS vs Dorado native, interpreting probability_modified vs mod_ratio vs per-read probabilities, deciding between m6Anet (known DRACH sites) and Dorado/Remora (genome-wide screening), pinning RNA002 vs RNA004 chemistry and basecaller versions, or troubleshooting eventalign/dataprep failures.

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 patterns, cache-aside, write-through, TTL strategies, and invalidation. Activate on: caching, Redis, cache invalidation, cache-aside, write-through, TTL, CDN cache, stale-while-revalidate. NOT for: CDN/reverse proxy setup (use api-gateway-reverse-proxy-expert), database query optimization (use data-warehouse-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。

dev-graph を静的 HTML に可視化したいとき、外部 CDN/npm なしの自己完結 SVG + inline JS 成果物を生成したいときに使う。

Customize WP Rocket behavior from a third-party plugin / theme via filter hooks — exclude URIs / cookies / user agents / REST API namespaces from caching, configure CDN URL rewrites, extend lazy load handling, override capability requirements, hook into Action Scheduler integration. Critical guidance — rocket_cache_reject_uri takes URI patterns (regex-like), NOT full URLs; rocket_cache_reject_* filters all expect arrays. The rocket_buffer filter is the FULL HTML output filter — extremely powerful but dangerous; one fatal error in the callback breaks every cached page until WP Rocket is disabled. Use when extending WP Rocket's default rules, NOT for cache invalidation (see wp-rocket-cache-invalidation). Triggers on rocket_cache_reject_, rocket_cdn_, do_rocket_lazyload, rocket_buffer, rocket_capacity, "exclude from WP Rocket cache".

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。

在授权渗透测试中系统性挖掘 HTTP 请求走私（HTTP Request Smuggling / desync）。当目标前面有反向代理/CDN/负载均衡（前端）转发给后端应用，且怀疑前后端对 Content-Length 与 Transfer-Encoding、畸形头、chunked trailer 的解析不一致时使用——典型场景：想毒化后端 socket 劫持他人请求、批量窃取会话 Cookie/令牌、缓存投毒、绕过前端访问控制。适用目标类型 Web / REST API（有分层代理）。触发场景包括用户说"测下有没有 HTTP 走私/desync""这个 CDN 后端解析一致吗""能不能毒 socket 偷别人 cookie""CL.TE / TE.CL 打一下"。输出：带 desync 时序证据与原始报文的 finding 报告（含 killed 记录）。

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。

在授权渗透测试中挖掘 Web 缓存投毒与缓存欺骗（web cache poisoning / cache deception）。当目标前有缓存层（CDN/反代/Varnish）且缓存键未覆盖某些影响响应的输入（unkeyed header/参数/解析差异）时使用——典型场景：X-Forwarded-Host 反射进响应被缓存、unkeyed 参数、缓存键规范化差异、静态扩展名欺骗缓存私有页。适用目标类型 Web / CDN。触发场景包括用户说"测下缓存投毒""X-Forwarded-Host 能不能毒缓存""缓存欺骗看一下""unkeyed 输入有没有"。输出：投毒/欺骗可行性 + 被缓存证据的 finding（含 killed 记录）。

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 en edge computing v2 (CDN, edge functions, WebAssembly, IoT gateway, contexte DZ)

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。

Caching Specialist IA — Expert en caching (Redis, Memcached, CDN, HTTP caching, stale-while-revalidate)

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。

Caching specialist v2 — Redis, Memcached, CDN caching, invalidation strategies, distributed, 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。

Vercel プラットフォームリファレンス。Vercel CLI、vercel.json / vercel.ts 設定、 Vercel Functions（Node.js / Edge / Fluid Compute / ISR / Middleware）、 Vercel Blob、Edge Config、Marketplace Storage（Neon / Upstash / Supabase）、 デプロイメント管理（Git 連携 / rollback / rolling release）、 環境変数、ドメイン、DNS、ログ、キャッシュ、CDN。

Next.js App Router 専用 API リファレンス（Pages Router / getStaticProps 等は非対応）。 Server Components, Server Actions, layout/page/loading/error ファイル規約, dynamic routes, parallel/intercepting routes, Metadata API (generateMetadata), use cache, revalidatePath/revalidateTag, next/image・next/font・next/link, cookies/headers, useRouter, next.config.js, proxy（旧 middleware）。 プラットフォーム実行基盤・CDN・ISR インフラは vercel スキル参照。

AMD ROCm / HIP GPU コンピューティングリファレンス。 hipMalloc, hipLaunchKernelGGL, HIP Graph, HIPRTC, hipify, rocBLAS, MIOpen, RCCL, rocprofv3, amd-smi, rocminfo, CDNA1-4 / RDNA1-4, MI300 / MI350, gfx942, Matrix Core, wave32/64。

Detects m6A modifications from Oxford Nanopore direct-RNA-sequencing (ONT DRS) signal data using m6Anet (Hendra 2022 *Nat Methods* 19:1590; multiple-instance-learning neural network over DRACH 5-mer signal). Covers the required upstream pipeline (Dorado / Guppy basecalling -> minimap2 transcriptome alignment with `-ax map-ont -uf -k14 --secondary=no` -> nanopolish eventalign with `--scale-events --signal-index` (m6Anet-required) plus `--summary` / `--threads` housekeeping -> m6anet dataprep -> m6anet inference), per-site vs per-read probability interpretation including the `mod_ratio` per-site stoichiometry column, the DRACH-only modeling constraint, minimum-coverage thresholds (20-50 reads per site for stable probability estimates), multi-condition comparison via xPore (Pratanwanich 2021 *Nat Biotechnol* 39:1394), Nanocompore (Leger 2021 *Nat Commun* 12:7198), ELIGOS (Jenjaroenpun 2021 *NAR* 49:e7), and Dorado native modification calling (RNA004 chemistry, 2024+), reference-transcriptome version pinning, the cDNA-vs-DRS chemistry distinction (cDNA-Nanopore CANNOT be used for modification detection), and orthogonal validation against MeRIP / GLORI. Use when calling m6A from ONT DRS without immunoprecipitation, choosing m6Anet vs xPore vs Nanocompore vs ELIGOS vs Dorado native, interpreting per-site `probability_modified` vs `mod_ratio` vs per-read modification probabilities, comparing methylation between conditions from ONT data, deciding between m6Anet for known DRACH sites and Dorado/Remora for genome-wide screening, pinning RNA002 vs RNA004 chemistry and basecaller model versions, or troubleshooting eventalign / dataprep failures.

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。

Automate Bunnycdn tasks via Rube MCP (Composio). Always search tools first for current schemas.

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。

Detects m6A modifications from Oxford Nanopore direct-RNA-sequencing (ONT DRS) signal data using m6Anet (Hendra 2022 *Nat Methods* 19:1590; multiple-instance-learning neural network over DRACH 5-mer signal). Covers the required upstream pipeline (Dorado / Guppy basecalling -> minimap2 transcriptome alignment with `-ax map-ont -uf -k14 --secondary=no` -> nanopolish eventalign with `--scale-events --signal-index` (m6Anet-required) plus `--summary` / `--threads` housekeeping -> m6anet dataprep -> m6anet inference), per-site vs per-read probability interpretation including the `mod_ratio` per-site stoichiometry column, the DRACH-only modeling constraint, minimum-coverage thresholds (20-50 reads per site for stable probability estimates), multi-condition comparison via xPore (Pratanwanich 2021 *Nat Biotechnol* 39:1394), Nanocompore (Leger 2021 *Nat Commun* 12:7198), ELIGOS (Jenjaroenpun 2021 *NAR* 49:e7), and Dorado native modification calling (RNA004 chemistry, 2024+), reference-transcriptome version pinning, the cDNA-vs-DRS chemistry distinction (cDNA-Nanopore CANNOT be used for modification detection), and orthogonal validation against MeRIP / GLORI. Use when calling m6A from ONT DRS without immunoprecipitation, choosing m6Anet vs xPore vs Nanocompore vs ELIGOS vs Dorado native, interpreting per-site `probability_modified` vs `mod_ratio` vs per-read modification probabilities, comparing methylation between conditions from ONT data, deciding between m6Anet for known DRACH sites and Dorado/Remora for genome-wide screening, pinning RNA002 vs RNA004 chemistry and basecaller model versions, or troubleshooting eventalign / dataprep failures.

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 patterns, cache-aside, write-through, TTL strategies, and invalidation. Activate on: caching, Redis, cache invalidation, cache-aside, write-through, TTL, CDN cache, stale-while-revalidate. NOT for: CDN/reverse proxy setup (use api-gateway-reverse-proxy-expert), database query optimization (use data-warehouse-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。

コードの構造を調べ、理解やテストを難しくしている箇所の改善案を図入りHTMLレポートにまとめます。候補を選んだ後は、制約や設計判断を対話で掘り下げます。

• 変更が多い領域の設計を見直したいとき
• リファクタリング案を図で比較
• テストしやすいモジュール設計を検討

ローカルの計画書やHTMLをブラウザで開き、該当箇所への注釈、チャット、承認や修正依頼を受け取るスキル。保存した変更が画面に反映され、レビューを続けられます。

• 実装計画のレビューと承認
• デザインの変更箇所を示したいとき
• レポートや比較資料への注釈