「age」の検索結果

フロントエンドのチェック項目に合うnpmパッケージを調査し、利用数と更新時期の基準を満たす候補を選び、ルールファイルのメタデータに追記するスキル。

• チェック項目にnpmの参照を加えたいとき
• 利用数と公開時期で候補を絞りたいとき
• ルールの検出・修正・テスト用ツール探し

画像ファイル名を点検し、内容が伝わる小文字・ハイフン区切りの名前へ整理します。変更に伴う参照先の更新も扱い、画像検索と素材管理に役立てます。

• 商品画像の名前を見直したいとき
• 画像ライブラリの命名統一
• 画像の一括改名と参照更新

画像の読み込みに失敗したときの表示を点検し、代替画像や意味のあるプレースホルダーの実装を支援します。エラーログや読み込み中の表示、修正の確認方法も扱います。

• リンク切れ画像の代替表示を整えたいとき
• 画像読み込み中の仮表示の見直し
• ログとDevToolsで画像エラーを調査

読み込み中に画像や広告でページの配置がずれる原因を測定し、表示領域の確保やフォント・アニメーションの見直しで、誤クリックや読書の中断を減らす改善を支援します。

• 読み込み中に内容が動く原因を調べたいとき
• 画像・埋め込み・広告の表示領域を確保
• フォントやアニメーションの安定性確認

OpenSpecのドキュメントを、利用者と構成を相談しながら節ごとに執筆します。ページ内に目的と作業計画を記録し、承認した手順で草稿を作成して、関連リンクの更新まで進めます。

• 新しい文書の構成を相談したいとき
• 既存ページを一から書き直したいとき
• 節ごとに確認して執筆したいとき

プロジェクトの言語に合う言語サーバーを検出・導入・設定し、エラー診断や定義への移動、参照検索、名前変更をエージェントから使えるよう動作確認まで行うスキル。

• LSP未設定エラーを解消したいとき
• 新規プロジェクトの言語ツール導入
• 定義への移動や参照検索の有効化

AI開発の実践課題を一段階ずつ進め、予測・実装・採点・振り返りを通じて学ぶスキル。完成コードに頼らず、ヒントを受けながら自分で書き、進捗を記録します。

• 実践課題でAI開発を学びたいとき
• 中断したプロジェクトを再開したいとき
• ヒントで実装ミスを解きたいとき

写真やイラスト、商品画像などを生成し、既存画像の背景変更や不要物の除去も行います。参考画像を使う別案づくりや、背景が透明な素材の作成にも対応します。

• Webサイト用の写真やイラスト作成
• 商品写真の背景変更や不要物の除去
• 背景が透明な切り抜き素材の作成

When the user wants to optimize, improve, or increase conversions on any marketing page or form — including homepage, landing pages, pricing pages, feature pages, lead capture forms, or contact forms. Also use when the user says 'CRO,' 'conversion rate optimization,' 'this page isn't converting,' 'improve conversions,' 'why isn't this page working,' 'my landing page sucks,' 'form abandonment,' 'nobody's converting,' 'low conversion rate,' or 'this page needs work.' Use this even if the user just shares a URL and asks for feedback. For signup/registration flows, see signup. For post-signup activation, see onboarding. For popups/modals, see popups.

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。

设计或评审多 Agent 系统、判断该用单 Agent 还是多 Agent 时使用——选择对等/管理者/去中心化协作拓扑、决定上下文是否共享、设计 Agent 间通信与共享文件系统、诊断多 Agent 失败模式（并发冲突、错误级联、同质趋同、互相扯皮、循环失控）。覆盖协作架构选择依据、多 Agent 优于单 Agent 的新信息判据、控制平面四原语与虚拟文件系统四类区域的设计检查表。

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。

Looks up precomputed AlphaGenome Atlas effects for any GRCh38 single-nucleotide variant (AVI score with Phred and 18 SHAP feature attributions, plus raw and quantile scores for RNA-seq, DNase, ATAC, ChIP-TF, ChIP-histone, CAGE, PRO-cap, splicing, polyadenylation and contact-map tracks), scores variants or scans windows on demand with the AlphaGenome model for human and mouse (variant scoring, in silico mutagenesis, REF-versus-ALT track prediction), and builds Atlas website deep links. Use when the user mentions AlphaGenome, AlphaGenome Atlas, AVI or AlphaGenome Variant Impact, DeepMind variant effect prediction, or wants to prioritise or mechanistically interpret non-coding, regulatory, splicing, enhancer, promoter, or chromatin-accessibility effects of SNVs from a VCF, credible set, or region. Research use only; not a clinical tool.

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 and orchestrate parallel agents using the standalone Antigravity 2.0 Agent Manager and Antigravity IDE.

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。

Brand-first landing page designer — runs a brand-identity interview (colors, typography, shape language), then generates and iterates on a polished landing page via Stitch with deployment-ready HTML. Use when the user asks to create, design, or build a landing page, homepage, or marketing page and has no established visual direction. Skip when they have a design mockup, need a dashboard or app UI, are working at component level, building a multi-page app, or restyling with known design tokens — use frontend-design instead.

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。

When the user wants to create SEO-driven pages at scale using templates and data. Also use when the user mentions "programmatic SEO," "template pages," "pages at scale," "directory pages," "location pages," "[keyword] + [city] pages," "comparison pages," "integration pages," or "building many pages for SEO." For auditing existing SEO issues, see seo-audit.

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。

Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image 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。

When the user wants to create SEO-driven pages at scale using templates and data. Also use when the user mentions "programmatic SEO," "template pages," "pages at scale," "directory pages," "location pages," "[keyword] + [city] pages," "comparison pages," "integration pages," or "building many pages for SEO." For auditing existing SEO issues, see seo-audit.

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。

Diagnoses GKE persistent-storage failures — volume attach/mount errors (Regional PD on optimized VMs, fsGroup mount timeouts), disk-performance and node storage-pressure issues, slow-disk Pod-creation failures, volume-expansion problems, Local SSD / Hyperdisk Storage Pool creation errors, and Cloud Storage FUSE OOM. Use when Pods are stuck in ContainerCreating, volumes fail to attach or mount, or nodes report storage pressure. Don't use for routine storage provisioning or StorageClass/PVC authoring (see the gke-storage skill).

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。

Manages GKE storage, including PVCs, PersistentVolumes, and Filestore. Use when configuring GKE storage or creating PVCs. For GCS FUSE mounts, use google-cloud-storage-fuse. For diagnosing storage failures (volume attach/mount errors, disk performance/node storage pressure, or Cloud Storage FUSE OOM), use gke-storage-troubleshooting. Don't use for database administration or replication strategies outside volume provisioning context.

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。

Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models. Supports multi-turn image chat, visual question answering, and instruction following. Use for vision-language chatbots or image understanding tasks. Best for conversational image 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。

Use when configuring Django to store static and media files on AWS S3 with django-storages. Invoke when working with the STORAGES setting, S3 buckets, presigned URLs, CloudFront, or boto3-backed file storage in settings.py. Configures the Django 4.2+ STORAGES dict, public/private custom backends, presigned GET/POST URLs, IAM policies, and S3 mocking for tests. Trigger terms: django-storages, S3, boto3, S3Boto3Storage, STORAGES, presigned URL, CloudFront, media files, collectstatic, AWS_STORAGE_BUCKET_NAME.

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。

Deep-dive offensive methodology for dependency confusion and namespace attacks across all major package ecosystems. Covers npm scope confusion exploiting the gap between public and private scoped packages and .npmrc misconfigurations where registry mappings fail to pin internal scopes exclusively. Addresses PyPI namespace attacks through --extra-index-url resolution ordering, NuGet feed priority exploitation when multiple package sources are configured without clear directives, Maven and Gradle repository ordering where artifact resolution traverses repositories sequentially, Go module proxy abuse through GOPROXY misconfiguration, Ruby gems namespace squatting, and Docker image tag confusion with unqualified image references. Provides complete proof-of-concept methodology using safe callbacks including DNS canary via interactsh or Burp Collaborator and HTTP beacon with no destructive payload. Covers reconnaissance techniques for discovering internal package names through GitHub repository analysis, error message harvesting, JavaScript source map extraction, lock file parsing, job postings mentioning internal tools, and package manifest inspection. Directly references and builds upon Alex Birsan's seminal 2021 dependency confusion research. Each ecosystem section includes registry-specific exploitation mechanics, configuration vulnerabilities, and defensive countermeasures for engagement reporting.

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。

Creates Cursor-specific AI subagents with isolated context for complex multi-step workflows. Use when creating subagents for Cursor editor specifically, following Cursor's patterns and directories (.cursor/agents/). Triggers on "cursor subagent", "cursor agent". Do NOT use for generic subagent creation outside Cursor (use subagent-creator instead).

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。

Amazon search and category listing scraper: extract product listings from any Amazon search results page, keyword search URL, or category browse page and return per-item cards (asin, title, url, image, price, listPrice, stars, reviewCount, badges, isAmazonChoice, isBestSeller, isSponsored, delivery, boughtInPast, positionIndex) plus pagination state (currentPage, hasNextPage, nextPageUrl, totalResultsApprox). Works across all Amazon regional TLDs (amazon.com, amazon.co.uk, amazon.de, amazon.co.jp, amazon.in, amazon.fr, amazon.ca, amazon.com.au, amazon.it, amazon.es, amazon.com.mx, amazon.com.br, amazon.nl, amazon.se, amazon.sg, amazon.ae, amazon.sa, amazon.pl, amazon.tr, amazon.eg). Use when user mentions Amazon, amazon.com, Amazon SERP, Amazon search results, Amazon keyword search, Amazon category page, Amazon subcategory URL, scrape Amazon listings, extract Amazon search, Amazon product cards, Amazon browse page, Amazon /s URL, Amazon /s?k= URL, Amazon /b/ category URL, Amazon /gp/browse category, Amazon bbn category filter, Amazon rh filter, Amazon search pagination, Amazon 7 pages limit, Amazon subcategory scraper, Amazon keyword scraper, Amazon SERP scraper, Amazon by URL, Amazon by category, Amazon by keyword. Also applies to price monitoring across a keyword or category, competitive listing tracking on Amazon, brand keyword ranking on Amazon, category catalog audits, best-of category discovery from a search, paginated bulk extraction of Amazon search hits, and building ASIN lists from a search.

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。

This skill should be used when the user wants to "create an agent project", "start a new ADK project", "build me a new agent", "add CI/CD to my project", "add deployment", "enhance my project", or "upgrade my project". Part of the agents-cli skills suite. Covers `agents-cli scaffold create`, `scaffold enhance`, and `scaffold upgrade` commands, template options, deployment targets, and the prototype-first workflow. Do NOT use for writing agent code (ADK projects: use google-agents-cli-adk-code) or deployment operations (use google-agents-cli-deploy).

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。