4,793 件 ・ 関連度順
概要と使いどころ
Especialista em containerização Docker com conhecimento profundo de multi-stage builds, otimização de imagens, segurança em containers, orquestração com Docker Compose e padrões de deploy em produção. Use PROATIVAMENTE para otimização de Dockerfile, problemas em containers, problemas de tamanho de imagem, hardening de segurança, networking e desafios de orquestração.
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。
Detect kernel-level rootkits in Linux memory dumps using Volatility3 linux plugins (check_syscall, lsmod, hidden_modules), rkhunter system scanning, and /proc vs /sys discrepancy analysis to identify hooked syscalls, hidden kernel modules, and tampered system structures.
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。
Role-based multi-model strategy. The model catalog lives in a local configuration file instead of the skill text -- roles (thinker/decision-maker, long-running worker, draft generator, reviewer/acceptance, escalation), reasoning effort as an independent axis, mandatory review for draft models, provider switching for independent reviews, budgets, delegation flow, and cost/quality of small workers.
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。
Builds a DRAFT month-end, quarter-end or year-end close checklist and status table for a finance team from the close calendar, the open items list and last month's close issues that the user attaches, pastes or the agent can reach, marks every task on time, due, late, at risk or blocked, and flags dependency chains and repeat issues. Use when the user asks to "build the close checklist", "where are we on the month-end close", "what is late or blocked in the close", "refresh the close tracker as of today" or "prepare the close status note". Do not use for a project tracker or weekly project status, use project-status-tracker instead; for corrective actions from audits or NCRs, use corrective-action-tracker. Drafts for human review; never approves, authorises or signs off.
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。
Docker containerization expert with deep knowledge of multi-stage builds, image optimization, container security, Docker Compose orchestration, and production deployment patterns. Use PROACTIVELY for Dockerfile optimization, container issues, image size problems, security hardening, networking, and orchestration challenges.
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。
Hardening Docker containers for production involves applying security best practices aligned with CIS Docker Benchmark v1.8.0 to minimize attack surface, prevent privilege escalation, and enforce leas
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。
Swift Design Systemを使用したiOS UI実装スキル。デザイントークン、UIコンポーネント（Button、Card、Chip、FAB、Snackbar、Picker等15種）、レイアウトパターンのベストプラクティスを提供。「デザイン」「UI」「テーマ」「カラー」「タイポグラフィ」「スペーシング」「ボタン」「カード」「FAB」「Snackbar」「Picker」「SwiftUI」「DesignSystem」などで自動適用。
PR の CI / マージ監視 (tools/pr-watch.sh) を broker tmux セッション内の専用ペイン pr-watch-<PR> で回す。窓口が PR 作成直後に `/pr-watch-pane <PR>` で起動すると、 ja-root cwd・sandbox 外で監視が走り、/clear や窓口セッション寿命と無関係に継続する。 pane name で冪等起動 (二重監視しない)、role=watcher で identity 登録、監視終了 (CI green / PR merged / timeout) で broker の tmux backend ならペイン自動 close (herdr / wezterm / renga のペインは tmux ペインでないため自動 close されず、窓口が 監視終端でイベント駆動 close する)。Bash tool の background は session 寿命依存で長時間 watcher には不適なので本 skill が推奨経路。 「CI 監視をペインで」「pr-watch をペインで回して」「PR <N> の CI を見張って」等で発動。
ワーカーから「判断仰ぎます」「承認を仰ぎます」「続行可否」「スコープ拡張提案」 「想定外」「runbook 逸脱」「ブロック / ブロッカー」等の peer message を受信した際、 窓口は一次承認せず人間にエスカレーションする。発動条件は worker からの judgment-escalation / scope-expansion / blocker メッセージ受信時。 通常の進捗 / 完了報告は org-delegate Step 5 (1) / (2a) で扱う。本スキルは 「自己解釈で承認しないための register 更新を含む正準フロー」を担当する。
Cross-Entity Disclosure Tracker App-in-Skill — a Busabase review workspace that helps a compliance/IR team assemble and track a standardized disclosure package per financing vehicle (fund/SPV), across a generic onshore origination entity, an offshore fund-manager entity, and a listing/exchange venue. Use when the user invokes $kelly-disclosure-tracker or /kelly-disclosure-tracker, wants to review disclosure checklists, vehicle readiness, cross-entity reconciliation flags, or reviewer notes across multiple financing vehicles. Review workspace only — it never files anything or calls any external system.
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。
Detect kernel-level rootkits in Linux memory dumps using Volatility3 linux plugins (check_syscall, lsmod, hidden_modules), rkhunter system scanning, and /proc vs /sys discrepancy analysis to identify hooked syscalls, hidden kernel modules, and tampered system structures.
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。
End-to-end biomarker discovery workflow from expression data to validated biomarker panels. Covers feature selection with Boruta/LASSO, leakage-safe cross-validation, calibration, and SHAP interpretation. Use when building and validating diagnostic or prognostic biomarker signatures from omics data.
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。
Packages an agent for CARLA Leaderboard submission — builds the docker image with make_docker.sh (plain or ROS variant), checks the four required roots and the egg layout it assumes, sets the agent/track/routes environment inside the image, and verifies the image can import the stack and load the agent before submission. Use when the user asks to "build the leaderboard docker image", "submit to the leaderboard", "package my agent", or make_docker.sh fails.
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。
Soc2 Compliance Checker - Auto-activating skill for Security Advanced. Triggers on: soc2 compliance checker, soc2 compliance checker Part of the Security Advanced skill category.
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。
Windows アプリ開発 (WinUI 3 / Windows App SDK) のコントロール API リファレンス。 Microsoft.UI.Xaml.Controls。Button, CheckBox, RadioButtons, ToggleSwitch, Slider, TextBox, RichEditBox, AutoSuggestBox, NumberBox, ListView, GridView, ItemsView, ItemsRepeater, TreeView, ComboBox, NavigationView, TabView, Frame, SplitView, BreadcrumbBar, ContentDialog, Flyout, CommandBar, TeachingTip, InfoBar, MediaPlayerElement, WebView2, CalendarView, DatePicker, ColorPicker, TitleBar。
TanStack Start (TanStack Router ベースのフルスタック React フレームワーク、 @tanstack/react-start) の API リファレンス。Next.js とは別フレームワーク。 createServerFn (validator / handler), createMiddleware, server routes, createServerOnlyFn / createIsomorphicFn、SSR / selective SSR / SPA mode / static prerendering / ISR、streaming、hydration、 server entry / client entry、hosting (Cloudflare Workers / Netlify / Vercel / Node / Bun / Docker)、authentication / session、Tailwind、SEO、 environment variables。ルーティングは tanstack-router スキルを参照。
Android アプリ開発 (Kotlin) のバックグラウンド・非同期処理リファレンス。 Jetpack androidx WorkManager: Worker, CoroutineWorker, WorkRequest, Constraints, WorkInfo, WorkContinuation, expedited work, テスト。 Service: フォアグラウンドサービス, バウンドサービス, AIDL, Messenger。 AlarmManager, PendingIntent, BroadcastReceiver, JobScheduler, Doze。 Kotlin コルーチン, Flow, StateFlow, SharedFlow, Channel。
Android Jetpack Compose (Kotlin) の androidx Material3 コンポーネントリファレンス。 Button, IconButton, FloatingActionButton, Checkbox, Switch, Slider, TextField, SearchBar, DropdownMenu, Chip, DatePicker, TimePicker, Card, Scaffold, Dialog, BottomSheet, TopAppBar, NavigationBar, NavigationRail, Tab, Snackbar, ProgressIndicator, Badge, Icon, MaterialTheme, ColorScheme, Typography, Shapes。
Apple グラフィックスフレームワークリファレンス。 Metal, Core Animation, Core Graphics, Core Image, SpriteKit, SceneKit。 MTLDevice, MTKView, MTLBuffer, MTLTexture, Metal 4 (MTL4CommandQueue, MTL4CommandBuffer, MTL4ArgumentTable), CALayer, CABasicAnimation, CADisplayLink, CAMetalDisplayLink, CAMetalDrawable, CGContext, CGPath, CGImage, CIFilter, CIContext, CIImage, CIRAWFilter, CIWarpKernel, CIBlendKernel, SKScene, SKSpriteNode, SKAction, SCNNode, SCNGeometry, SCNMaterial。
Assign cell types from marker expression in IMC/MIBI data using clustering (PhenoGraph/FlowSOM/Leiden/Pixie), marker-based probabilistic classifiers (Astir), or image-context CNNs (CellSighter), covering the double-positive segmentation artifact, lineage-vs-state markers, the two spillover types, and why a "cell type" in imaging is conditioned on a segmentation guess. Use when phenotyping segmented IMC cells, choosing clustering vs classification, diagnosing implausible double-positive populations, separating lineage from functional markers, or transferring labels across a cohort.
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。
Infers person-to-person transmission from pathogen genomes using outbreaker2 (Campbell 2018), TransPhylo (Didelot 2017), phybreak (Klinkenberg 2017), BadTrIP (De Maio 2018), SCOTTI (De Maio 2016), BEASTLIER (Hall 2015), and SNP-distance / cluster-picker approaches (HIV-TRACE for HIV; transcluster). Defines outbreak clusters using pathogen-specific SNP thresholds (NOT a universal cutoff -- TB <=12 SNPs / Walker 2013; MRSA <=15 / Coll 2017; C. difficile <=2 / Eyre 2013; Klebsiella <=21 / Snitkin 2012), models within-host diversity and transmission bottlenecks (Worby-Lipsitch-Hanage 2014; McCrone 2018; Sobel Leonard 2017; Lythgoe 2021 SARS-CoV-2), integrates contact-tracing data, distinguishes generation interval from serial interval (Britton & Scalia Tomba 2019; Ali 2020), attributes source via Bayesian source attribution (Mather 2013 DT104; islandR), and reconciles transmission-network reconstruction with epi metadata. Use when investigating outbreaks for who-infected-whom, defining SNP-cluster outbreak definitions, accounting for unsampled intermediates, choosing between outbreaker2 (rich epi data) and TransPhylo (genomic-only after dated phylogeny), running source attribution between host populations, calling HIV-TRACE thresholds appropriate to the local subtype, or distinguishing recent transmission from reactivation in TB / chronic HIV.
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。
Dockerfile, multi-stage build, Compose, buildx, registry, otimização e segurança de imagem. Use quando o usuário disser "docker", "dockerfile", "imagem", "container", "build", "compose", "imagem muito grande", "trivy", "vulnerabilidade na imagem".
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。
Assign cell types from marker expression in IMC/MIBI data using clustering (PhenoGraph/FlowSOM/Leiden/Pixie), marker-based probabilistic classifiers (Astir), or image-context CNNs (CellSighter), covering the double-positive segmentation artifact, lineage-vs-state markers, the two spillover types, and why a "cell type" in imaging is conditioned on a segmentation guess. Use when phenotyping segmented IMC cells, choosing clustering vs classification, diagnosing implausible double-positive populations, separating lineage from functional markers, or transferring labels across a cohort.
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。
Infers person-to-person transmission from pathogen genomes using outbreaker2 (Campbell 2018), TransPhylo (Didelot 2017), phybreak (Klinkenberg 2017), BadTrIP (De Maio 2018), SCOTTI (De Maio 2016), BEASTLIER (Hall 2015), and SNP-distance / cluster-picker approaches (HIV-TRACE for HIV; transcluster). Defines outbreak clusters using pathogen-specific SNP thresholds (NOT a universal cutoff -- TB <=12 SNPs / Walker 2013; MRSA <=15 / Coll 2017; C. difficile <=2 / Eyre 2013; Klebsiella <=21 / Snitkin 2012), models within-host diversity and transmission bottlenecks (Worby-Lipsitch-Hanage 2014; McCrone 2018; Sobel Leonard 2017; Lythgoe 2021 SARS-CoV-2), integrates contact-tracing data, distinguishes generation interval from serial interval (Britton & Scalia Tomba 2019; Ali 2020), attributes source via Bayesian source attribution (Mather 2013 DT104; islandR), and reconciles transmission-network reconstruction with epi metadata. Use when investigating outbreaks for who-infected-whom, defining SNP-cluster outbreak definitions, accounting for unsampled intermediates, choosing between outbreaker2 (rich epi data) and TransPhylo (genomic-only after dated phylogeny), running source attribution between host populations, calling HIV-TRACE thresholds appropriate to the local subtype, or distinguishing recent transmission from reactivation in TB / chronic HIV.
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。