2,516 件 ・ 関連度順
概要と使いどころ
Use when working with Ansible — ansible automation and configuration management. Covers playbook execution, inventory management, role management, vault secrets, ad-hoc commands, fact gathering, and task debugging. Use when running playbooks, managing inventories, debugging task failures, or auditing Ansible configurations.
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 only when the user explicitly requests strict code-cell-only output for a Jupyter or undergraduate data-science task, or when an ITX2007 assignment requires that format. Do not activate for ordinary data analysis or explanation requests.
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 produits digitaux avancé (ebooks, templates, presets, Notion, courses)
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。
Digital product builder — Ebooks, templates, presets, Notion templates, Gumroad setup
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。
Design System Builder IA — Expert en construction de design systems (Storybook, tokens, component API, theming, Figma sync)
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 construction de design systems avancés (tokens, composants, Storybook, Figma sync, versioning, theming)
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 Ansible (playbooks, roles, inventory, Galaxy, configuration idempotente)
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。
AI vocal agents — Vapi, Airtable, phone answering, booking, 24/7, DZ market
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。
Production-ready templates for incident response runbooks covering detection, triage, mitigation, resolution, and communication.
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。
Updates tdmcp docs and roadmap for newly shipped or newly merged capabilities. Use when asked to update docs, update the roadmap, reconcile release docs, document new features, sync docs with CHANGELOG/package release, refresh cookbook examples after a feature wave, re-run/continue/fix a docs-roadmap pass, or check whether docs/ROADMAP.md is current. Runs a sub-agent workflow: release audit -> roadmap/docs edit + cookbook sync -> QA.
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 asks to "calculate traffic accident damages", "交通事故の損害額を計算", "損害賠償額を算出", "赤い本基準で計算", "逸失利益を計算", "後遺障害の慰謝料", "過失相殺後の金額", or wants deterministic computation of personal-injury damages under the Red Book (赤い本) standard.
Analyze competitor strategies, content, pricing, ads, and market positioning across Google Maps, Booking.com, Facebook, Instagram, YouTube, and TikTok.
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。
Analyze market conditions, geographic opportunities, pricing, consumer behavior, and product validation across Google Maps, Facebook, Instagram, Booking.com, and TripAdvisor.
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。
Decomposition playbook + anti-temptation rules for an orchestrator profile routing work through Kanban. The "don't do the work yourself" rule and the basic lifecycle are auto-injected into every kanban worker's system prompt; this skill is the deeper playbook when you're specifically playing the orchestrator role.
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。
penpotを含む場合は必ず読み込む。セルフホスト環境管理、MCP経由デザインシステム構築・ UI/UXデザイン作成・プロトタイプ参照、デザインからのアプリケーション生成、 外部パイプライン（トークン同期・Style Dictionary・Storybook）、デザインレビュー・コメント操作。
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。
Execute model inference on GPU cloud providers. Handles code generation, deployment, execution, and result collection across HF Inference API/Endpoints, Colab, Modal, beam.cloud, Vast.ai, and RunPod. Use when running models on GPU, deploying to cloud, executing notebooks, or troubleshooting GPU execution failures. Triggers on "run on GPU", "execute model", "deploy to modal", "colab notebook", "beam deploy", "HF inference", "HF endpoints", "vast", "runpod".
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。
Meta-skill that generates compliant PLAYBOOK.md files following the BRAINIAC template. Use when creating or editing modules in the command center. For general readme creation, see create-readme.
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。
Social media command desk (Busabase App-in-Skill) for Kelly's Twitter/X, Facebook, and Instagram accounts (extensible to LinkedIn, YouTube, Threads, TikTok, Xiaohongshu), covering cross-platform monitoring and ECHO-based publishing. Use when the user invokes $kelly-social or /kelly-social, wants cross-platform account metrics and timelines, or needs a content calendar, draft review, engagement inbox, crisis playbook, share-of-voice, or pre-publish quality gate.
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 and operate a Busabase-backed mainland China A-share strategy experiment desk with a bundled local Hono App-in-Skill, evidence-backed strategy research, strategy-level L1/L2/L3 manual maturity approvals, one CNY virtual ledger per strategy, and dated strategy backtest reports. Use when the user invokes $kelly-invest-stock or /kelly-invest-stock, wants to define or compare A-share strategies, inspect a strategy and its virtual book, record research evidence, manually approve strategy maturity, or review dated backtests, drawdown, and contribution to the total book. It never connects to a brokerage, places orders, moves money, or presents generated analysis as personalized investment advice.
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。
Friendly elementary-school homework tutoring App-in-Skill. Use when the user invokes $kelly-homework-coach or /kelly-homework-coach, mentions 小学生作业辅导, homework photo tutoring, 拍照讲题, 作业答疑, 错题本, error notebook, mistake-book review, practice paper generation, exam paper analysis, parent/teacher review of AI explanations, or wants a child-friendly UI for step-by-step homework help with parent/teacher review and safety boundaries.
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。
Busabase App-in-Skill dashboard over a fixed, deterministic mock user-behavior funnel dataset (browse → search → compare → booking attempt/abandon → complete) for a generic consumer booking product. Use when the user invokes $kelly-behavior-predict or /kelly-behavior-predict, wants to review funnel drop-off, per-segment predicted next actions, or backtest a rule-based "predicted next action" heuristic against a mock historical sample. Fully deterministic mock data and a hand-recomputable rule — never a real ML/LLM model, never a live 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。
Generates standard operating procedures for B2B SaaS marketing operations: campaign naming conventions, UTM governance, tool administration, workflow QA, data hygiene, lead routing, and incident response playbooks. Use when setting up or auditing marketing ops processes, onboarding a new marketing ops hire, standardizing campaign tracking, fixing broken lead routing, cleaning up HubSpot or CRM data, building QA checklists for campaign launches, or creating incident response procedures for marketing system failures. Also use when asked to "fix our UTM mess," "standardize campaign naming," "build a QA checklist," "audit our marketing ops," or "create an ops runbook." Designed for B2B SaaS marketing teams running HubSpot with multi-geo, multi-segment operations.
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。
Facebook's library for efficient similarity search and clustering of dense vectors. Supports billions of vectors, GPU acceleration, and various index types (Flat, IVF, HNSW). Use for fast k-NN search, large-scale vector retrieval, or when you need pure similarity search without metadata. Best for high-performance applications.
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。