1,882 件 ・ 人気順
概要と使いどころ
Use when working with Banana Dev — banana.dev ML inference platform management covering model inventory, deployment status, API call history, GPU allocation, scaling configuration, build logs, and latency metrics. Use for comprehensive Banana.dev model deployment assessment and inference performance 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 working with Betteruptime — better Uptime monitoring, status pages, incident management, on-call scheduling, and heartbeat tracking. Covers monitor configuration, response time analysis, incident lifecycle, on-call rotations, and SLA reporting. Use when managing uptime monitors, reviewing incident history, configuring on-call schedules, or analyzing response times in Better Uptime.
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 working with Baseten — baseten ML deployment platform management covering model inventory, deployment status, autoscaling configuration, inference call history, GPU allocation, environment management, and performance metrics. Use for comprehensive Baseten workspace assessment and ML serving optimization.
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 working with Snowflake — snowflake data warehouse analysis, query performance tuning, cost optimization, warehouse management, and schema inspection. Covers QUERY_HISTORY analysis, credit consumption, warehouse utilization, storage analysis, data sharing, and Time Travel. Read this skill before any Snowflake operations — it enforces two-phase execution, anti-hallucination rules, and read-only safety constraints.
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。
Hyperliquid market data, account history, trade review.
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。
Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.
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。
Evaluate recommender system quality for the CSX4207 Vinyl Record Store. Use whenever you must compute or report recommender metrics (Precision@k, Recall@k, HitRate@k, MRR, MAP@k, NDCG@k, coverage, diversity, novelty, serendipity, personalization), design an evaluation protocol/split, run a baseline comparison, or write the evaluation section of a course deliverable. Covers formulas, JavaScript reference implementations, and the reporting checklist.
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。
Generate user-facing App Store release notes from git history since the last tag.
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。
Product Inventor e Design Alchemist de nivel maximo — combina Product Thinking, Design Systems, UI Engineering, Psicologia Cognitiva, Storytelling e execucao impecavel nivel Jobs/Apple.
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 a user asks to "proofread", "review and correct", "fix grammar", "improve readability while keeping my voice", and to proofread a document file and save an updated version.
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。
Generate structured changelogs from git history. Use when user asks "what changed recently", "generate a changelog", "summarize commits" or user wants to understand recent development activity.
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。
Reads Copilot conversation history and extracts executive-ready success stories. Use when the user asks to study prior Copilot sessions, summarize what was done before, mine evidence, or quantify time, cost, risk, and priority alignment from GitHub Copilot history in any workspace or repository.
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。
Alternative Slowbar coffee intelligence — scientific analysis from seed to cup using First Principle + System Thinking. Covers: varieties, terroir, cultivation, disease diagnosis, processing, roasting physics/chemistry, extraction science, brewing, business strategy, storytelling. ALWAYS trigger for coffee-related questions requiring scientific depth. DO NOT trigger for simple recipes or general food questions. Style: science-driven, farmer-first, quality-obsessed.
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。
Authoritative reference for submitting tdmcp to the Anthropic Connectors Directory as a Codex Desktop Extension (MCPB). Use whenever drafting, checking, or fixing the submission — it defines the two submission paths, why tdmcp is a Desktop Extension (never a remote connector), every form field, the rejection-causing gates, and the local-only compliance story. Read this before writing any submission deliverable.
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。
Survey one surface of tdmcp (artist controls, library/packaging, CLI/DX, AI/LLM, or TouchDesigner depth) for candidate NEW features — inventory what exists, cross-check the roadmap, apply the gap-finding lenses, vet each idea, and emit a structured, novelty- and confidence-labelled candidate list to _workspace/discovery/. Use when a td-surveyor agent is scouting a surface during the feature-discovery harness.
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。
ユーザー本人の声で日本語のプローズを起草・推敲・レビューする際に文体ガイドを適用する。対象は Qiita/Zenn 技術記事、note 記事、Slack メッセージ下書き、ユーザーが書く PR/コードレビューコメント、その他ユーザー名義で外部に出る日本語の長文。基本トーン・句読点ルール・用語表記・禁止表現（em ダッシュ「——」、「刺さる/効く」、「リポ」略称など）・シチュエーション別温度感を読み込んだ上で文章を組み立てる。コード・ログ・コミットメッセージの定型文、および他者が書いた文章のレビュー（他人の PR コメントの校正など）には適用しない。
技術記事の並列レビュー Council。anti-ai-slop / fact-checker / narrative-critic / reader-advocate を並列 spawn、severity 付き findings を最大3ラウンドで収束。Zenn などのドラフト完成後に使う。「記事レビュー」「editorial swarm」「編集会議」「記事推敲」「記事添削」で発動。
Japanese document co-authoring and editing assistant with proofreading checklist, keigo adjustment, essay structure patterns (起承転結, PREP), and revision tracking. Triggers on requests for 文章推敲, 共同執筆, 文章校正, 敬語調整, 文体統一, レビュー依頼, ドキュメント編集.
Create user-facing App Store release notes by collecting and summarizing all user-impacting changes since the last git tag (or a specified ref). Use when asked to generate a comprehensive release changelog, App Store "What's New" text, or release notes based on git history or tags.
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 someone asks to write, rewrite, review, or improve text that appears inside a product or interface. Examples: "review the UX copy", "is there a better way to phrase this", "rewrite this error message", "write copy for this screen/flow/page", reviewing button labels, improving CLI output messages, writing onboarding copy, settings descriptions, or confirmation dialogs. Trigger whenever the request involves wording shown to end users inside software — apps, web, CLI, email notifications, modals, tooltips, empty states, or alerts. Also trigger for vague requests like "review the UX" where interface copy review is implied. Do NOT trigger for content marketing, blog posts, app store listings, API docs, brand guides, cover letters, or interview questions — this is a technical writing skill for interface language.
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 personal brand assets using Seth Godin's frameworks: signature symbol, slogan, surprise (Purple Cow), salient idea, and signature story. Use when named (branding), or when the user asks for a brand symbol, slogan, tagline, Purple Cow, counterintuitive angle, core idea, brand story, or personal brand positioning.
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 or improve a job seeker's resume.md source file from conversational career input. Use when the user wants to create resume.md, organize new-grad or experienced career history, convert raw experiences into STAR/CAR evidence, add missing metrics, or prepare reusable career evidence for cover letters and job applications. 한국어 요청도 포함합니다 - 이력서 작성, 이력서 정리, 경력기술서, 경력 정리, 커리어 정리, 자소서 소재 정리, 내 경험 정리해줘, 신입 이력서, 경력직 이력서.
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 this skill when writing or editing Japanese documentation, teaching material, comments, or explanations for this template (Sabakyan style). Trigger words: ドキュメント執筆, 教材, 解説を書く, 日本語スタイル, README 作成, 説明文, サバキャン, わかりやすく書く.
This skill should be used when the user asks to "proofread", "校正", "誤字脱字チェック", "表記揺れ", "typo check", "文書チェック", "法律文書の確認", "この書面チェックして", "おかしいところない？", "文章確認して", "間違いがないか確認", "書面の確認", or wants to review a Japanese legal document for writing errors. Do NOT trigger for translation, summarization, or content generation requests.