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概要と使いどころ
Transforms research findings into executive-ready briefings. Automatically activated when user mentions 'executive', 'briefing', 'C-suite', 'board', 'leadership', or 'presentation'.
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。
Doctrine for drafting and keeping working-group docs under `docs/wg/**` — RFC/RFD specs and findings/research/glossary. A WG doc is a language-agnostic, code-agnostic study of a domain: it argues *why* and defines *what*, never *how in our code*. Use when writing or editing anything under `docs/wg/`, an RFC/RFD, a spec, a design note, a glossary, or research findings — including "write up the design", "document the spec", or "capture what we learned". Not for plans/TODOs (untracked `*.plan.md`), user docs, or SDK API refs — use `docs` to route those.
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。
Decide which family a doc belongs to before drafting — SDK/developer, user/product, or working-group (WG) — since family sets the audience, home, and tone. Use when creating, moving, or restructuring docs, when unsure which directory a doc belongs in, or when a request says "document this" / "write docs for X" without naming the kind. Routes to the specialized skill for each family.
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。
Make short product / skill motion videos (10–30 s, narrated feature demos up to ~60 s) the way high-end launch clips are made — kinetic type, real UI as the material, a hand that causes every reaction, beats that carry into each other instead of replacing each other, hard cuts only where they mean something — without HyperFrames or Remotion. A single HTML composition where every value is a pure function of time, built from a library of measured moves (springs, entrances, carries, contact, camera), rendered frame by frame with real shutter motion blur (1080p30 drafts, 4K60 final), with synthesised sound effects that share one room and an oracle that fails a slideshow before a human has to watch it. Use for 做个动效短片 / 产品宣传片 / 介绍视频 / 发布视频 / 15 秒 launch video / 给 skill 或 app 做个视频 / promo / teaser, for turning real pages or screen recordings into a cut, for product feature demos (产品功能演示 / 功能展示动效) where the UI is rebuilt in HTML from screenshots instead of screen-recorded (不录屏 / 复刻界面 / 截图还原 UI), for narrated cuts with voice-over and subtitles (配音 / 字幕 / 换配音) and for the same film in other languages (日语版 / 多语言 / 本地化), for adding motion vocabulary (动效库 / 转场 / 衔接), and for auditing why a motion video reads as a slideshow (像 PPT / 没节奏 / 一个一个展示 / 转场生硬).
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。
Spawn the comment-sicko subagent, fix accepted findings, and offer encodings for claimed 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。
When the user wants to analyze, respond to, or improve their app reviews and ratings. Also use when the user mentions "reviews", "ratings", "negative reviews", "how to get more reviews", "review response", or "my rating is dropping". For broader ASO audit, see aso-audit. For retention issues causing bad reviews, see retention-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。
When the user wants to optimize their Google Play Store listing — title, short description, full description, keywords, ratings, or Play Store-specific features. Use when the user mentions "Google Play", "Android", "Play Store", "Play Console", "short description", "full description indexed", "Google Play ASO", or wants Google Play-specific keyword, creative, or ratings strategy. For iOS App Store optimization, see aso-audit and metadata-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。
How to pull SEC EDGAR data with the edgartools Python package — company lookup, filings, XBRL financial statements, and filing sections like Item 1A risk factors. Use whenever a task involves SEC filings, 10-K/10-Q data, or company financials.
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。
Adversarial dual-model code review that runs two AI models in parallel, cross-references findings, and produces a consensus severity table with fix confidence ratings. Use when asked for a thorough code review, adversarial review, dual-model review, confidence-rated review, or 'Hanselman 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。
Plans, runs, and synthesizes customer research — interviews, surveys, win-loss analysis, and message testing — into findings that change decisions. Use this when the customer is being guessed at, before positioning or a major launch, when churn or conversion has an unexplained cause, or when a team is arguing from anecdotes. Also use to turn raw interview notes into usable findings.
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。
Create engaging Xiaohongshu (RED/小红书) content including titles, body text, hashtags, and image style recommendations. Supports multiple content types such as product reviews, tutorials, lifestyle sharing, and shopping guides with platform-specific 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。
NetEase Cloud Music skill for searching songs, managing playlists, getting personalized recommendations, and controlling playback via ncm-cli. Use when user wants to search music, play songs, manage playlists, or get music recommendations.
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。
Verifies whether a scientific or biomedical claim is actually supported by the cited original papers rather than by citation drift, overstatement, selective citation, or correlation-to-causation inflation. Use this skill whenever a user wants to check whether a repeated statement, slide claim, manuscript sentence, review assertion, or “people often say” scientific conclusion is truly supported by the underlying primary literature. Always separate the claim itself, the cited paper(s), what the paper actually showed, what it did not show, and whether later retellings drifted beyond the original evidence. Never fabricate references, findings, study features, or citation chains.
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。
Rewrites technical research content into a structured lay summary that cross-disciplinary teams can quickly understand and act on. Use when the user wants to explain research to colleagues outside their specialty — clinicians, wet-lab scientists, bioinformaticians, product managers, or leadership. Trigger on: "lay summary", "explain my research to the team", "non-technical summary", "cross-disciplinary summary", "translate my findings", "align our team on the study", or any request to communicate research goals, findings, or next steps to a mixed or non-specialist audience. Part of the AIPOCH Academic Writing skill hub. Sits midstream: after research content is clarified, before downstream deliverables like slide decks or graphical abstracts.
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。
Spawn Comment Sicko, fix accepted findings, and offer encodings for claimed 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。
Perform various data analysis on SEC 13-F and obtain some insights of fund activities such as number of holdings, AUM, and change of holdings between two quarters.
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。
Choose and implement clustering algorithms for grouping speaker embeddings after VAD and embedding extraction. Compare Hierarchical clustering (auto-tunes speaker count), KMeans (fast, requires known count), and Agglomerative clustering (fixed clusters). Use Hierarchical clustering when speaker count is unknown, KMeans when count is known, and always normalize embeddings before clustering.
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。
LangSmith tracing and debugging setup for LLM applications. Configure observability, capture traces, and enable debugging for LangChain/LangGraph agents.
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。
Gestaltet Darlehens- und Finanzierungsbedingungen mit Prüfung von Bearbeitungsentgelten, Pflichtangaben, Zinsänderung und vorzeitiger Rückzahlung. Trennt Kreditgeber, Händler und Vermittler sowie B2B und Verbraucherkredit.
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。
Für Zahlungsverzug Mahnkosten: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.
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。
Prüft, ob AGB-Änderungen durch ausdrückliche Zustimmung, Schweigen oder Weiternutzung wirksam vereinbart werden können. Für Änderungsmitteilungen einschließlich Bankbedingungen; liefert Zustimmungsweg, Beweisplan und konkrete Fassung.
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。
Für Zahlungsmittel Chargeback: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.
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。
Für Beweismittel-Katalog: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Beweislast- und Substantiierungsmatrix.
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。
Für Zahlungsdienste AGB: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.
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。