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概要と使いどころ
Verifies a completion, fix, passing, compatibility, release, or readiness claim with fresh task-specific evidence mapped to the actual requirements. Use before saying a change is done, before merge, after review fixes, and at release gates. Not a substitute for diagnosing the cause of a failing check.
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 a soak test protocol for extended play sessions. Defines what to observe, measure, and log during long play sessions to surface slow leaks, fatigue effects, and edge cases that only appear after sustained play. Primarily used in Polish and Release phases.
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 a comprehensive pre-release validation checklist covering build verification, certification requirements, store metadata, and launch readiness.
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 @aleabitoreddit ("Serenity")'s full mention archive (built by the follow-aleabito skill) to anticipate where her attention is moving and generate candidate ideas in her style. Two modes — (1) RADAR reads the live mention data for attention momentum (which tickers she is heating up on, new entrants, conviction core, theme rotation) via scripts/radar.js; (2) GENERATOR applies her empirically-mined patterns (theme-rotation logic, selection signature, catalyst playbook) to propose her likely next focus. Every candidate is gated through the serenity-method checklist. This is a CANDIDATE GENERATOR + CHECKLIST, never an oracle or buy/sell signal. Trigger on "what is Serenity ramping on / her next pick / aleabito radar / predict her next move / generate ideas like her / 她下一个可能看什么".
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 preparing a PlainTab release or bumping the PlainTab version, triggered by phrases like "更新版本", "bump version", "upgrade to vX.Y.Z", "发布新版本". Updates manifest.json, runtime UI/version constants, localized changelogs, store listings, release notes, validation notes, and current project docs.
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。
Nexscope Ozon category product search: fetches the product list for a given Ozon category ID, returning category-level aggregates (total sales, total revenue, average price, average rating, seasonality) and per-product sales, price, rating, review count, brand, seller, and fulfillment method. Use for category selection analysis, category bestseller mining, category capacity and price band analysis, seasonality assessment. Trigger when the user mentions Ozon category products, Ozon category analysis, Ozon category selection, Ozon category bestsellers, Ozon category total sales, Ozon category average price, Ozon category search, Ozon category products, category best-sellers, category analysis. Also trigger when the intent is to view products and category-level summary data within an Ozon category, even without explicitly mentioning Nexscope.
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。
Google Trends keyword search popularity comparison and trend analysis, supporting global regions and custom time ranges. Triggered by: Google Trends, keyword popularity over time, search interest comparison, keyword trend analysis, seasonal trend detection, regional search popularity, keyword heatmap, multi-keyword comparison on Google, keyword research, market trend analysis, search trends, seasonal analysis, regional popularity.
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。
Query and analyze Amazon ABA (Brand Analytics) search term data, covering 15 marketplaces with nearly 3 years of weekly data. Trigger when the user mentions ABA data, Amazon search term analysis, keyword mining, search ranking trends, market opportunity analysis, seasonal keywords, high-click low-conversion analysis, blue ocean keyword discovery, competitor keyword analysis, ABA data, search term report, keyword mining, search ranking trends, blue ocean keywords, click share, conversion share, seasonal keywords, market opportunity analysis, competitor keywords. Even if the user does not explicitly mention "ABA", if their need involves Amazon search term data and ranking analysis, this skill should also be triggered.
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。
Nexscope keyword historical search volume query, returning Amazon keyword exact search volume trends in 7-day periods, covering 10 marketplaces including US, UK, DE, JP, etc. Trigger when the user mentions keyword search volume trends, historical search volume, search popularity changes, keyword seasonality, search volume fluctuations, Nexscope search volume, keyword search volume history, keyword trend, search volume over time, seasonal search volume, keyword popularity trend. Even if the user does not explicitly mention "Nexscope", if their need involves viewing the search volume trend of an Amazon keyword over time, this skill should also be triggered.
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。
Multi-dimensional Amazon product search and filtering based on Nexscope data, covering 14 marketplaces, with support for historical monthly snapshot lookback. Trigger when the user mentions Nexscope product search, Amazon product filtering, competitor research, category analysis, brand bestsellers, seller analysis, seasonal products, historical snapshot review, product search, monthly sales/revenue, ABA keyword product discovery, price range filtering, new product discovery, multi-condition combined filtering, product search, competitor research, category analysis, brand bestsellers, seller analysis, seasonal products, historical snapshot. Even if the user does not explicitly mention "Nexscope", if their need involves Amazon product search, filtering, comparison, or product exploration by category/brand/seller dimensions, this skill should also be triggered.
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。
Implement ReasoningBank adaptive learning with AgentDB's 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.
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。
Implement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.
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。
Periodically scan project dependencies for security vulnerabilities, outdated packages, and unused dependencies. Produces a prioritized action report. Run before every major release and at least once per month.
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。
Verify mini-program implementations and fixes with risk-calibrated evidence across static checks, unit tests, integration tests, state matrices, simulators, real devices, cloud environments, and release artifacts. Use when users ask to test, validate, accept, regression-check, quality-check, confirm readiness, or determine whether a mini-program feature is actually complete. Binds results to a source and build fingerprint, records commands and observable evidence, separates passed, failed, blocked, and not-run layers, prioritizes the next highest-information check, and never converts local success into device, cloud, release, or formal acceptance claims.
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。
Orchestrate evidence-first engineering for WeChat and other mini programs from a vague idea or existing repository through project discovery, product specification, architecture, implementation, debugging, device adaptation, verification, and release readiness. Use when users ask to build a mini program from zero to one, take over an existing mini-program project, deliver a cross-stage feature, diagnose project status, coordinate development and testing, or judge whether a mini program is ready to upload or release. Enforces fact discovery, change boundaries, stage gates, evidence-calibrated status, sensitive-information redaction, and continuity after side questions.
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 scaffolds that gradually increase student choice, voice, and ownership within a learning task. Use when students depend heavily on teacher direction and need to develop autonomy.
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 and evaluate grounded ideas. Use when the user asks for ideas, improvements, surprising options, or AI-generated directions before choosing one to develop; use ce-brainstorm to refine the user's own idea.
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 evaluating biology grant ideas in the Chinese funding context (NSFC, MOST, etc.) — diagnosing project legitimacy, mechanism-centered scientific questions, reviewer-aware logic, innovation discipline, feasibility, and scope control across funding levels (youth, general, key).
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 Agent Workflow & Skill Architecture Guide — turn expert work into measurable, reusable agent systems. Covers workflow discovery, skill decomposition, harness design, evaluation, human escalation, observability, cost control, and multi-agent orchestration. Includes a measured marketing-delivery case: 15 people × 3–4 weeks reduced to one strategist + AI in 5 days. By Gingiris.
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, prioritize and run measurable growth experiments across acquisition, activation, retention, referral and revenue. Use when a startup needs an experiment backlog, ICE/RICE prioritization, referral or UGC loops, rapid weekly testing, causal measurement, or stop conditions without spam, fake accounts or dark patterns.
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。
Vercel AI Elements for workflow UI components. Use when building chat interfaces, displaying tool execution, showing reasoning/thinking, or creating job queues. Triggers on ai-elements, Queue, Confirmation, Tool, Reasoning, Shimmer, Loader, Message, Conversation, PromptInput.
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 release notes for changes since a given 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。
Add or modify a GitHub Actions job. Use when editing a file under .github/workflows/. Not for running a workflow locally (local-ci-act) or release signing (release-signing).
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。
Kontextspezifische Marketinghypothesen entwickeln, vorprüfen und als messbare Experimente priorisieren. Nutze diesen Skill, wenn Ideen für Kanäle, Kampagnen, Angebote oder Wachstum gesucht werden, wenn eine Ideenliste auf Risiko und Machbarkeit geprüft werden soll, oder wenn aus Vorschlägen Experimentsteckbriefe mit Metrik, Laufzeit, Budget und Stopkriterium werden sollen. Sortiert vor der Bewertung aus, was rechtlich, plattformseitig oder finanziell nicht tragbar ist, und trennt Evidenz von Vermutung. Führt keine Kampagne aus und schaltet keine Anzeigen.
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。