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概要と使いどころ
Manage AgentKit skills, SkillHub/skillhub, skill centers, and skill spaces. Use this skill whenever the user has a management intent for AgentKit skills, skill中心, skill 空间, skill space, or skill hub, including listing, inspecting, downloading, fetching, uploading, publishing, registering, or syncing skills between local directories and remote skill spaces.
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。
Resizes, scales, and adjusts video resolution and dimensions using GPU-accelerated NVENC encoding via Volcengine LAS. Video resizing, video scaling, video upscaling, and video downscaling — change video resolution, enlarge or shrink video dimensions, and adjust video size for different platforms and screens. Video compression by reducing resolution and video transcoding and re-encoding with specific dimension constraints. Supports flexible min/max width and height ranges with aspect ratio preservation strategies (increase, decrease, or disable), including landscape to portrait conversion. Async submit-poll workflow with batch support. Use this skill when the user wants to resize or scale video resolution (upscale/downscale), change video dimensions for different platforms, compress videos by reducing resolution, transcode/re-encode videos with GPU NVENC, adjust aspect ratio including landscape-to-portrait conversion, adapt videos for mobile/web/social media, or batch process multiple videos.
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。
Compresses and uncompresses file objects stored in Volcengine TOS through TOS data-process async jobs. Use this skill when the user needs to zip files, unzip archives, create tar or zstd archives, extract compressed files, pack multiple TOS objects into a single archive, bundle files together, or distribute files as a package — even if they don't explicitly mention 'compression', 'archive', '打包', or '压缩'.
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。
Converts audio objects stored in Volcengine TOS into PCM-oriented WAV output through TOS data-process async jobs. Use this skill when the user needs to convert audio to PCM or WAV, resample audio to 16k, convert to mono, change sample format, normalize audio for ASR pipelines, or prepare TOS audio files for speech recognition — even if they don't explicitly mention 'PCM' or 'audio conversion'.
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。
Performs deep AI-powered analysis and understanding of long-form videos (up to 3 hours, 10GB) using Volcengine LAS large language models. Video analysis, video comprehension, and video summarization — generates comprehensive video summaries, video recaps, chapter breakdowns, event timelines, key moments, and structured content indexing. Supports behavior detection, action detection, video annotation, video tagging, and video content recognition. Enables intelligent video question answering — ask questions about video content and get AI answers. Handles long meeting recordings, lecture videos, webinars, surveillance and security footage, movies, tutorials, and any long video that needs detailed understanding. Async processing with submit-poll workflow. Use this skill when the user wants to analyze or understand long videos (up to 3h/10GB) with LLM-based deep comprehension, summarize video content or generate recaps, extract chapters/key moments/timelines from videos, do video Q&A (ask questions about video content), detect actions/behaviors in videos, review meeting recordings/lectures/webinars, or get structured video descriptions.
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 kernel threads block on driver synchronization or Verifier reports a lock-order violation; build an owner/waiter graph. Not for treating every watchdog stop as a deadlock or listing every lock type with !locks.
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。
Direct and produce Chinese-first cinematic motion videos with HyperFrames. Use this skill when the user wants a rendered promo film, article-to-video piece, product launch film, website-to-video piece, keynote reveal, kinetic typography sequence, text/icon transition promo, music-synced motion graphic, HTML/CSS/SVG/GSAP video, short-form vertical video, or a landing page/product story turned into motion. Default to Simplified Chinese, vertical 9:16, and 1080x1920 unless the user or platform clearly requires another format. The skill enforces a two-phase workflow: brief first, confirmation second, then assets, composition, validation, snapshots, render, and review report.
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 reviewing Java enterprise evidence for MiFID II investment services, investment activities, client classification, suitability, appropriateness, order-handling evidence, best-execution evidence, algorithmic-trading governance evidence, market-access governance evidence, transaction evidence, record keeping, monitoring, or compliance-owner handoff. This should trigger for requests such as Review a Java investment-service platform for MiFID II evidence; Assess suitability, appropriateness, order-handling evidence, or best-execution evidence; Document audit, monitoring, or clock-synchronisation gaps for algorithmic-trading governance; Assess investment-service engineering evidence before production release. Part of Plinth Toolkit
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 creating or updating OpenSpec artifacts from an issue, plan, approved design, ADRs, existing OpenSpec, or a valid combination. The workflow assesses reviewable scope, records source authority and derivation, handles conflicts, and prevents silent synchronization. Triggers include Create OpenSpec from an issue; Convert a plan into OpenSpec; Update an OpenSpec change; Split broad requirements into reviewable changes. Part of Plinth Toolkit
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 you need to apply Java exception handling best practices — including using specific exception types, managing resources with try-with-resources, securing exception messages, preserving error context via exception chaining, validating inputs early with fail-fast principles, handling thread interruption correctly, documenting exceptions with @throws, enforcing logging policy, translating exceptions at API boundaries, managing retries and idempotency, enforcing timeouts, attaching suppressed exceptions, and propagating failures in async/reactive code. This should trigger for requests such as Exception handling; Use try-with-resources in Java code; Create exception chaining in Java code; Apply fail-fast validation in Java code; Review Java exception taxonomy and propagation. Part of Plinth Toolkit
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 documentation drift against filesystem state.
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。
Pull request lifecycle: commit, codex review, sync, review, fix, status, cleanup, and PR mining. Use when user wants to commit changes, get a second-opinion code review from Codex, push changes, create a PR, check PR status, fix review comments, clean up branches after merge, or mine tribal knowledge from PR reviews. Use for "commit my changes", "codex review", "push my changes", "create a PR", "pr status", "fix PR comments", "clean up branches", "mine PRs", or "address feedback".
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。
Delegate coding tasks to Google Jules AI agent for asynchronous execution. Use when user says: 'have Jules fix', 'delegate to Jules', 'send to Jules', 'ask Jules to', 'check Jules sessions', 'pull Jules results', 'jules add tests', 'jules add docs', 'jules review pr'. Handles: bug fixes, documentation, features, tests, refactoring, code reviews. Works with GitHub repos, creates PRs.
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 dynamic schema-based forms using @delon/form (SF component). Use this skill when building complex forms with validation, conditional rendering, async data loading, custom widgets, and multi-step workflows. Ensures forms follow JSON Schema standards, integrate with Angular reactive forms, support internationalization, and maintain consistent validation patterns across the application.
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 RxJS patterns for reactive programming in Angular. Use this skill when working with Observables, operators, subscriptions, async data flows, and error handling. Covers common patterns like combineLatest, switchMap, debounceTime, catchError, retry logic, and integration with Angular Signals using toSignal() and toObservable(). Ensures proper subscription cleanup with takeUntilDestroyed().
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。
Debug WebSocket connection issues between CLI and FigJam plugin. Use when diagrams aren't syncing, connection fails, plugin shows "Connecting..." indefinitely, or patches aren't being applied to canvas.
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。
Guide for using twscrape to collect public Twitter/X data through its GraphQL interface, asynchronous queries, and account session management.
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 AI videos with Google Veo, Seedance 2.0, HappyHorse, Wan, Grok and 40+ models via inference.sh CLI. Models: Veo 3.1, Veo 3, Seedance 2.0, HappyHorse 1.0, Wan 2.5, Grok Imagine Video, OmniHuman, Fabric, HunyuanVideo. Capabilities: text-to-video, image-to-video, reference-to-video, video editing, lipsync, avatar animation, video upscaling, foley sound. Use for: social media videos, marketing content, explainer videos, product demos, AI avatars. Triggers: video generation, ai video, text to video, image to video, veo, animate image, video from image, ai animation, video generator, generate video, t2v, i2v, ai video maker, create video with ai, runway alternative, pika alternative, sora alternative, kling alternative, seedance, happyhorse
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。
Integration skill for Lovable.dev projects. Activates when working with: - Lovable.dev projects with GitHub sync - Supabase Edge Functions that need deployment - Database migrations for Lovable Cloud - Projects with supabase/ directory structure - Any mention of "Lovable", "deploy edge function", "apply migration" Provides exact Lovable prompts for backend operations that can't be done via GitHub alone.
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。
FastAPI web framework patterns. Triggers on: fastapi, api endpoint, dependency injection, pydantic model, openapi, swagger, starlette, async api, rest api, uvicorn.
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。
SQLAlchemy and database patterns for Python. Triggers on: sqlalchemy, database, orm, migration, alembic, async database, connection pool, repository pattern, unit of work.
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。
Detects stale project plans and suggests session commands. Triggers on: sync plan, update plan, check status, plan is stale, track progress, project planning.
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。
Patterns for SQLite databases in Python projects - state management, caching, and async operations. Triggers on: sqlite, sqlite3, aiosqlite, local database, database schema, migration, wal mode.
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 Jira workflows end-to-end. Use when building stories with approvals, transitioning items through lifecycle states, or syncing task completion with Jira.
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。