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概要と使いどころ
This skill should be used when the user asks to "audit claude permissions", "audit permissions", "review local claude settings", "promote permissions to global", "clean up claude settings", "find permission patterns", or wants to identify project-local Claude Code permissions that should be added to global configuration.
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。
Read a real .pptx using text extraction, OOXML inspection, slide rendering, OCR, visual inventory, and vision-capable screenshot review; then write academic speaker notes grounded in every visible slide element, generate a complete display-version document, and inject clean notes into the PowerPoint notes pane. Use when the user wants speaker notes, presenter notes, a speech script, narration, or annotated notes for an existing PowerPoint deck, especially when slides contain images, charts, tables, SmartArt, axes, legends, or screenshot text.
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。
自动清洗赛题或爬取的数据（处理缺失/异常/格式），并生成可视化图表。Invoke when 用户需要处理原始数据、清洗数据或生成数据分析图表。
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。
Качество русского текста для агента. Russian text quality for agents: proofreading and AI-slop cleanup for Cyrillic text. Триггеры: очеловечь, вычитай, отредактируй, поправь, причеши, проверь текст, убери канцелярит, humanizer. Молча снимает жёсткие запреты в собственном русском выводе агента; чужой текст молча не трогает. Use when надо убрать из русского текста канцелярит, воду и нейросетевую манеру, не сломав смысл, факты и голос автора. Три режима по запросу: редактура, аудит без переписывания, точечная правка одной категории. Со скиллом едет детерминированный сканер scripts/scan.py: считает хард-баны, категории маркеров, ритм и морфологию, печатает ЧИСТОТА: N/100, поэтому правка измерима («было N, стало M»). Флаг --genre academic/legal/fiction/news снимает маркеры, законные для научного, юридического и новостного регистра. Работает ТОЛЬКО с русским: для английского humanizer, для итальянского humanizer-it. НЕ используй для: перевод, написание с нуля, грамматика без стилистики, код.
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 write or improve integration tests for Quarkus — including @QuarkusTest, Dev Services for automatic container provisioning, Testcontainers via QuarkusTestResourceLifecycleManager, WireMock for external HTTP stubs, @QuarkusIntegrationTest for black-box testing against packaged artifacts, REST Assured, data isolation strategies (@TestTransaction vs @BeforeEach cleanup), and Maven Surefire/Failsafe three-tier split (*Test, *IT, *AT). This should trigger for requests such as Add or improve integration tests in a Quarkus project; Configure Testcontainers or Dev Services for Quarkus tests; Add WireMock stubs for external HTTP dependencies in Quarkus integration tests; Set up @QuarkusIntegrationTest for packaged artifact or native binary testing; Fix test data isolation or configure Maven Surefire/Failsafe split. 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 add or review Flyway database migrations in a Quarkus application — quarkus-flyway extension, db/migration scripts, quarkus.flyway.* configuration, migrate-at-start, and alignment with JDBC or Panache. This should trigger for requests such as Add or review Flyway migrations in a Quarkus project; Configure quarkus-flyway or db/migration layout; Add versioned Flyway SQL migrations for Quarkus; Review Quarkus database migration ordering; Configure Flyway clean migrate or baselines in Quarkus. 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。
Audit your Obsidian vault in Claude Code — finds stale drafts, empty folders, duplicate filenames, and incomplete files. Saves a dated 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。
Generate a clean morning brief in Claude Code — pulls today's priorities, unposted content, and weather from your vault.
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。
Extract video transcripts: yt-dlp subtitles to clean paragraphs.
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。
Writing: voice creation and validation, prose editing, anti-AI cleanup, professional communication, translation.
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。
Code quality: cleanup, linting, formatting, quality gates.
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。
Enterprise-level Go architecture patterns including clean architecture, hexagonal architecture, DDD, and production-ready application structure.
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。
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
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 event-driven communication using BlueprintEventBus for cross-module coordination. Use this skill when modules need to communicate without tight coupling, broadcasting domain events (task.created, member.added), subscribing to events with proper lifecycle management, and implementing event-driven workflows. Ensures events follow naming conventions ([module].[action]), include Blueprint context, and use takeUntilDestroyed() for automatic cleanup.
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。
This skill should be used when refactoring existing CSS from inline styles or utility classes to semantic patterns. Triggers on "refactor CSS", "extract styles", "consolidate CSS", "convert inline", "clean up styles", "migrate to semantic". Transforms to semantic classes with dark mode and tests.
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。
Fetches web content as clean markdown by preferring markdown-native responses and falling back to selector-based HTML extraction. Use for documentation, articles, and reference pages at http/https URLs.
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。
Creates, updates, or reviews a project's gen-env command for running multiple isolated instances on localhost. Handles instance identity, port allocation, data isolation, browser state separation, and cleanup.
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。
Decision rubric for promoting a prose prompt into a typed DSPy Signature. This is an ENHANCE overlay on top of the [[dspy]] library skill: it does NOT teach DSPy syntax — it answers the coder-agent decision "when do I stop hand-writing a prompt string and declare it as a `dspy.Signature`, and how do I name/describe its fields so the optimizer and the calling code both get a clean contract." Activate when: a prompt string grows past ~50 lines; the LM output is consumed by code (parsed, branched on, stored) rather than read by a human; the same prompt is reused across >1 call site; or a teammate asks "should this be a Signature?". Do NOT activate for one-shot throwaway prompts, or for HOW-TO questions about DSPy modules /optimizers/compile — defer those to the [[dspy]] skill and the [[agentsop-dspy]] workflow skill. Search keywords: typed prompt, structured prompt, DSPy Signature, prompt as a function, prompt contract, when to formalize a prompt.
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。
Enhancement overlay — version the WHOLE deployable LLM-app artifact as one bundle: prompts + compiled programs + model snapshot pins + retrieval config + eval-set version, versioned together so a deploy is reproducible and rollback is atomic. Activate when preparing to deploy an LLM app, when asking "what exactly is running in prod right now?", when a deploy must be reproducible months later, or when an incident needs a clean rollback. The core reframe: an LLM app artifact is NOT an ML model — it is a manifest over many independently-mutable parts, not one weights file. Do NOT activate for one-off prompt edits with no deploy, for a single-component demo, or where a vendor owns the whole prompt lifecycle. For versioning ONE compiled prompt use [[agentsop-per-model-artifacts]]; for the CI comparison mechanism use [[agentsop-regression-gate]]. Search keywords: prompt versioning, reproducible deploy, what is running in prod, rollback LLM app, model pinning, prompt registry, version prompts and config.
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。
Pre-flight checklist for long-running ML training jobs covering config diff, run naming, path verification, monitoring setup, and restart-cleanup. Use when the user asks to launch, kick off, start, restart, or kill a training run, or mentions launching a multi-hour or multi-day GPU job (python train, accelerate launch, torchrun, deepspeed, sbatch, tmux training).
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。
Presents options for merge, PR, or cleanup. Use when work is complete, tests pass, and you must decide how to integrate.
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。
Acquire, clean, analyze, verify, visualize, and explain data for journalism. Use for reproducible data reporting, statistical analysis, maps, or public methodology.
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。
Shared rules for test runs that drive the running app or run a test target: isolation from concurrent runs, stubs for infrastructure that cannot be stood up, provisioning privileged state, approval before writes to shared external systems, and cleanup of only what the run created. Not typically invoked directly.
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。