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概要と使いどころ
Rewrite `outline/claim_evidence_matrix.md` as a projection/index of evidence packs (NO PROSE), so claims/axes are driven by `outline/evidence_drafts.jsonl` rather than outline placeholders.
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 a retrieval-informed chapter skeleton (`outline/chapter_skeleton.yml`) from taxonomy/core scope before stable H3 decomposition.
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。
Retrieves up-to-date documentation, API references, and code examples for any developer technology. Use this skill whenever the user asks about a specific library, framework, SDK, CLI tool, or cloud service — even for well-known ones like React, Next.js, Prisma, Express, Tailwind, Django, or Spring Boot. Your training data may not reflect recent API changes or version updates. Always use for: API syntax questions, configuration options, version migration issues, "how do I" questions mentioning a library name, debugging that involves library-specific behavior, setup instructions, and CLI tool usage. Use even when you think you know the answer — do not rely on training data for API details, signatures, or configuration options as they are frequently outdated. Always verify against current docs. Prefer this over web search for library documentation and API details.
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。
UI/UX design-system intelligence - 84 styles, 192 palettes, 74 font pairings, 25 charts, 99 UX guidelines across 22 stacks (searchable dataset + CLI). Internal genjutsu module: loaded by /genjutsu:cast and /genjutsu:paint, not 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。
MUST USE when an existing .NET test project was excluded from a .slnf/CI solution filter, disappeared from .sln/.slnx discovery, or lost its production ProjectReference; also for requests to set up, create, reuse, add, register, include, or repair a test project. Handles "tests pass directly but CI discovers zero", exact solution wiring, xUnit/NUnit/MSTest, and central packages. DO NOT USE to only author tests in an already-wired project (code-testing), run tests, migrate, or correct MSTest syntax/configuration without changing project or CI files (writing-mstest-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。
Audits existing tests in any language using formal, research-backed test smell names and the testsmells.org 19-smell academic taxonomy. Use when the caller asks for an academic or citable test-smell review, named smell categories, or a formal severity-ranked smell assessment. Covers Assertion Roulette, Conditional Test Logic, Mystery Guest, Eager Test, Sleepy Test, Unknown Test, Sensitive Equality, and the rest of the catalog across .NET, Python, JavaScript/TypeScript, Java, Go, Ruby, Rust, Swift, Kotlin, PowerShell, and C++. DO NOT USE FOR a quick pragmatic test review (use test-anti-patterns), writing or running tests, framework migration, coverage, or assertion-diversity metrics.
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。
ALWAYS USE before running .NET tests or answering with a test command or flags. Trigger on "run the tests", "exact dotnet test command", one test/class/category/trait/target framework, combined filters, `--filter-query`, `--no-build`, `--diag`, diagnostic logs, TRX, coverage collection, crash/hang dumps, filter errors, or unrecognized options. Chooses repository-compatible classic, VSTest, bridged MTP, or native MTP syntax for MSTest/xUnit/NUnit/TUnit. DO NOT USE for platform identification alone (platform-detection), writing or debugging test code, interpreting an existing coverage report, CI investigation, migration, or a persistent hot reload/watch loop.
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。
Find caller-visible production changes existing tests would miss through pseudo-mutation analysis; verify candidates or close gaps only when requested. Includes read-only per-test composition for grading. Polyglot. USE FOR: would tests catch a bug, behavioral blind spots, surviving mutations. DO NOT USE FOR: concrete fix/feature revision proof (test-value-evidence); suite taxonomy (test-tagging); .NET coverage, Cobertura, plateaus or coverage-backed priorities (coverage-analysis); named CRAP (crap-score); new suites (code-testing); assertion/smell audits; mutation tools.
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。
Migrate .NET test projects from xUnit.net v2 to xunit.v3 and fix v3 breaks. Use for package/CPM conversion, OutputType=Exe, preserving the VSTest or MTP runner (including projects currently using YTest.MTP.XUnit2), incompatible TFMs, async void tests, string-to-Type attributes, custom Fact/Theory/BeforeAfterTest attributes, Xunit.SkippableFact, xunit.abstractions/extensibility consolidation, and Xunit.Combinatorial/StaFact compatibility. Do not use for framework conversion or a runner-only migration. For xUnit v3 MTP filter syntax, also use migrate-vstest-to-mtp.
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。
Comprehensive guide for developing WebGPU-enabled Three.js applications using TSL (Three.js Shading Language). Covers WebGPU renderer setup, TSL syntax and node materials, compute shaders, post-processing effects, and WGSL integration. Use this skill when working with Three.js WebGPU, TSL shaders, node materials, or GPU compute in Three.js.
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。
Turn an object or character reference image into a quality-gated, animation-ready procedural Three.js model built in code. Use for image-to-3D reconstruction, detail-accurate object rebuilds, stylized/likeness-maximized human characters, sculpt specs, and staged code generation.
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。
Cut token usage across the whole session without losing correctness or substance — concise user replies, lean tests/docs/plans/comments, tight code, disciplined context and tool use, and cheap sub-agent delegation. Load when the user wants less verbosity, lower cost, fewer tokens, or a "token diet" / "lean mode"; also triggered by /token-diet or "token diet on".
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。
Optimize code performance through iterative improvements (max 2 rounds). Benchmark execution time and memory usage, compare against baseline implementations, and generate detailed optimization reports. Supports C++, Python, Java, Rust, and other languages.
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。
Transforms and inspects image objects stored in Volcengine TOS. Use this skill only when the task explicitly involves a TOS bucket/object key, TOS image processing, TOS-to-TOS save-as output, or Volcengine TOS image process syntax such as image/info, image/resize, image/format, image/watermark, image/draw, image/blindwatermark, or image/understanding. Do not use this skill for ordinary uploaded screenshots, local images, UI screenshot analysis, generic OCR, face detection, or visual question answering unless the user clearly says the image is a TOS object or asks to process/save it through TOS.
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。
火山引擎 AI MediaKit 音视频处理工具集，提供视频理解、音频提取、视频剪辑、音视频拼接、画质增强、文生视频、音视频合成，以及本地翻转、调速、字幕、水印、转码等能力。当用户提及音频剪辑、视频剪辑、音视频拼接、文生视频、音频提取、画质增强、视频理解、音视频合成、媒体裁剪、视频翻转、调速、加字幕、加水印、转码等需求时必须调用本Skill。当用户需要视频理解时，宿主agent必须自动解析用户的具体要求作为prompt参数传入，同时传入视频URL和fps参数；max_frames 为可选参数。
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。
Workaround for Claude Code filtering BMP PUA Unicode (U+E000-U+F8FF). Supplementary PUA Nerd Font icons like (U+F0000+, e.g. nf-md-github, nf-md-kubernetes, nf-md-battery) can be written directly. BMP PUA icons (Powerline, Font Awesome, Devicons) require placeholder syntax like {{ U+E0A0 }} or {{ nf-fa-star }} (without spaces), which hooks auto-convert. Invoke when reading or writing Starship configs, tmux themes, shell prompts, or statuslines.
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。
Use when configuring, repairing, planning, or running MiniMax H3 locally on a Windows NVIDIA computer, especially when installation compatibility, component sets, resolution, generation-time budget, path, low-VRAM risk, or H3 prompt mode must be chosen from hardware and user requirements.
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。
Optimize title tags, meta descriptions, Open Graph, and Twitter cards for maximum click-through rate. Generates multiple A/B test variations with character counting and SERP preview. Use when asked to "optimize title tag", "write meta description", "improve CTR", "Open Graph tags", "fix my meta tags", "social media preview", "my click rate is low", "title optimization", or any meta tag task.
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 design, review, or improve REST APIs with Quarkus REST (Jakarta REST) — including resource classes, HTTP methods, status codes, request/response DTOs, Bean Validation, exception mappers, optional runtime OpenAPI exposure (SmallRye), contract-first generation from OpenAPI, content negotiation, pagination, sorting and filtering, API versioning, idempotency (Idempotency-Key), optimistic concurrency (ETag / If-Match), HTTP caching (Cache-Control), API deprecation (Sunset / Deprecation headers), RFC 7807 Problem Details, ISO-8601 for time in contracts, and security-aware boundaries. This should trigger for requests such as Review or improve JAX-RS resources in a Quarkus project; Design HTTP APIs with validation and error handling on Quarkus; Add API versioning, idempotency, ETag concurrency, or deprecation headers; Implement pagination, sorting, or RFC 7807 Problem Details error responses; Improve Quarkus REST resources and exception mappers. 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 design, review, or improve validation in Quarkus applications — including Bean Validation on JAX-RS resources, @Valid on parameters and CDI beans, constraint groups, @ConfigMapping validation, custom constraints, nested DTO validation, and ExceptionMapper-based error mapping. This should trigger for requests such as Add validation support in Quarkus; Review Quarkus validation rules; Improve request validation in Quarkus REST APIs; Add custom validation constraints in Quarkus; Validate Quarkus @ConfigMapping properties. 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。
Use when you need to refactor Java code for high performance — including memory/allocation reduction, CPU hot-path optimization, and syntax/API/control-flow improvements. This should trigger for requests such as Review Java code for high performance; Optimize Java hot path; Reduce Java allocations; Improve Java latency/throughput. 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。