「perf」の検索結果

Simplification audit or authorized codebase simplification whose stated objective is to remove accidental complexity. Use for evidence-backed deletion or consolidation of dead code, duplicate state, redundant APIs or layers, ownerless abstractions, obsolete compatibility or design records, and over-engineering in any language; also use for 代码简化 or 熵回收. Do not use for general code review, onboarding, style-only refactoring, or performance tuning.

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 audit checklist - motion gaps, accessibility, color consistency, responsive, performance.

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。

Mobile-specific UX principles - touch targets, hover-less doctrine, thumb zones, safe areas, gestures, mobile perf budgets. Cross-platform (web mobile, iOS, Android).

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。

Motion design foundation - timing, easing, enter/exit patterns, accessibility, performance.

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。

Kimi Browser Extension（Kimi 浏览器扩展，原 Kimi WebBridge）lets AI control the user's real browser — navigate, click, type, read, screenshot, and interact with any website using the user's actual login sessions. Use this skill whenever the user wants to interact with websites, automate browser tasks, scrape web content, or perform any action requiring a real browser. Also use when the user mentions "browser", "webpage", "open URL", "screenshot", asks to read/interact with any website, or wants a reusable CLI tool or script that automates a specific website. Use even for simple-sounding browser requests — the daemon handles all complexity.

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。

Diagnosis loop for hard bugs and performance regressions. Use when the user says "diagnose"/"debug this", or reports something broken/throwing/failing/slow.

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。

Remove repeated NuGet restores from multi-step .NET builds safely. USE FOR: build/test/publish steps that each restore, Directory.Build.rsp with -restore, safe restore suppression, NETSDK1004/NETSDK1047 after --no-restore. DO NOT USE FOR: slow first restore, only one restore, version or lock errors, unranked build slowness (use build-perf-baseline).

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。

Choosing an MSBuild CopyToOutputDirectory / CopyToPublishDirectory mode: Never, PreserveNewest, Always, and IfDifferent (MSBuild 17.13+), plus $(SkipUnchangedFilesOnCopyAlways). USE FOR: removing the per-build Always copy perf hit; resetting output files mutated between builds. DO NOT USE FOR: general incremental-build diagnosis (use incremental-build); non-MSBuild build 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。

Use `pvanalyze` to inspect existing .NET `.nettrace` files from the command line, including GC, JIT, CPU stacks, allocation, DATAS, events, exceptions, timeline, and call-tree analysis with JSON or SpeedScope. USE FOR: the user mentions pvanalyze, PerfView-style CLI trace analysis, or cross-platform .nettrace inspection; the task starts from an existing .nettrace file and needs. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

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 Stylelint in .NET repositories that ship CSS, SCSS, or other stylesheet assets alongside web frontends. USE FOR: stylelint.config.*, .stylelintrc*, CSS or SCSS assets; CSS linting; duplicate style cleanup and naming-convention checks. DO NOT USE FOR: JavaScript or TypeScript lint ownership; runtime accessibility, performance, SEO, or header checks. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

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 when asked to fix, rewrite, update, improve, modernize, show corrected code for, or explain existing MSTest tests or MSTest-specific configuration. Use for "review" when corrected code or edits are wanted, even for one pasted assertion or passing tests with bad failure output. Covers expected/actual labels; generic Boolean, collection, string, numeric, null, identity, exception, hard-cast, and object[] checks; TestContext/lifecycle; timeout/cancellation; OS/CI conditions, retry, cleanup, parallelization, MSTest.Sdk project setup, and MSTESTxxxx. Honor the installed MSTest version. DO NOT USE to design new test cases (code-testing), perform report-only audits, create project files rather than explain MSTest setup, run tests, migrate frameworks, or handle non-MSTest/non-.NET code.

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 only for MSBuild failure investigation, build-performance analysis, or review of existing build XML/extension contracts. A plan to convert a working legacy/non-SDK project to SDK style or migrate packages.config is a project-system migration, NOT a build-file review: do not activate, even to check scope. Framework/API upgrades are also excluded. Activate for advisory Import/Exists hook and NuGet packed-import questions even without a checkout or failed build; .csproj/.fsproj/.vbproj/.props/.targets conditions; custom-target inputs/outputs; .binlog capture/replay; failing dotnet build/restore/pack/publish or MSBuild-based test builds; slow evaluation, compilation, copying, or no-change builds; and controlled timing comparisons. Exclude SDK installation alone, C# refactoring, runtime profiling, assertions after successful builds, and non-MSBuild builds.

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。

Review and optimize application data access that uses Entity Framework Core (EF Core). Use for EF Core performance and correctness reviews of services, repositories, imports, and background jobs: slow or memory-heavy queries, excessive round-trips, hidden SaveChanges, premature materialization, dynamic query construction, result-graph tracking, bulk writes, DbContext lifetime or overlapping operations, search semantics, paging, raw SQL, and model/index coverage. Use whether or not EF Core owns the schema. For EF Core, not Dapper or raw ADO.NET.

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。

Invoke when the user asks to review, check, audit, or look over Qt6 QML code -- or suggest before committing. Runs deterministic linting (47+ rules) then six parallel deep- analysis agents covering bindings, layout, loaders, delegates, states, and performance. Optionally invokes system qmllint for type-level checks. Reports only high-confidence issues (>80/100) with structured mitigations. Read-only -- never modifies code.

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。

Invoke when the user asks to review, check, audit, or look over Qt6 C++ code — or suggest before committing. Runs deterministic linting (60+ rules) then six parallel deep- analysis agents covering model contracts, ownership, threading, API correctness, error handling, and performance. Reports only high-confidence issues (>80/100) with structured mitigations. Read-only — never modifies code.

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 the user is investigating QML / Qt Quick performance — both vague complaints ("the UI feels laggy", "this is slow", "frames are dropping", "the app stutters") and explicit asks to profile, find hotspots, or optimize bindings, signals, or rendering. Runs qmlprofiler on a 2D QML application, parses the .qtd trace, and analyzes hotspots against the source with frame-time, memory, and pixmap-cache summaries. Does NOT cover Qt Quick 3D.

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。

Remove the AI tells readers react to in an Instagram caption or carousel slide: 2026 vocabulary by density, reveal bridges, staccato stacks, stacked triads, performed sincerity, emoji storms; caps em dashes. Includes --mode audit (first-125 hook, length, hashtags, emoji, CTA, media) and --mode profile. Not for beating AI detectors (no edit reliably does). Not for writing from scratch (use ig-caption-writer or ig-carousel-planner). Keywords: humanize, de-AI caption, audit before posting.

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。

SQL query review for correctness, performance, and best practices. Activate when a query needs review before production use, shows unexpected results, or runs too slowly.

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。

Systematic investigation of metric changes and anomalies. Use when a metric unexpectedly changes, investigating business metric drops, explaining performance variations, or drilling into aggregated metric drivers.

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。

Entrypoint for managing Volcengine Flink (based on Apache Flink) workloads. Use it for developing and deploying streaming and batch jobs, diagnosing real-time issues (e.g., backpressure, checkpoint failures, OOM), troubleshooting resources, and performing SRE actions (stop/start/restart/scale/config changes). It intelligently routes requests to four specialized sub-skills and leverages flink-mcp for tool execution.

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。

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。

Guide a user conversationally through generating a new ad video from a template video and a user-provided product image. The host agent performs video understanding, detailed analysis, and rewrite planning; BytePlus Seedance is used only for final video generation with local product images as generation references.

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 app, service, or user-mode driver C++ coroutine code holds a thread-affine lock across suspension and later hangs or fails. Not for all coroutine crashes or choosing lock performance.

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。