253건 · 관련도순
Identifies Oracle-to-PostgreSQL migration risks by cross-referencing code against known behavioral differences (empty strings, refcursors, type coercion, sorting, timestamps, concurrent transactions, etc.). Use when planning migration of a procedure, trigger, query, or refcursor client, and again to validate the finished port.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Extract clean markdown from any URL, including JavaScript-rendered SPAs. Use this skill whenever the user provides a URL and wants its content, says "scrape", "grab", "fetch", "pull", "get the page", "extract from this URL", or "read this webpage". Handles JS-rendered pages, multiple concurrent URLs, and returns LLM-optimized markdown. Use this instead of WebFetch for any webpage content extraction.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Bulk extract content from an entire website or site section. Use this skill when the user wants to crawl a site, extract all pages from a docs section, bulk-scrape multiple pages following links, or says "crawl", "get all the pages", "extract everything under /docs", "bulk extract", or needs content from many pages on the same site. Handles depth limits, path filtering, and concurrent extraction.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when designing, implementing, reviewing, debugging, testing, profiling, or porting concurrent, parallel, distributed, high-performance, network dataplane, kernel-bypass, or real-time software, including locks, semaphores, monitors, MPI, CSP rendezvous, DPDK, VPP, eBPF, XDP, AF_XDP, SR-IOV, RSS, RoCEv2/RDMA, RMS/EDF, priority inversion, and environment selection from silicon to edge.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Brief on concurrent sessions — who else is working, in which repos, on which files, and what landed underneath you. Use when a commit appears that you did not make, before touching a shared file, or when orienting mid-task in a busy workspace.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implements and reviews mobile identity and session flows across Flutter, Android, iOS, React Native and Kotlin Multiplatform. Use for sign-in, passkeys, account recovery, provider linking, reauthentication, logout and concurrent refresh. Security audits belong to mobile-security; account deletion belongs to mobile-privacy.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Implements and reviews mobile API integration across Flutter, Android, iOS, React Native and Kotlin Multiplatform. Use for HTTP clients, pagination, request cancellation, concurrent token refresh, resumable uploads and WebSocket lifecycle. Durable offline mutation queues belong to mobile-offline-sync.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Upgrade React applications to latest versions, migrate from class components to hooks, and adopt concurrent features. Use when modernizing React codebases, migrating to React Hooks, or upgrading to latest React versions.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Leverage concurrent terminal background processes to debug multiple independent failures simultaneously using ACH methodology. Use when you have 2+ failures across different subsystems.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Orchestrate concurrent analysis or implementation across independent domains. Use when a task can be decomposed into independent workstreams (e.g., via simultaneous tool calls or background processes) — spec writing, code review, security audit, feature implementation.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use multiple Claude agents to investigate and fix independent problems concurrently
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Expert en stratégie de marque (positionnement, messaging, architecture de marque, analyse concurrentielle)
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Master Go concurrency with goroutines, channels, sync primitives, and context. Use when building concurrent Go applications, implementing worker pools, or debugging race conditions.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Resolve Swift concurrency compiler errors, adopt approachable concurrency (SE-0466), and write data-race-safe async code. Use when fixing Sendable conformance errors, actor isolation warnings, or strict concurrency diagnostics; when adopting default MainActor isolation, @concurrent, nonisolated(nonsending), or Task.immediate; when designing actor-based architectures, structured concurrency with TaskGroup, or background work offloading; or when migrating from @preconcurrency to full Swift 6 strict concurrency.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Diagnose data races, convert callback-based code to async/await, implement actor isolation patterns, resolve Sendable conformance issues, and guide Swift 6 migration. Use when developers mention: (1) Swift Concurrency, async/await, actors, or tasks, (2) "use Swift Concurrency" or "modern concurrency patterns", (3) migrating to Swift 6, (4) data races or thread safety issues, (5) refactoring closures to async/await, (6) @MainActor, Sendable, or actor isolation, (7) concurrent code architecture or performance optimization, (8) concurrency-related linter warnings (SwiftLint or similar; e.g. async_without_await, Sendable/actor isolation/MainActor lint).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Comprehensive PR code review for OneKey monorepo. Use when reviewing PRs, code changes, or diffs — covers security (secrets/PII leakage, supply-chain, AuthN/AuthZ), code quality (hooks, race conditions, null safety, concurrent requests), and OneKey-specific patterns (Fabric crashes, MIUI, BigNumber). Triggers on "review PR", "review this PR", "code review", "check this diff", "审查 PR", "代码审查", "review
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Reference for concurrent steps within a GitHub Actions job and the background, wait, wait-all, cancel, and parallel keywords.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Visualises RNA-modification data with transcript-feature metagene plots (Guitar GuitarPlot with 5'UTR / CDS / 3'UTR scaling; MetaPlotR; deepTools `computeMatrix scale-regions`), peak-centred heatmaps (ComplexHeatmap; deepTools plotHeatmap), IP-vs-input paired browser tracks (bigWig of log2 IP/input via deepTools `bamCompare`; ggcoverage; pyGenomeTracks; Gviz; IGV / UCSC track hubs), DRACH sequence-logo plots (ggseqlogo; MEME), 5'UTR / CDS / 3'UTR stacked-bar feature-distribution summaries, and volcano / MA plots for differential modification. Establishes stop-codon enrichment in the metagene plot as the biological QC anchor for any MeRIP dataset (Dominissini 2012 *Nature* 485:201; Meyer 2012 *Cell* 149:1635 — concurrent founding papers from different labs both showed this independently). Use when producing the canonical metagene plot with stop-codon enrichment as a QC anchor, building paired IP/input genome-browser tracks at single-locus resolution, plotting peak-centred heatmaps clustered by condition, summarising peak distribution across transcript features for figure 1, generating DRACH motif logos as sanity checks on the peak set, rendering volcano plots of differential m6A, or reproducing the Dominissini 2012 / Meyer 2012 stop-codon enrichment plot.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Comprehensive guidance for implementing asynchronous Python applications using asyncio, concurrent programming patterns, and async/await for building high-performance, non-blocking systems.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Visualises RNA-modification data with transcript-feature metagene plots (Guitar GuitarPlot with 5'UTR / CDS / 3'UTR scaling; MetaPlotR; deepTools `computeMatrix scale-regions`), peak-centred heatmaps (ComplexHeatmap; deepTools plotHeatmap), IP-vs-input paired browser tracks (bigWig of log2 IP/input via deepTools `bamCompare`; ggcoverage; pyGenomeTracks; Gviz; IGV / UCSC track hubs), DRACH sequence-logo plots (ggseqlogo; MEME), 5'UTR / CDS / 3'UTR stacked-bar feature-distribution summaries, and volcano / MA plots for differential modification. Establishes stop-codon enrichment in the metagene plot as the biological QC anchor for any MeRIP dataset (Dominissini 2012 *Nature* 485:201; Meyer 2012 *Cell* 149:1635 — concurrent founding papers from different labs both showed this independently). Use when producing the canonical metagene plot with stop-codon enrichment as a QC anchor, building paired IP/input genome-browser tracks at single-locus resolution, plotting peak-centred heatmaps clustered by condition, summarising peak distribution across transcript features for figure 1, generating DRACH motif logos as sanity checks on the peak set, rendering volcano plots of differential m6A, or reproducing the Dominissini 2012 / Meyer 2012 stop-codon enrichment plot.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use when running analytical SQL over Parquet/CSV/JSON without a warehouse, replacing pandas for data wrangling, joining S3 data in-place, building local data marts, or embedding OLAP into an app. Triggers: read_parquet/read_csv setup, partitioned dataset queries, hive partitioning, glob patterns for S3, COPY TO export, attach Postgres/MySQL, UDFs in Python/R, MotherDuck cloud sync, columnar performance vs row stores. NOT for OLTP workloads (concurrent writes), distributed analytics at petabyte scale (use Spark/Trino), or vector search (use pgvector/Lance).
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.