「thread」の検索結果

Build local BLAST databases and run searches using NCBI BLAST+ command-line tools. Use when running >50 queries, building custom databases with -parse_seqids and -taxid, downloading prebuilt NCBI databases via update_blastdb.pl, choosing -task variants (megablast/dc-megablast/blastn/blastn-short), tuning soft/hard masking, scaling threads, or extracting hits with blastdbcmd. Encodes BLAST v5 vs v4 database format, taxonomy filtering, makeblastdb pitfalls.

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。

Refactor Spring Boot and Java code to improve maintainability, readability, and adherence to enterprise best practices. This skill transforms messy Spring Boot applications into clean, well-structured solutions following SOLID principles and Spring Boot 3.x conventions. It addresses fat controllers, improper transaction boundaries, field injection anti-patterns, and scattered configuration. Leverages Java 21+ features including record patterns, pattern matching for switch, virtual threads, and sequenced collections.

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。

Genera endpoints REST con Kotlin + Spring Boot 3.4+ (Records, Virtual Threads, ProblemDetail)

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 real-time chat applications with thread management, messaging, participants, and read receipts.

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。

Azure AI Agents Persistent SDK for Java. Low-level SDK for creating and managing AI agents with threads, messages, runs, and 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。

Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and 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。

PRの未Resolveレビュー指摘に対応するスキル。「PRの指摘に対応して」「Resolveされていないスレッドを解消」「PR reviewの対応」「未解決のレビューコメントを修正」「Copilotの指摘を直して」「Codexの指摘に対応」「chatgpt-codex-connectorの指摘」「レビュー対応」で起動。PR URL or 番号 → 未Resolveスレッド取得 → 対象ファイル修正 → ユーザーへ最終ゲートとプッシュの実行手順を案内、の流れで進める。

Escreve copy para redes sociais — post avulso, carrossel, thread e legenda — respeitando limite, formato e cultura de cada plataforma. Use quando o usuário disser "post para", "legenda", "conteúdo para LinkedIn", "carrossel", "social media", "adaptar para as redes", "texto do Instagram". Para o gancho isolado ver copy-hooks; para derivar de material existente ver copy-repurpose.

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。

Transforma uma peça de conteúdo em várias — case em thread, webinar em posts, artigo em carrossel, vídeo em cortes. Use quando o usuário disser "reaproveitar", "transformar isso em", "adaptar para", "repurpose", "derivar conteúdo", "aproveitar melhor esse material", "do blog para as redes", ou apresentar material longo pedindo derivados. Produz peça nativa de cada canal, nunca copia e cola.

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。

Daily per-section review cycle driving a section toward the smallest, clearest form that still does everything it does today. Selects its section live each run (scripted), inventories every file, derives the target shape before any scan, works parallel reading threads into one ranked list and strikes it on a 2-3h budget. One PR per run; each run's report and Needs-Peter queue live in its own docs/health/runs/ file; 'resume' applies Peter's answers later. Use for the morning section-improvement run, 'doctor <section>', or 'run section doctor'.

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。

When the user wants help creating, scheduling, or optimizing social media content for LinkedIn, Twitter/X, Instagram, TikTok, Facebook, or other platforms. Also use when the user mentions 'LinkedIn post,' 'Twitter thread,' 'social media,' 'content calendar,' 'social scheduling,' 'engagement,' 'viral content,' 'what should I post,' 'repurpose this content,' 'tweet ideas,' 'LinkedIn carousel,' 'social media strategy,' or 'grow my following.' Use this for any social media content creation, repurposing, or scheduling task. For broader content strategy, see content-strategy.

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。

Resize, crop, or export any image or video into platform-ready social media assets using Adobe Creative Cloud tools. Use this skill when a user wants to prepare a photo, image, or video for one or more social platforms — Instagram, TikTok, LinkedIn, Facebook, YouTube, Snapchat, Pinterest, Threads, or X/Twitter. Triggers on: "prepare my image for Instagram", "resize for TikTok", "get this ready to post", "make versions for all platforms", "social media sizes", "crop for stories", "export for LinkedIn", "resize my video for social", "make social media assets", or any request to adapt a photo or video for specific platforms. Handles subject-aware cropping, AI canvas expansion, test previews before full runs, and same-ratio video resizing.

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。

Single entry point for all AEM as a Cloud Service Workflow skills. Covers workflow model design, custom process step and participant chooser development, launcher configuration, workflow triggering, and production support including debugging stuck/failed workflows, triaging incidents with Cloud Manager logs, thread pool analysis, and Sling Job diagnostics for the Granite Workflow Engine.

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。

Guides Rust performance optimization. Use when profiling, benchmarking, reducing allocations, improving cache locality, choosing between rayon/async/threads, or applying SIMD/parallelism.

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。

Guides concurrency and async decisions in Rust. Use when encountering Send/Sync errors (E0277), choosing between threads vs async, designing shared state, or debugging deadlocks.

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。

Manage timers, cancellation, entity lifetime, asynchronous work, and main-thread state safely.

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。

Load bounded working context at the start of a coding session. FIRES ON EVERY FIRST USER MESSAGE in a fresh session, regardless of content — including bare greetings ("hi", "hello", "hey"), task-only openers, or "let's start". Also triggers on: "fresh session", "session start", "first message in a new thread", "new chat", "cold start", "begin work in this repo", "starting work", "continue from prior session", "what were we working on", "resume", "what happened last time", "load memory", "recall context", "create a handoff", "prior session context", "latest handoff", "current state", "decision context". Skip ONLY if the user explicitly says "fresh start" or "ignore prior context". Self no-ops if invoked mid-session when context is already loaded.

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。

Triage customer support tickets/emails/chats into categories, priority, and next action; draft responses and create reproducible steps; use for Zendesk/Intercom/Help Scout exports or pasted threads.

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, validate, and troubleshoot deep links for Codex, Cursor, VS Code, Visual Studio, and similar tools. Use when users ask for clickable links (especially in Slack) that open threads, files, folders, or app settings.

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 real-time chat applications with thread management, messaging, participants, and read receipts.

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。

Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and 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。

Azure AI Agents Persistent SDK for Java. Low-level SDK for creating and managing AI agents with threads, messages, runs, and 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。

Detects m6A modifications from Oxford Nanopore direct-RNA-sequencing (ONT DRS) signal data using m6Anet (Hendra 2022 *Nat Methods* 19:1590; multiple-instance-learning neural network over DRACH 5-mer signal). Covers the required upstream pipeline (Dorado / Guppy basecalling -> minimap2 transcriptome alignment with `-ax map-ont -uf -k14 --secondary=no` -> nanopolish eventalign with `--scale-events --signal-index` (m6Anet-required) plus `--summary` / `--threads` housekeeping -> m6anet dataprep -> m6anet inference), per-site vs per-read probability interpretation including the `mod_ratio` per-site stoichiometry column, the DRACH-only modeling constraint, minimum-coverage thresholds (20-50 reads per site for stable probability estimates), multi-condition comparison via xPore (Pratanwanich 2021 *Nat Biotechnol* 39:1394), Nanocompore (Leger 2021 *Nat Commun* 12:7198), ELIGOS (Jenjaroenpun 2021 *NAR* 49:e7), and Dorado native modification calling (RNA004 chemistry, 2024+), reference-transcriptome version pinning, the cDNA-vs-DRS chemistry distinction (cDNA-Nanopore CANNOT be used for modification detection), and orthogonal validation against MeRIP / GLORI. Use when calling m6A from ONT DRS without immunoprecipitation, choosing m6Anet vs xPore vs Nanocompore vs ELIGOS vs Dorado native, interpreting per-site `probability_modified` vs `mod_ratio` vs per-read modification probabilities, comparing methylation between conditions from ONT data, deciding between m6Anet for known DRACH sites and Dorado/Remora for genome-wide screening, pinning RNA002 vs RNA004 chemistry and basecaller model versions, or troubleshooting eventalign / dataprep failures.

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 local BLAST databases and run searches using NCBI BLAST+ command-line tools. Use when running >50 queries, building custom databases with -parse_seqids and -taxid, downloading prebuilt NCBI databases via update_blastdb.pl, choosing -task variants (megablast/dc-megablast/blastn/blastn-short), tuning soft/hard masking, scaling threads, or extracting hits with blastdbcmd. Encodes BLAST v5 vs v4 database format, taxonomy filtering, makeblastdb pitfalls.

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。