「imap」の検索結果

メールの一覧表示・検索から作成、返信、転送、フォルダ整理までをエージェントに頼めます。IMAP/SMTPのメールをコマンドで扱うためのスキルです。

• 差出人と件名でメールを探したいとき
• メールを作成・返信・転送したいとき
• メールをフォルダ間で移動・コピー

ターミナルからメールを検索・閲覧し、作成・返信・転送やフォルダ整理を行うスキル。複数アカウントの切り替え、添付ファイルの保存、JSON形式での一覧取得にも対応します。

• 送信者や件名でメールを探したいとき
• メールの返信・転送を行いたいとき
• メールの移動や既読管理をしたいとき

Read and send email via IMAP/SMTP. Check for new/unread messages, fetch content, search mailboxes, mark as read/unread, and send emails with attachments. Works with any IMAP/SMTP server including Gmail, Outlook, 163.com, vip.163.com, 126.com, vip.126.com, 188.com, and vip.188.com.

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。

Route, label, and clean routine email traffic with scripted IMAP rules instead of doing the same inbox chores by hand.

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 and manage email via IMAP (ProtonMail Bridge, Gmail, etc.). Check for new/unread messages, fetch content, search mailboxes, and mark as read/unread. Works with any IMAP server including ProtonMail Bridge.

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 and manage email via IMAP (ProtonMail Bridge, Gmail, etc.). Check for new/unread messages, fetch content, search mailboxes, and mark as read/unread. Works with any IMAP server including ProtonMail Bridge.

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。

aerc is a terminal-based email client written in Go with first-class support for IMAP, SMTP, JMAP, Maildir, and Notmuch. It features Vim-like keybindings, email threading, HTML rendering, built-in patch management, and deep UNIX integration through pipes and commands.

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。

139邮箱IMAP/POP3操作技能。支持通过IMAP/POP3协议查看收件箱/未读邮件、发送邮件、搜索邮件、管理邮件、邮件分拣。首次使用需配置账号和授权码。当用户需要操作139邮箱（mail.10086.cn）时触发此技能。

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。

Orchestrates an end-to-end long-read structural-variant pipeline - basecalling to minimap2 alignment (platform-matched preset) to Sniffles2/cuteSV/pbsv calling to optional assembly-based calling (dipcall/PAV) to two-step .snf cohort merging to Truvari benchmarking - chaining ONT and PacBio HiFi runs while handing the SV signal mechanism off to the component skills. Use when running a long-read SV workflow from reads to a benchmarked callset, choosing the minimap2 preset and SV caller by platform and goal, deciding when long reads are worth it for the insertions and repeat-mediated SVs short reads physically miss, building a joint-genotyped cohort with the two-step .snf design, or parameterizing a Truvari benchmark against GIAB HG002 Tier 1 plus CMRG. Not for the SV signal mechanism itself (see variant-calling/structural-variant-calling) or short-read SV.

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。

React Flow (ノードベース UI / フロー図ライブラリ for React) リファレンス。 ReactFlow コンポーネント、Node, Edge, Handle, Viewport、 カスタムノード / エッジ、Controls / MiniMap / Background、 レイアウトアルゴリズム (dagre, elkjs)、ドラッグ&ドロップ、エッジ接続。

Connect to 163/126/yeah.net (Coremail) email via IMAP, read inbox, search emails, and send emails via SMTP. Activate when user asks to check email, read mail, send email, or monitor inbox on 163/126/yeah.net accounts. Handles the Coremail-specific IMAP ID command requirement that causes "Unsafe Login" errors in standard clients.

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。

Himalaya CLI: IMAP/SMTP email from terminal.

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。

AutoFixture and NSubstitute Integration Guide - Implementing Auto-Mocking. Use when you need to automatically create mock objects and simplify testing of complex dependency injection. Covers AutoNSubstituteDataAttribute, Frozen mechanism, Greedy construction strategy. Includes customized handling for special dependencies like IMapper (AutoMapper/Mapster). Keywords: autofixture nsubstitute, auto mocking, AutoNSubstituteDataAttribute, auto-mocking, Frozen, AutoNSubstituteCustomization, AutoFixture.AutoNSubstitute, Greedy, fixture.Freeze, Received(), Returns(), IMapper, AutoMapper, Mapster, mapper testing

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。

AIエージェント専用のメール受信箱を用意し、送受信や返信、添付ファイルの処理を行います。メールで届く認証コードの確認や、受信をきっかけにした継続的な処理にも使えます。

• AIエージェント専用アドレスの作成
• メール送信と返信・添付ファイルの処理
• メールで届く認証コードの確認

Align long reads using minimap2 for Oxford Nanopore and PacBio data. Supports various presets for different read types and applications. Use when aligning ONT or PacBio reads to a reference genome for variant calling, SV detection, or coverage analysis.

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-seq (DRS) signal using m6Anet (multiple-instance-learning over DRACH 5-mer signal). Covers the upstream pipeline (Dorado/Guppy basecalling -> minimap2 map-ont -> nanopolish eventalign -> m6anet dataprep -> m6anet inference), per-site vs per-read probability including the mod_ratio stoichiometry column, the DRACH-only constraint, minimum-coverage thresholds (20-50 reads/site), multi-condition comparison via xPore/Nanocompore/ELIGOS, Dorado native modification calling (RNA004, 2024+), and the cDNA-vs-DRS distinction (cDNA Nanopore CANNOT detect modifications). Use when calling m6A from ONT DRS without immunoprecipitation, choosing m6Anet vs xPore vs Nanocompore vs ELIGOS vs Dorado native, interpreting probability_modified vs mod_ratio vs per-read probabilities, deciding between m6Anet (known DRACH sites) and Dorado/Remora (genome-wide screening), pinning RNA002 vs RNA004 chemistry and basecaller 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。

Discovers, classifies, and masks repetitive elements and transposable elements with RepeatModeler2 (de novo family library), RepeatMasker (masking against a library), EDTA (plant/structural TEs), or EarlGrey (auto-curating wrapper), and quantifies TE expression from RNA-seq with TEtranscripts/SQuIRE. Covers de-novo-library-as-curation-project, soft-vs-hard masking, the domesticated-gene over-masking massacre, Dfam-vs-RepBase, TE classification (Class I/II, family-vs-copy), Kimura repeat landscapes, LAI, and the RNA-seq multimapping problem. Use when masking repeats before gene prediction, building a TE library for a non-model genome, or analyzing transposable-element content or expression.

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 whole-genome alignments using Progressive Cactus (Armstrong 2020 reference-free clade-level WGA), Minigraph-Cactus (Hickey 2024 pangenome-aware), LASTZ chain/net (UCSC pipeline), MUMmer4 (Marçais 2018 pairwise), minimap2 -x asm5/10/20 (Li 2018 fast pairwise), AnchorWave (Song 2022 WGD-aware), and Mauve / progressiveMauve (bacterial). Operates the HAL toolkit (Hickey 2013) for downstream extraction including halSynteny, halLiftover, halBranchMutations, and hal2maf. Use when constructing multi-species alignments for comparative-annotation projection (TOGA), synteny detection, conservation analyses (phyloP / PhastCons), or pangenome graph construction; selecting between reference-free (Cactus) and reference-anchored (LASTZ chains/nets) approaches; tuning sensitivity for closely vs distantly related genomes; or producing HAL files for genome-wide downstream 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。

Analyzes alternative splicing from PacBio Iso-Seq (HiFi, Kinnex/MAS-Iso-seq) and Oxford Nanopore (direct cDNA, direct RNA, R10.4.1+) long-read RNA-seq with full-isoform resolution. Tools include FLAIR (correct/collapse/quantify/diffSplice for PacBio + ONT), IsoQuant (de-novo or annotation-guided isoform discovery 2024 SOTA), Bambu (annotation-aware Bayesian discovery + quantification with Novel Discovery Rate), SQANTI3 (isoform classification: FSM/ISM/NIC/NNC + artifact flags), rMATS-long (event calling on long-read isoforms), and minimap2 (-ax splice:hq for HiFi; -ax splice -k14 for ONT cDNA; add -uf only for direct RNA or stranded cDNA preps). Solves microexon detection, recursive splicing, complex multi-exon isoforms, and DTU without transcript-quantification uncertainty. Use when short-read AS limitations (anchor length, complex isoforms, microexons, recursive splicing, transcript ambiguity) demand full-isoform resolution.

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。

Predict enhancer-gene regulatory connections from ATAC-seq using ABC, ENCODE-rE2G, HiChIP, or Cicero. Use when linking distal enhancers to target genes, choosing between contact-aware (ABC, ENCODE-rE2G), accessibility-only (Cicero), and orthogonal (HiChIP H3K27ac, EpiMap) approaches, validating predictions against CRISPRi-FlowFISH gold-standard, or building cell-type-specific regulatory maps for fine-mapping or therapeutic target discovery.

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 building or fixing game UI in Godot 4.7: main menu, settings screen, HUD (health bar, ammo, minimap frame), Control layout, containers, anchors, themes in code, 'UI scales wrong on phones', 'text too small on 4K', notch or safe area, stretch mode and aspect, gamepad or keyboard menu navigation, focus lost, input rebinding screen, localization (CSV, PO, tr_n plurals, Arabic RTL, CJK fonts, pseudolocalization), screen reader accessibility, UI scale slider, or clicks not reaching the game.

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 building or fixing game UI in Unity 6.3: main menu, settings screen (resolution, quality, volume, key rebinding), HUD, health bar, minimap frame; choosing uGUI or UI Toolkit or mixing both; 'UI scales wrong on phones', portrait to 4K, Canvas Scaler, anchors, layout groups collapsing, sort order, UXML/USS, data binding, TextMeshPro or UI Toolkit fonts missing glyphs, localized menus, gamepad navigation, UI draw calls, canvas rebuild spikes, UI tests, or capturing UI to check it.

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。

Expert blueprint for racing games including vehicle physics (VehicleBody3D, suspension, friction), checkpoint systems (prevent shortcuts), rubber-banding AI (keep races competitive), drifting mechanics (reduce friction, boost on exit), camera feel (FOV increase with speed, motion blur), and UI (speedometer, lap timer, minimap). Use for arcade racers, kart racing, or realistic sims. Trigger keywords: racing_game, vehicle_physics, checkpoint_system, rubber_banding, drifting_mechanics, camera_feel.

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 building in-game HUDs — health bars, score displays, minimap, notifications, and damage numbers

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。