🇺🇸 ASO & Mobile App Growth Playbook 2026 — Complete App Store Optimization guide. ASO keyword ranking, App Store & Google Play listing optimization, app cold start, UGC creator operations, TikTok/Instagram/YouTube Shorts marketing, AI-matrix content scaling, mobile user acquisition. 🇨🇳 ASO 增长与 App 冷启动权威指南 — 从应用商店优化到 UGC 运营、多平台内容策略、AI 辅助内容创作的完整实操手册。 🇯🇵 ASO＆アプリコールドスタート成長ガイド — App Store最適化からUGC運営、マルチプラットフォーム戦略、AIマトリックスまで。 🇰🇷 ASO 및 앱 콜드 스타트 성장 플레이북 — 앱스토어 최적화부터 UGC 운영, 멀티플랫폼 전략, AI 매트릭스까지. Triggers: "ASO" | "App Store Optimization" | "ASO keywords" | "App Store ranking" | "Google Play optimization" | "app cold start" | "app launch" | "mobile app growth" | "user acquisition" | "UA" | "UGC creator" | "TikTok marketing" | "Instagram Reels" | "YouTube Shorts" | "creator matrix" | "app growth" | "应用商店优化" | "App冷启动" | "UGC运营" | "矩阵号"
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概要と使いどころ
Classical orbital mechanics from Kepler to Hohmann. Covers the six orbital elements, Kepler's three laws, vis-viva, orbit types (circular, elliptical, parabolic, hyperbolic), transfer orbits, gravity assists, the two-body problem, and practical methods for computing ephemerides. Use when reasoning about planet motion, spacecraft trajectories, comet orbits, exoplanet transits, or binary star dynamics.
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Extract data from subcontractor bid PDFs and produce a comparison spreadsheet. Feeds into /bid-evaluator. Triggers: 'tabulate bids', 'bid comparison', 'compare bids', 'buyout analysis', 'bid tab'.
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Audit mobile applications (iOS and Android) against RAAM 1.1 (Luxembourg Mobile Accessibility Assessment Framework). Use when reviewing existing mobile app code for accessibility compliance, generating audit reports, checking conformance levels, or preparing for Luxembourg accessibility certification. Covers all 15 themes with platform-specific test procedures. Default target: Level AA.
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Develop accessible mobile applications (iOS and Android) conforming to RAAM 1.1 (Luxembourg Mobile Accessibility Assessment Framework, based on EN 301 549 v3.2.1 / WCAG 2.1). Use when building native mobile apps, React Native, Flutter, or any mobile UI that must meet Luxembourg accessibility law. Covers all 15 RAAM themes with platform-specific code guidance. Default conformance target: Level AA.
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"Implement and select ad bidding strategies from manual CPC to automated target-CPA and target-ROAS. Use this skill when the user needs to choose a bidding strategy, set up automated bidding, or optimize bid parameters — even if they say 'what bidding strategy should I use', 'target CPA setup', or 'smart bidding configuration'.".
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Hunts for living-off-the-land binary (LOLBin) abuse in Windows process-creation telemetry by flagging trusted system binaries used with download, execution-proxy, or encoded-command arguments. Activates for requests to hunt LOLBins, detect signed-binary proxy execution, or find suspicious certutil/mshta/regsvr32 usage.
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Fingerprints unknown binaries using rabin2 — detects architecture (ARM, x86, MIPS), ABI, libc, dependencies, and strings of interest. Use when first encountering an unknown binary, ELF file, or firmware blob, or when you need architecture or ABI information before committing to deeper analysis.
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Plan a webinar end-to-end using April Dunford's Obviously Awesome positioning framework to find the topic angle that makes the webinar obviously valuable to the right audience. Produces topic positioning, abstract, speaker brief, registration page, promotion sequence, day-of run-of-show, and post-webinar follow-up. Use when the user asks to plan a webinar, virtual event, online workshop, "we need a webinar on X", host a webinar, online masterclass, or any live virtual event with promotion and follow-up. Reads ICP, services, and brand voice from knowledge/. For the promotion emails, see email-nurture. For the deck, see ppt-maker. For the social promotion plan, see social-calendar.
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Create a requirements traceability matrix linking requirements to design, test, and delivery. Use when the user says "traceability matrix", "RTM", "requirements traceability", "link requirements to tests", "trace requirements", "coverage matrix", "are all requirements tested", "requirements coverage", "forward traceability", "backward traceability" - even if they don't explicitly say "traceability matrix".
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Configure and control the claude-bionify bionic reading plugin. Use when the user asks about bionic reading settings (fixation/strength, boundary, minimum word length, acronyms, URLs, headings), wants to turn the bionic display on, off, or toggle it, asks for the current status, or asks how to use the /claude-bionify commands.
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Supermicro X11DPU/X10DRT-P BIOS Setup 操作。KVM スクリーンショット + キーストロークで BIOS メニューを操作する。BIOS 設定変更、確認、保存を行う。4-6号機 + 10号機対応。
WCAG 準拠のアクセシビリティチェックをチェックリスト駆動で実行するスキル。 コンポーネント・ページ・PR に対して Pass/Fail/N/A/Needs review の構造化レポートを 生成し、エビデンスと修正案を提示する。 「アクセシビリティチェック」「a11y チェック」「WCAG をチェック」「a11y レビュー」 「アクセシビリティ監査」「WCAG 準拠確認」「アクセシビリティレポート」への言及、 または PR やコンポーネントのアクセシビリティレビュー依頼で発動する。 English: "check accessibility", "a11y audit", "a11y check", "WCAG review", "accessibility report", "screen reader test", "review for a11y", "review this PR for accessibility", "axe audit"
Processes eDNA metabarcoding from raw paired-end reads to species tables, navigating ASV (DADA2, UNOISE3) vs OTU (swarm v2) decision (Callahan 2017 vs Schloss multi-copy-16S critique), marker/primer choice (Leray COI, MiFish 12S, 515F/806R 16S, ITS2) with primer-specific bias, OBITools3 v3 command-name break (obi stats plural; .tar.gz taxonomy), tag-jumping with dual-indexing (Schnell 2015; NovaSeq 10x MiSeq), decontam as screening-not-classifier (Davis 2018), read-counts-not-abundance critique (Lamb 2019), site-occupancy modeling (Ficetola 2015), Naive-Bayes calibration limits (Bokulich 2018), and eDNA decay (Strickler 2015). Use when going from raw eDNA FASTQ to species tables, picking marker + denoising pipeline, deciding whether read counts represent abundance, applying occupancy modeling, configuring OBITools3 v3, or interpreting decontam output. Not for clinical 16S microbiome (see microbiome/amplicon-processing).
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Estimates time-scaled phylogenies, molecular-clock rates, effective reproduction number R_e, and population dynamics from dated pathogen genomes using TreeTime (maximum-likelihood) and BEAST2 (Bayesian; strict/relaxed clocks; coalescent, Bayesian-Skyline, Skygrid, Birth-Death-Skyline, and sampled-ancestor priors; structured coalescent via MASCOT). Covers root-to-tip clock QC via TempEst, date-randomisation tests, recombination masking via Gubbins/ClonalFrameML before clock inference for recombining bacteria, BDSKY origin-vs-rootHeight pitfalls, sampling-bias correction, multi-chain convergence diagnostics, and reconciling phylodynamic R_e with case-based R_t. Use when dating outbreak origins, estimating substitution rates, inferring R_e through time, building time-calibrated Nextstrain Augur trees, choosing between strict and relaxed clocks, fitting Birth-Death-Skyline models, diagnosing temporal-signal failure, running MASCOT for structured-population analyses, or using UShER for pandemic-scale placement.
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Designs and analyzes combinatorial CRISPR screens covering paired-Cas9 (Big Papi, Najm 2018), enhanced AsCas12a multiplex (enCas12a, DeWeirdt 2021), in4mer 4-guide-array Cas12a (Esmaeili Anvar N et al 2024 Nat Commun 15:3577) and the Inzolia paralog-pair library, paralog-buffering detection (Dede 2020 Genome Biol; Thompson 2021 Nat Commun 12:1302), genetic-interaction (GI) scoring as observed_double_LFC minus expected_additive_double_LFC, synthetic-lethal and synthetic-rescue interaction interpretation, the half-of-essentiality buffered by paralogs phenomenon, multiplex screen statistical analysis with MAGeCK MLE interaction terms, and the relationship to single-cell combinatorial Perturb-seq. Use when designing a paralog or pathway-pair screen, choosing between paired-Cas9 (Big Papi) and Cas12a multiplex (Inzolia), interpreting genetic interaction scores, identifying synthetic-lethal targets for drug development, or scaling beyond single-gene CRISPR screens.
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Detects allele-specific transcription factor or histone modification binding from heterozygous-variant ChIP-seq using WASP (reference-bias filter; mandatory upstream), RASQUAL (joint QTL + bias-corrected testing), BaalChIP (Bayesian beta-binomial with copy-number-aware overdispersion), and AlleleSeq (personalized diploid genome). Handles imprinted-locus awareness, X-inactivation artifacts, cancer copy-number imbalance, and integration with downstream caQTL / bQTL mapping. Use when identifying variants with allelic effects on TF binding, fine-mapping causal regulatory variants, validating deep-learning variant predictions, or characterizing cis-acting regulatory effects.
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Identifies differentially bound ChIP-seq regions between conditions using DiffBind, csaw (sliding windows), DESeq2/edgeR/PyDESeq2 on count matrices, NormR (control-aware), or MAnorm2. Distinguishes three distinct normalization problems (composition bias, trended bias, global shifts) and matches each to its appropriate fix including spike-in scaling. Use when comparing ChIP-seq binding between experimental conditions, choosing normalization for global vs local changes, integrating spike-in data, or reconciling DiffBind/DESeq2 disagreement.
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Infer cis-regulatory connections (peak-to-peak co-accessibility) from scATAC-seq using Cicero, ArchR getCoAccessibility, or SCENIC+. Use when linking enhancer accessibility to promoter accessibility, identifying enhancer-gene pairs from chromatin alone (without paired RNA), running gene-regulatory inference combining ATAC + RNA, or comparing predicted regulatory contacts against Hi-C/Micro-C ground truth.
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。
End-to-end binder design using BindCraft hallucination. Use this skill when: (1) Designing protein binders with built-in AF2 validation, (2) Running production-quality binder campaigns, (3) Using different design protocols (fast, default, slow), (4) Need joint backbone and sequence optimization, (5) Want high experimental success rate. For backbone-only generation, use rfdiffusion. For QC thresholds, use protein-qc. For tool selection guidance, use binder-design.
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-level biomaterials covering biocompatibility, metals, ceramics, and polymers for medical implants, surface modification, host response, and regulatory considerations.
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-level exoplanet science covering detection methods, orbital dynamics, planetary atmospheres, habitability, and the search for biosignatures.
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-level biochemistry from a biology perspective covering metabolic pathways, enzyme kinetics, bioenergetics, signal transduction, and the biochemical basis of cellular processes.
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Quantiza LLMs para 8-bit ou 4-bit com redução de memória de 50-75% e perda mínima de acurácia. Use quando a memória GPU é limitada, precisa ajustar modelos maiores ou quer inferência mais rápida. Suporta formatos INT8, NF4, FP4, treinamento QLoRA e otimizadores 8-bit. Funciona com HuggingFace Transformers.
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。