210 件 ・ 関連度順
概要と使いどころ
Provider-independent asset continuity and version management for generated-media production. Use when an agent must track generated or reference assets, prompts, seeds, model/tool versions, manifests, approvals, edit decisions, derivatives, localization variants, metadata/provenance, and continuity QA across image, video, audio, avatar, product-ad, social, explainer, or film-style pipelines.
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。
Provider-independent media quality control and delivery direction for generated images, video, audio, ads, product content, social clips, broadcast and streaming assets, localization packages, and mixed-source edits. Use when an agent must define final export specs, inspect technical and perceptual quality, check captions/audio/color/accessibility/provenance/rights, create delivery sheets, version filenames, checksums, manifests, package deliverables, set acceptance or rejection criteria, and perform final delivery QA before handoff to a platform, broadcaster, streamer, client, or ad trafficker.
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。
Provider-independent dialogue editing and ADR direction for AI agents producing generated videos, films, ads, avatar clips, explainers, localization/dubbing, podcasts, recuts, and social content. Use for dialogue prep, repair, room tone, take comping, sync, ADR cueing, dubbing direction, pronunciation, de-essing, plosives, mouth clicks, voice continuity, synthetic voice consent boundaries, captions/transcripts handoff, mix handoff, loudness, intelligibility, accessibility, and QA.
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。
Provider-independent explainer video production for AI agents creating educational, product, concept, nonprofit/public-service, onboarding, training, animated, mixed-media, and short social explainers. Use when an agent must turn a topic, brief, research corpus, product, process, policy, dataset, or complex idea into a factual, accessible, narrated, captioned, storyboarded, generated-media-ready explainer video with claim review, localization, pacing, variants, and QA.
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。
Maps GWAS-implicated loci to candidate effector (causal) genes by integrating variant-to-gene (V2G) features via Open Targets L2G (Mountjoy 2021), MAGMA gene-based association (de Leeuw 2015), FUMA SNP2GENE, cS2G combined SNP-to-gene scores (Gazal 2022), Polygenic Priority Scores (PoPS, Weeks 2023), FLAMES, INQUISIT, DEPICT, and enhancer-gene predictors (ABC, ENCODE-rE2G). Use when narrowing a GWAS lead locus to a candidate causal gene, picking between proximity, eQTL-based, and similarity-based prioritizers, integrating multi-evidence streams (fine-mapping, colocalization, ABC enhancer-gene, distance, chromatin), reconciling discordant L2G vs PoPS calls, prioritizing tissue-specific eQTL evidence, or triangulating across at least three independent lines of evidence for a publication-grade effector-gene nomination.
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。
Resolves GWAS associations to candidate causal variants and credible sets via SuSiE, susie_rss, FINEMAP, CAVIAR, DAP-G, PAINTOR, PolyFun, SuSiEx, MultiSuSiE, and FOCUS. Use when narrowing a GWAS lead SNP to a 95 percent credible set, choosing between in-sample and reference LD, calibrating non-sparse loci with SuSiE-inf or FINEMAP-inf, integrating functional priors via PolyFun, fine-mapping across ancestries with SuSiEx, diagnosing LD mismatch via estimate_s_rss and kriging_rss, handling HLA or long-range LD, or feeding credible sets into coloc.susie for colocalization.
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 post-GWAS causal inference pipeline orchestrating heritability partitioning, genetic correlation, Mendelian randomization with CHP-aware sensitivity (CAUSE / LHC-MR), colocalization, fine-mapping with SuSiE / FOCUS, mediation, TWAS triangulation, cis-pQTL drug-target MR, effector-gene prioritization (L2G / PoPS / cS2G), and GenomicSEM common-factor GWAS. Use when triangulating causal inference across multiple complementary methods, prioritizing tissues via stratified LDSC, nominating or de-risking drug targets, mapping a lead SNP to a candidate effector gene, modeling shared genetic architecture across correlated traits, or producing a STROBE-MR-compliant publication-grade evidence battery from GWAS summary statistics.
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。
Workflow for fine-mapping, colocalization, mediation, pleiotropy analysis, and Mendelian randomization.
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。
You are an expert in Contentful, the API-first content platform for enterprise teams. You help developers integrate Contentful's Content Delivery API (CDN-backed, read), Content Management API (write), and Content Preview API (draft content) into websites and apps — using typed content models, localization, rich text rendering, image transformations, and webhooks for build triggers.
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 mobile app listings for discovery and conversion in Apple App Store and Google Play. Use when tasks involve ASO keyword research, title and subtitle optimization, screenshot and preview video design, A/B testing store listings, review management, localization for international markets, tracking keyword rankings, or improving download conversion rates. Covers both iOS and Android store algorithms and best practices.
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。
Binding-resolved Python symbol queries via pyright — every true caller (--refs), the real definition (--def), or an inferred signature (--hover) of a .py symbol, excluding the same-named false positives text search cannot tell apart. Use when a task needs ALL callers or users of a named Python symbol and grep would over-match. Python only, and only for the caller/definition question: measured 2026-07-04 on real issue-localization tasks, plain ripgrep tied or beat the semantic and indexed-regex tiers at 4-60x less wall-clock, so those tiers survive below without being a default.
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 interfaces that adapt gracefully to multiple languages, writing directions, and cultural contexts.
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。
Translate existing blog posts into one or more target languages with SEO-optimized localization. Produces native-quality translations that preserve markdown structure, frontmatter, schema JSON-LD, image and chart embeds, and citation capsules. Localizes keywords, meta tags, numbers, dates, currencies, and quote styles per locale. Flags machine-translation artifacts for review. Run BEFORE blog-localize: this handles language conversion; localize handles cultural adaptation after translation completes. Use when user says "translate blog", "blog translate", "uebersetzen", "traduire", "traducir", "translate post", "blog auf Deutsch", "blog en espanol".
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 has a video + an SRT and wants the subtitles either burned into the pixels (libass, always-visible) or soft-muxed as a togglable track. Also handles the final composite step for the localization pipeline — burn subs, mix a dub track, and keep the original audio as a low-volume bed, all in ONE ffmpeg encode (no cascade). Verifies libass availability and auto-downloads a static evermeet ffmpeg build when Homebrew's stripped binary lacks it. Triggers — "烧字幕", "硬字幕", "burn subtitles", "burn-in subs", "embed subtitle", "soft mux SRT", "把字幕烧进视频", "做最终合成".
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 App Store and Google Play listings via a 7-phase, plan-approval-gated ASO workflow (keyword strategy, metadata, localization). Don't use for web SEO, paid UA campaigns, or pre-submission compliance audits.
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。
Professional translation and localization for 8 languages (ES, JA, FR, DE, PT, ZH, KO, AR). Covers tone matrix, formality levels, i18n patterns (react-intl, i18next, ICU), RTL layout, cultural adaptation, and locale formatting. Use when user asks to translate text, localize an app, adapt tone, review translations, add i18n, or set up RTL.
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。
Phase D of a WinForms-to-Avalonia migration: build the Avalonia UI shell with composition, MVVM state and commands, responsive XAML, accessibility, localization boundaries, and behavior-focused unit/Headless tests. Use only when an explicit migration is ready to port Forms or when the orchestrator routes here. Prefer this over control-by-control ports.
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。
Convert PDF files into editable Word documents with ComPDF. Use for PDF-to-Word requests involving contracts, reports, forms, proposals, review, revision, localization, or business reuse.
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。
Maintain HitKeep dashboard localization. Use whenever a contributor adds or changes user-visible dashboard text, Transloco keys, locale JSON files, OptimusUI locale behavior, language switching, translated labels, localized layout, date/number/duration formatting, or supported dashboard 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。
Write and rewrite Turkish so it reads as native Turkish rather than translated English. Use for Turkish marketing copy, product and UI text, localization, documentation, support, legal or security prose, and reviews of AI-written Turkish. Detect translationese, copied clause structure, nominalization, wrong case and collocations, generic helper verbs, SaaS and sales calques, jargon leakage, forced slogans, corporate abstraction, cross-sector template residue, unsupported operational claims, and page-level repetition.
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。
Prioritize drug targets from a ranked gene list (e.g., scRNA-seq DE output) by orchestrating parallel API queries against UniProt, OpenTargets (with integrated DepMap CRISPR essentiality + gnomAD constraint), PubMed, the Human Protein Atlas (HPA), and ChEMBL tool compounds, then re-ranking by a composite score combining protein localization, druggability, disease genetics, tissue specificity (safety), focus-cell-type expression, CRISPR essentiality, LoF safety constraint, and research maturity. Use whenever the user wants to filter, triage, prioritize, or "do due diligence" on a list of candidate genes for drug discovery, especially after a DE / DEG analysis when they say things like "which of these should I follow up on", "filter for druggable targets", "make a target dossier", "rank these for tractability", "annotate these genes for druggability", or "build a target report". Trigger even when the user says just "filter these candidate genes" or hands over a CSV from a DE pipeline.
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 Product / SaaS Go-Global Complete SOP — From competitor research to launch to monetization. A full-cycle playbook covering Phase 0-5 (market validation, positioning, first 100 users, user interviews, beta-to-growth) plus open-source launch, Product Hunt, Reddit, SEO/GEO, conversion, and org principles. **Defaults to dev tools / OSS / B2B SaaS; for 2C products (education, apps, games) the launch channels & metrics differ — see gingiris-seo-geo/references/2c-adaptation.md.** 🇨🇳 AI 产品 / SaaS 企业出海完整 SOP — 从竞品调研到 Launch 到商业化的全流程操作手册。覆盖 Phase 0-5（市场验证、定位、前100用户、用户访谈、Beta转增长）+ 开源发布、Product Hunt、Reddit、SEO/GEO、转化与组织原则。**默认面向开发者工具/开源/B2B SaaS；2C 产品（教育/应用/游戏）的启动渠道与指标不同，见 gingiris-seo-geo/references/2c-adaptation.md。** 🇯🇵 AI製品/SaaS海外展開フルサイクルSOP — 競合調査からローンチ、マネタイズまで。Phase 0-5（市場検証、ポジショニング、最初の100ユーザー、ユーザーインタビュー、ベータから成長）＋オープンソース、Product Hunt、Reddit、SEO/GEO、コンバージョン、組織原則。 🇰🇷 AI 제품/SaaS 글로벌 진출 완전 SOP — 경쟁사 조사부터 런칭, 수익화까지 전 주기 플레이북. Phase 0-5(시장 검증, 포지셔닝, 첫 100명 사용자, 사용자 인터뷰, 베타→성장) + 오픈소스 런칭, Product Hunt, Reddit, SEO/GEO, 전환, 조직 원칙. Triggers: "go global" | "出海" | "overseas expansion" | "GTM" | "cold start" | "launch strategy" | "international expansion" | "海外增长" | "出海SOP" | "product launch overseas" | "海外进出" | "グローバル展開" | "글로벌 진출" | "go-to-market" | "出海打法"
Plan and run manual tests of the project's running app. Runs a session in one of five modes: exploratory, verification, smoke, assessment (UX, localization, accessibility, improvement review), or AI probe. Also writes a manual test plan that holds only what automated tests cannot judge. Use whenever the user asks, in any language, for something to be tested by hand or for a manual test plan — "manual test", "exploratory test", "bug hunt", "verify the bug fix", "smoke test", "QA this screen", "review this screen's UX", "what would you improve", "check the localized copy", "test the AI agent's answers", "write manual test cases", "kịch bản test manual" — or assigns a test design, test plan or test-case IDs to execute by hand. Not for writing automated tests.
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。
Implements email service abstraction with SendGrid provider. Includes template support, localization, async sending, and domain event integration for transactional emails.
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。