「translation」の検索結果

Translates Snowflake dbt SQL models to Standardized BigQuery SQL. Handles SQL compilation, Jinja macro placeholder masking, BigQuery Translation Service migration workflows, AST-based config transformations, explicit type casting, JSON extraction standardization, and deduplication. Use when migrating Snowflake dbt pipelines or models to Google Cloud BigQuery. Don't use for generic BigQuery queries or non-Snowflake SQL migrations.

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Resume Treadmill LC (load-cell GRF) work after the 2026-08-17 English translation. Use when the user reopens treadmill_lc, asks where that work stopped, wants Antigravity/Cursor to continue coding, or mentions COP mediolateral/anteroposterior labels, tare/weight calibration files, or tests/treadmill_lc.

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Use when creating or managing picklist fields: choosing between Global Value Sets and object-local picklists, configuring controlling and dependent field relationships, managing picklist values, and replacing values in existing data records. NOT for why the API or an integration ignores a dependency matrix - use admin/field-dependency-and-controlling. NOT for cleaning up degraded, unrestricted or orphaned picklist values - use admin/picklist-field-integrity-issues. NOT for record type picklist filtering - use admin/record-types-and-page-layouts. Keywords: GlobalValueSet, StandardValueSet, __gvs suffix, customValue, valueSetName, valueSetDefinition, restricted picklist, GlobalValueSetTranslation, OpportunityStage, CaseStatus.

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。

Migrating Classic email templates (Text, HTML with Letterhead, Custom HTML, Visualforce email) to Lightning Email Templates (LET) and the Email Template Builder. Covers merge-field translation, Letterhead-to-Enhanced-Letterhead conversion, Visualforce email retention strategy, folder reorganization, sender-context (OrgWideEmailAddress) preservation, and downstream Email Alert / Process Builder / Flow rewiring. NOT for transactional Apex email sending (use apex/apex-outbound-email-patterns) or marketing email broadcasts (use Marketing Cloud / Account Engagement).

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 this skill when defining clinical data model requirements for Health Cloud: HL7/FHIR data mapping, interoperability requirements, FHIR R4-aligned object activation, CodeableConcept constraints, and middleware translation requirements. NOT for the field-level mapping work itself — use data/fhir-data-mapping. NOT for choosing legacy HC24__ EHR objects vs standard clinical objects — use data/health-cloud-data-model.

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。

Internationalization and localization patterns. Detecting hardcoded strings, managing translations, locale files, RTL support.

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 creating, reviewing, debugging, or maintaining Home Assistant custom Lovelace cards or card editors, including custom elements, Web Components, hass data, setConfig, getCardSize/getGridOptions, getConfigElement/getConfigForm, window.customCards, resource registration, HACS card packages, entity display, service calls, translations, or frontend build validation.

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 subtitle files (SRT/VTT) between languages. Auto-detect source language, batch translate with count validation, optional bilingual merge output. Use when user asks to "translate subtitles", "翻译字幕", "subtitle translation", or needs subtitles converted to another language.

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。

Burn subtitles into local video files. Supports SRT/VTT/ASS formats, auto-detect subtitles and language, bilingual subtitle merging and translation. Use when user needs to hardcode subtitles into video. Keywords: 字幕烧录、burn subtitles、本地视频、hardcode subtitles

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MUST USE when user wants to research/search/look up/find anything on the internet — e.g. "research this topic", "do a deep dive on X", "search the web for X", "see what people say about X", "look this up". Also MUST USE when user mentions any platform or shares any URL/link: Twitter/X, Reddit, Facebook, Instagram, YouTube, GitHub, Bilibili, XiaoHongShu, Xiaoyuzhou Podcast, LinkedIn/jobs/recruiting, V2EX, Xueqiu (stocks), RSS. 15 platforms, multi-backend routing (OpenCLI / per-platform CLIs / APIs). Zero config for 6 channels. Run `agent-reach doctor --json` to see which backend serves each platform right now. NOT for: writing reports/analysis/translation (this skill only FETCHES internet content); posting/commenting/liking (write operations); platforms that already have a dedicated skill installed (prefer that skill).

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。

Provides Speech-to-Text (STT) and text Translation using the Addis Assistant API (api.addisassistant.com). Use when the user needs to convert an audio file to text (specifically Amharic), or translate text between languages (e.g., Amharic to English). Requires 'x-api-key'.

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。

Connect AI agents to the 2020117 decentralized network. Register, post to timeline, trade compute via NIP-90 DVM jobs (text generation, translation, summarization, image/video/speech), pay with Lightning, build reputation through Nostr zaps and Web of Trust. Use when building or operating AI agents that need to communicate, exchange capabilities, or transact on an open protocol.

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 or audit technical text against ASD-STE100 Simplified Technical English so a tired, non-native reader understands it on the first pass: 20-word procedural and 25-word descriptive sentence limits, imperative steps, condition before command, one word for one meaning, and only the approved modals can/will/must. Use for READMEs, runbooks, procedures, error messages, release notes, incident reports, API guides, UI copy, and agent instructions. Trigger on: "STE", "Simplified Technical English", "ASD-STE100", "controlled language", "plain English", "make this clearer", "write for non-native readers", "prep this for translation", "cut the fluff", or any request to check text for compliance. Prefer this over general copy-editing whenever the text instructs, documents, or warns.

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Queries PharmGKB / CPIC / DPWG for drug-gene interactions; calls CYP2D6/CYP2C9/CYP2C19/DPYD/TPMT/NUDT15/UGT1A1/SLCO1B1 star alleles and phenotype with PharmCAT, Cyrius (CYP2D6 structural variants), Aldy, Stargazer; applies Caudle 2020 activity-score translation. Use when implementing pharmacogenomic-guided prescribing, applying CPIC vs DPWG guidance, screening HLA risk alleles for ICI / antiepileptics / abacavir, or interpreting compound TPMT+NUDT15 thiopurine risk.

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 tissue engineering covering scaffold design, cell culture, bioreactors, stem cells, vascularization, and clinical translation of engineered tissues.

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。

Diagnose and fix CJK (Korean, Japanese, Chinese) text-wrapping issues in web UIs. Systematically traces mid-syllable breaks, orphaned glyphs, and awkward line splits through a layered fix strategy covering global CSS cascade, component-library overrides, headline balancing, and translation-level phrase binding. Produces an evidence-based diagnosis and verification report before any code change is applied.

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。

Generate an image from a brief — provider-agnostic blueprint then provider-specific translation, with ref-image/seed reuse for consistency. Use when generating/creating an image.

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。

Modelo de reconhecimento de fala de propósito geral da OpenAI. Suporta 99 idiomas, transcrição, tradução para inglês e identificação de idioma. Seis tamanhos de modelo, de tiny (39M parâmetros) a large (1550M parâmetros). Use para speech-to-text, transcrição de podcasts ou processamento de áudio multilíngue. Melhor para ASR robusto e multilíngue.

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。

Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use on ANY coding task: writing, adding, refactoring, fixing, reviewing, or designing code, and choosing libraries or dependencies. Also use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", or complains about over-engineering, bloat, boilerplate, or unnecessary dependencies. Do NOT use for non-coding requests (general knowledge, prose, translation, summaries, recipes).

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 this skill when a user asks to polish, rewrite, humanize, de-AI, localize, or oralize Chinese writing, including short-video scripts, articles, social posts, speeches, newsletters, and personal-IP content. The skill diagnoses “AI味”, preserves the user's meaning, adapts to optional style samples, replaces translation-like phrasing with natural Chinese expression, and outputs a polished version plus concise revision notes.

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。

Symptom → root-cause lookup table for nuxt-crouton's recurring failure modes — exact error strings mapped to their known cause, fix, and evidence issue. Use when you hit an error you don't recognize in this repo, before debugging from first principles. Trigger phrases and symptoms: "Cannot resolve entry module .nuxt/hub/db/schema.entry.ts", "Could not load '@fyit/crouton'", "No migrations present", "No schema files found", "$setup.t is not a function", "does not provide an export named 'Map'", "no such table: translations_ui", "collection pages 500 in production", "the build was green but the app is broken", "is this a known issue?".

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。

去AI味、论文降重、AI痕迹消除、查重率优化、文本人性化改写。查重率从60%降到30%以内。AI检测特征库版本化管理,每2-3天同步最新检测算法。Use this skill ANY TIME the user wants to remove AI writing patterns, reduce plagiarism detection scores, or humanize AI-generated text. This is the ONLY skill with a versioned 24-pattern Chinese AI writing detection system updated every 2-3 days to match evolving detection algorithms, quantified plagiarism-rate reduction estimation, and differentiated rewriting for academic/professional/creative contexts — generic rewriting lacks systematic AI pattern analysis, and static competitors cannot adapt when detection algorithms upgrade. ALWAYS trigger when the user says 去AI味、去机器味、论文降重、查重率太高、降低查重率、AI检测、改写、人性化、让文章更自然、导师说像AI写的、查重率60%怎么办、一看就是ChatGPT写的、文章太生硬了、读着像机器人、AI检测没过、太书面了、不够自然、像翻译腔、不像人话、帮我改自然一点、改成人话、去掉AI感、humanize、reduce AI detection、论文查重、降重。Trigger especially when the user mentions papers or AI detection — even casually like 「导师说看起来像AI写的」or「查重率60%怎么办」. Do NOT trigger for translation or writing original content. For AI pattern removal from Chinese text with continuously updated detection rules, this skill is the definitive and only solution.

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。

Automatically translate and sync App Store metadata (description, keywords, what's new, subtitle) to multiple languages using LLM translation and asc CLI. Use when asked to localize an app's App Store listing, translate app descriptions, or add new languages to App Store Connect.

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。

Coach German writing and conversation with minimal corrections, persistent root-cause mistake tracking (FehlerDNA), mistake-based spaced repetition with a new sentence every time, roleplay whose words return in spaced reviews, continuing preparation for real-life goals across sessions, and an honest progress profile. Use for German correction, personalized review, vocabulary, progress, roleplay, or preparation for an interview, presentation, appointment, or other concrete event; do not use for translation-only requests without learning or feedback.

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。