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概要と使いどころ
Use Exasol JDBC-based virtual schemas for federated read-only access to external databases such as PostgreSQL, Oracle, MySQL, SQL Server, and DB2. Covers database-source adapter selection, `CREATE VIRTUAL SCHEMA`, `ALTER VIRTUAL SCHEMA`, `EXPLAIN VIRTUAL`, metadata refresh, and query-side troubleshooting.
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。
Elite website image-to-code skill for Codex. For visually important web tasks, it must first generate the design image(s) itself, deeply analyze them, then implement the website to match them as closely as possible. In Codex, it must prefer large, readable, section-specific images instead of tiny compressed boards, generate fresh standalone images for sections or detail views instead of cropping old ones, avoid lazy under-generation, avoid cards-inside-cards-inside-cards UI, and keep the hero clean, spacious, readable, and visible on a small laptop.
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。
Improves typography by fixing font choices, hierarchy, sizing, weight, and readability so text feels intentional. Use when the user mentions fonts, type, readability, text hierarchy, sizing looks off, or wants more polished, intentional typography.
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。
Improves typography by fixing font choices, hierarchy, sizing, weight, and readability so text feels intentional. Use when the user mentions fonts, type, readability, text hierarchy, sizing looks off, or wants more polished, intentional typography.
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。
Detect anomalies in DNP3 (Distributed Network Protocol 3) communications used in SCADA systems by monitoring for unauthorized control commands, firmware update attempts, protocol violations, and deviations from baseline traffic patterns using deep packet inspection and machine learning approaches.
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。
This skill covers deploying anomaly detection systems for industrial control environments using machine learning models trained on OT network baselines, physics-based process models, and behavioral analysis of industrial protocol communications. It addresses building normal behavior profiles for SCADA polling patterns, detecting deviations in Modbus/DNP3/OPC UA traffic, identifying rogue devices, and correlating network anomalies with physical process data from historians.
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。
yt-dlpを使用した動画ダウンロードの専門スキル。YouTube、ニコニコ動画、Twitter/X、TikTok等1000以上のサイトから動画・音声・字幕をダウンロード。フォーマット選択、プレイリスト処理、メタデータ抽出を効率的に支援。Use when downloading videos, extracting audio, getting subtitles, or fetching metadata from YouTube and other video sites.
SF CLI経由でSalesforceレポートを作成するスキル。Metadata APIとREST APIの使い分け、フィールド命名規則、列数制限、レポートタイプ設定を網羅。カスタムオブジェクトレポート作成時の注意点も含む。Use when creating Salesforce reports via CLI, deploying report types, or automating report generation.
Two-phase code quality skill: (1) review codebase for structural smells — file LOC, method LOC, accidental complexity, test readability — producing a structured report, then (2) fix all smells via provable refactorings with ACN micro commits and green-bar-at-all-times discipline. Use this skill when the user says 'sweep', 'code review', 'find code smells', 'check method lengths', 'review for complexity', 'tidy up the codebase', 'refactor smells', or asks about long methods, test readability, or accidental complexity. Also trigger when users ask to 'clean up' or 'improve code quality' across multiple files.
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。
Especialista para todo el proceso de solicitud de empleo. Analiza ofertas de trabajo, optimiza perfiles (LinkedIn/CV) y genera cartas de presentación personalizadas. Genera CVs en ASCII a partir de una base de datos SQLite y una estructura de carpetas. cv_generator.py está adaptado de forma independiente -- no requiere la ejecución de BACH.
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。
Fetch video transcripts (subtitles) and metadata from online video sources and output them as Markdown, JSON, or plain text. Currently supported: YouTube. Prefers manually created subtitles, falls back to auto-generated ones.
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。
Analysiert bereitgestellte Medienlisten und Metadaten unabhängig von einer bestimmten Medien-App.
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。
Reads a contract list (spreadsheet, CSV or pasted table) and returns a DRAFT renewal radar: each active contract's end date, notice deadline with its arithmetic, days remaining, renewal type, owner and the decision it needs as options, sorted by urgency, with owner action lists and a deadline calendar. Never renews, terminates, serves notice or recommends. Use when the user asks to "build a renewal tracker", "tell me what comes up for renewal", "work out when notice is due", "show me which contracts auto-renew" or "run the quarterly contract review". Do not use for reviewing one contract's full text or clauses, use contract-review-pack instead. Drafts for human review; never approves, authorises or signs off.
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。
ユーザーの明示依頼により、dotfiles本体を中央engineで保全commit、統合、adapter再生成、submodule整合、pushまで同期する。
- Extract and interpret embedded file metadata with exiftool — EXIF GPS coordinates, camera make, model and serial, DateTimeOriginal and CreateDate timestamps, XMP and IPTC fields, and Office and PDF… Use when reading EXIF from a photo, checking who really wrote a document, dating a file, fingerprinting a camera or phone, or investigating provenance in JPEG, HEIC, RAW, MP4, DOCX, XLSX or PDF
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。
Split one source post into tier-sized drafts (teaser, main social post, longread, technical dev-log) with cross-links downward and a canonical link back to the repository. Draft-first: publishes nothing itself. Triggers: "/episode", "/adapt", "adapt this post", "make an episode".
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 command-only adapters for `eval` run mode using strict stdin/stdout JSON contracts.
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。
The AI native file format. EXIF for AI — stamps every file with trust scores, source provenance, and compliance metadata. Embeds into 20+ formats (DOCX, PDF, images, code). EU AI Act, SOX, HIPAA aud
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 asks to "codify our brand voice", "define naming rules for our products and tiers", or "write the tone-of-voice guide with banned phrases"; produces the brand-level voice canon (register, tone spectrum, banned-phrase list, few-shot examples drawn only from the brand's own published material) and the naming tax (product / feature / tier naming rules plus approved and banned terms) that seeds the narrative-registry canon and that every channel's voice adaptation points up to. Not for per-platform voice adaptation — use channel-registry's voice-dossier; not for finished copy or blog posts — use content-writer; not for the message hierarchy itself — use message-system-architect; not for claim adjudication — use offer-claims-registry. 品牌语气/词汇表/命名税/禁用词/品牌语言规范
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。
Hive CE (Community Edition v2.19.x) NoSQL object database for Flutter providing blazing-fast key-value and object storage with TypeAdapters. Use this skill when implementing offline-first architecture, high-performance local data caching, NoSQL document-style object stores, custom TypeAdapter serialization for complex objects, lazy loading boxes for memory efficiency, encrypted boxes (HiveAES encryption), database compaction for size optimization, storing large datasets without SQL schema overhead, implementing local-first sync patterns, or migrating from SQLite to NoSQL. Supports primitive types, custom objects, lists, and maps. Ideal for apps requiring ultra-fast read/write operations (microsecond latency), object persistence without ORM complexity, or local-first data architecture.
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 data visualization charts in Flutter using the fl_chart package (v1.2.0). Supports LineChart, BarChart, PieChart, ScatterChart, RadarChart, and CandlestickChart with implicit animations, touch interactivity, and pan/zoom transformations. Use when building any Flutter chart, graph, or data visualization — including line graphs for trends, bar charts for comparisons, pie/donut charts for proportions, scatter plots for distributions, radar charts for multi-axis comparisons, or candlestick charts for financial OHLC data. Also use when customizing chart axes, titles, tooltips, grid lines, touch callbacks, chart animations, or chart zoom/pan behavior.
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。
Latest research insight: Adaptive LLM routing under budget constraints
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。
API + Python SDK for ordering cell-free protein expression and binding assays. Submit sequences for expression (10–100 µg), measure binding affinity (KD) against targets, track status, and retrieve results programmatically — no wet-lab setup. Built for ML-guided directed evolution and antibody/nanobody optimization. Requires Adaptyv account and 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。