991 件 ・ 関連度順
概要と使いどころ
Translates LaTeX documents (.tex) to Typst (.typ), focusing on article-class documents. Use when asked to convert, port, migrate, or translate LaTeX to Typst. Covers document structure, text formatting, page layout, math equations and symbols, figures, tables, TikZ-to-CeTZ diagrams, bibliography, cross-references, footnotes, and code blocks. Includes comprehensive symbol mapping tables.
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Use when designing, redrawing, or validating research-paper figures and tables, including Matplotlib plots, LaTeX tables, benchmarks, captions, legends, annotations, color, and typography. Preserves exact evidence and checks rendered PDFs for clipping, overlap, and readability.
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 a task needs the judgment of an Electrical and Electronics Drafter — sizing a conductor and conduit for a panel or feeder circuit against NEC ampacity and fill tables, building a schematic/elementary diagram or one-line diagram on IEEE 315/ANSI Y32.2 symbols, cross-referencing wire numbers between a schematic and a panel wiring diagram, sizing a PCB trace against IPC-2221 current tables, or QC-checking an electrical drawing set before issuance.
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 publication-ready methods sections, figure legends, supplementary tables, and data availability statements from ENCODE analysis provenance. Implements the scientific documentation standards requiring complete metadata reporting. Use when the user needs to write methods, generate figure legends, create supplementary tables, draft data availability statements, compile tool citations, or auto-generate any publication text from their ENCODE analysis. Trigger on: methods section, figure legend, supplementary table, data availability, tool citations, publication writing, manuscript, write methods, methods draft, write up, write-up, paper writing, reproducible methods.
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 the downstream impact (blast radius) when a BigQuery table or view is broken, stale, or modified. Identifies all downstream tables, dashboards, and processes that will be affected. Use when: - Performing a blast radius or impact analysis for a BigQuery table or view. - Assessing the consequences of modifying, deleting, or pausing updates to a BigQuery asset. - Identifying downstream dependencies (tables, dashboards, processes) of a BigQuery asset. Don't use for: - General BigQuery querying or data analysis (use BigQuery-related tools instead). - Non-BigQuery assets (e.g., Cloud Storage files) unless they are part of the BigQuery lineage. - Creating or modifying lineage links directly.
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。
Manages datasets, tables, and jobs in BigQuery. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources (datasets, tables, views), or perform basic data ingestion and 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。
Use when tuning the numbers in a game — economy curves, progression rates, difficulty pacing, drop tables, win/loss odds, time-to-X targets, and currency velocities. Triggers on "balance pass", "tune the economy", "progression curve", "difficulty curve", "drop rate", "XP curve", "TTK", "time-to-content", "balance the economy", "spreadsheet model", "economy sim", or a system spec from game-systems-designer with `TBD` placeholders. Produces an economy spreadsheet, balance pass plan, sim outputs, and per-system balance tables. Stops at the numbers — does not change system rules or pricing. For systems design see game-systems-designer; for store catalog see iap-manager.
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。
Generates appellate-filing-ready Tables of Contents, Tables of Authorities, and Certificates of Compliance under FRAP 32(g) and related rules. Produces defensible word-count calculations with transparent exclusions and anti-hallucination guardrails for pagination and citations. Covers federal circuits, state appellate courts, and U.S. Supreme Court variations. Use when building TOC, TOA, compliance certificates, formatting briefs for filing, or when the user mentions word count calculation, FRAP 32 compliance, appellate brief assembly, or page numbering.
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。
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).
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。
Azure Tables SDK for Python (Storage and Cosmos DB). Use for NoSQL key-value storage, entity CRUD, and batch operations.
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 table storage applications using the Azure Tables SDK for Java. Works with both Azure Table Storage and Cosmos DB Table API.
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。
Rembric dashboard UI work (dark monochrome zinc surfaces, lime accent, Geist type, Spectrum data-tables) — building / editing / extending pages, styles, components, modals, tables, filters, pagination, mobile responsive, destructive confirmations. Use when the user asks for changes under `apps/web/src/app/dashboard/` or `apps/web/src/components/dashboard/`, mentions Rembric design tokens (lime, zinc, command bar, StatusPill, hl-lime, data-table), or requests a new dashboard page / form / table.
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 data structures covering arrays, linked lists, trees, heaps, hash tables, graphs, and advanced structures like segment trees, tries, and union-find.
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再発しやすい危険な実装パターンを、安全側に倒れる標準パターン・禁止事項・共通層・静的ルール候補へ 変換するスキル。ORM強制、deny-by-default認可、サービス経由I/O、永続化確認後の成功表示などを設計する。 レビューで危険コードを見つけるのではなく、危険コードを書きにくくする設計標準を作ることが目的。 Use when turning repeated defect patterns into safe architectural defaults, forbidden-to-safe mapping tables, common layer designs, and enforceable static analysis rules.
Creates data visualizations (charts, graphs, tables) optimized for AI engine parsing and citation. Produces inline SVG/HTML with text summaries, data tables, and JSON-LD so AI engines can quote the data.
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 table storage applications with Azure Tables SDK for Java. Use when working with Azure Table Storage or Cosmos DB Table API for NoSQL key-value data, schemaless storage, or structured data at...
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。
Azure Tables SDK for Python (Storage and Cosmos DB). Use for NoSQL key-value storage, entity CRUD, and batch operations.
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 working with Coda — coda document management covering docs, pages, tables, formulas, and workspace analytics. Use when auditing Coda workspace usage, managing documents and tables, querying structured data, or analyzing collaboration patterns across a Coda organization.
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。
Core Python library for astronomy/astrophysics: units with dimensional analysis, celestial coordinate transforms (ICRS/Galactic/AltAz/FK5), FITS I/O, tables (FITS/HDF5/VOTable/CSV), cosmology (Planck18, distance/age), precise time (UTC/TAI/TT/TDB, Julian, barycentric), WCS pixel-world mapping, model fitting. For general tables use pandas/polars; for radio interferometry use CASA.
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 table storage applications using the Azure Tables SDK for Java. Works with both Azure Table Storage and Cosmos DB Table API.
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。
Azure Tables SDK for Python (Storage and Cosmos DB). Use for NoSQL key-value storage, entity CRUD, and batch operations.
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。
Android Jetpack Compose (Kotlin) の UI 基盤リファレンス。androidx, Material3 土台。 Composable, Modifier, CompositionLocal, remember, mutableStateOf, State, LaunchedEffect。 Column, Row, Box, LazyColumn, Pager, ConstraintLayout, WindowSizeClass, ペインスキャフォールド。 BasicText, BasicTextField, TextStyle, IME, clickable, ジェスチャ, フォーカス, セマンティクス。
Facilitate Kimball-style dimensional (data warehouse / BI) modeling sessions through conversation, producing DimML (Dimensional Modeling Language, YAML) as the primary artifact plus a bus-matrix + star-schema HTML. Use whenever the user wants to design fact tables, dimensions, a star schema, or a bus matrix — declaring grain, choosing SCD types, identifying conformed dimensions and measures (additivity) — by grilling one step at a time. Also invoke for refining an existing DimML, or when the user says "ディメンショナル・モデリング", "ディメンションモデリング", "スタースキーマ", "バスマトリクス", "ファクト表を設計したい", "グレインを決めたい", "DimML を育てたい", "Kimball で整理したい".
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).
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。