「csv」の検索結果

The exact column header names required by the TRES Finance bulk transaction CSV upload. Use whenever building, fixing, or validating the header row of a TRES manual transaction or sub-transaction upload CSV — especially after an upload fails with "Missing required column(s): ...". Trigger phrases include: 'fix my CSV headers', 'bulk transaction upload failed', 'missing required columns', 'validate TRES upload CSV', 'transaction CSV template headers'. This skill is ONLY about the header naming convention; it does not cover row values or upload workflow. Do NOT trigger for contacts import CSV (use tres-import-contacts), wallet upload CSV (use tres-wallets-upload), or general CSV parsing unrelated to bulk TX upload headers.

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。

CSV格式化器。用于加载和格式化csv类型的文件。 本SKILL使用依赖data_juicer，请在调用前安装好python环境并安装data_juicer，你可用以下指令进行安装： pip install py-data-juicer 当用户提到CSV格式化、CSV数据加载、读取CSV文件、CSV转JSONL等需求时使用此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。

CSVファイルの行数・列数の取得、データ型推定、欠損値検出、数値列の統計情報を出力するスキル。 「CSVを分析して」「CSVの中身を確認」「データの概要を見せて」等のリクエストで発動。

Parse and generate CSV files with the csv package — stream large files, handle custom delimiters, transform records, validate data, and generate CSV output from objects. Use when tasks involve data import/export, ETL pipelines, processing uploaded CSV files, or generating downloadable reports.

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 DuckDB from MATLAB via Database Toolbox (R2026a+) as a non-math operations engine on large tabular files (CSV/Parquet/JSON) and as a zero-config embedded database. Use when connecting to DuckDB, querying CSV, Parquet, and JSON files directly with SQL, reducing or profiling large data before MATLAB analysis, creating portable development databases, or installing DuckDB extensions. Triggers on: DuckDB, duckdb(), large CSV/Parquet/JSON, file too large for readtable, filter/aggregate at source, deduplicate, reduce before analysis, profile large file, persistent file import, analytical engine, SQL on CSV, SQL on Parquet, SQL on JSON, query CSV with SQL, query Parquet with SQL, run SQL on files, SQL queries on files, query files directly, SQL without database, in-process SQL.

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。

Read, transform, analyze, and generate Excel and CSV files. Use when a user asks to open a spreadsheet, process Excel data, merge CSVs, create pivot tables, clean up data, convert between Excel and CSV, add formulas, filter rows, or generate reports from tabular data. Handles .xlsx, .xls, and .csv.

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 structured CSV security audit reports from vulnerability data with proper filtering and formatting. This skill covers CSV schema design for security reports, using Python csv.DictWriter, severity-based filtering, and field mapping from JSON to tabular format.

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。

讀取CSV文件，僅使用csv庫且不使用SequenceMatcher，計算第一列目標基因型與後續每一列基因型的相似度。

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 should be used when the user wants to record bookkeeping entries (仕訳), import transaction data from CSV files, receipts, or invoices, or manage their general ledger. Trigger phrases include: "仕訳を入力", "仕訳登録", "CSVを取り込む", "レシートを読み込む", "請求書を取り込む", "帳簿を付ける", "経費を記録", "売上を記録", "仕訳を修正", "仕訳を検索", "仕訳を削除", "取引を登録", "帳簿の初期化".

DuckDBを使用した大規模データ分析の専門スキル。DuckDBのアーキテクチャ、SQL構文、パフォーマンス最適化、各種ファイル形式（CSV、Parquet、JSON等）の効率的な読み込み・書き出しを熟知。メモリ効率の良い分析、複雑なクエリの最適化、データパイプライン構築を支援。Use when analyzing large datasets, querying CSV/Parquet/JSON files directly, building data pipelines, or optimizing analytical queries with DuckDB.

Search academic references for a manuscript and export them to a verified refs CSV, then optionally hand off to cec-sheet. Uses Codex CLI as the search driver, but Codex calls a bundled deterministic PubMed tool (scripts/pubmed_search.py) instead of writing its own E-utilities code — bibliography is fetched live from PubMed so PMIDs are never fabricated. Triggers: "論文検索", "文献検索", "文脈検索", "コンテキスト検索", "原稿の引用を探して", "refs.csv", "codex-refs", "/codex-refs".

Use this skill to build a multi-element Excel dashboard — Dashboard sheet on open, multiple formula-driven KPI cards, multiple charts, sparklines, and conditional formatting — from CSV or tabular input. Trigger on: 'dashboard', 'KPI dashboard', 'analytics dashboard', 'executive dashboard', 'metrics dashboard', 'CSV to dashboard', 'data visualization'. Output is a single .xlsx. Scene-layer on officecli-xlsx: inherits every xlsx hard rule. DO NOT invoke for: a single budget tracker / one-sheet CSV-with-formatting (use xlsx), a 3-statement / DCF / LBO financial model (use financial-model), a weekly report with at most 1 chart and fewer than 10 rows (use xlsx).

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 laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production 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。

Universal LaTeX document skill: create, compile, and convert any document to professional PDF with PNG previews. Supports resumes, reports, cover letters, invoices, academic papers, theses/dissertations, academic CVs, presentations (Beamer), scientific posters, formal letters, exams/quizzes, books, cheat sheets, reference cards, exam formula sheets, fillable PDF forms (hyperref form fields), conditional content (etoolbox toggles), mail merge from CSV/JSON (Jinja2 templates), version diffing (latexdiff), charts (pgfplots + matplotlib), tables (booktabs + CSV import), images (TikZ), Mermaid diagrams, AI-generated images, watermarks, landscape pages, bibliography/citations (BibTeX/biblatex), multi-language/CJK (auto XeLaTeX), algorithms/pseudocode, colored boxes (tcolorbox), SI units (siunitx), Pandoc format conversion (Markdown/DOCX/HTML ↔ LaTeX), and PDF-to-LaTeX conversion of handwritten or printed documents (math, business, legal, general). Compile script supports pdflatex, xelatex, lualatex with auto-detection, latexmk backend, texfot log filtering, PDF/A output, and verbosity control (--verbose/--quiet). Empirically optimized scaling: single agent 1-10 pages, split 11-20, batch-7 pipeline 21+. Use when user asks to: (1) create a resume/CV/cover letter, (2) write a LaTeX document, (3) create PDF with tables/charts/images, (4) compile a .tex file, (5) make a report/invoice/presentation, (6) anything involving LaTeX or pdflatex, (7) convert/OCR a PDF to LaTeX, (8) convert handwritten notes, (9) create charts/graphs/diagrams, (10) create slides, (11) write a thesis or dissertation, (12) create an academic CV, (13) create a poster, (14) create an exam/quiz, (15) create a book, (16) convert between document formats (Markdown, DOCX, HTML to/from LaTeX), (17) generate Mermaid diagrams for LaTeX, (18) create a formal business letter, (19) create a cheat sheet or reference card, (20) create an exam formula sheet or crib sheet, (21) condense lecture notes/PDFs into a cheat sheet, (22) create a fillable PDF form with text fields/checkboxes/dropdowns, (23) create a document with conditional content/toggles (show/hide sections), (24) generate batch/mail-merge documents from CSV/JSON data, (25) create a version diff PDF (latexdiff) highlighting changes between documents, (26) create a homework or assignment submission with problems and solutions, (27) create a lab report with data tables, graphs, and error analysis, (28) encrypt or password-protect a PDF, (29) merge multiple PDFs into one, (30) optimize/compress a PDF for web or email, (31) lint or check a LaTeX document for common issues, (32) count words in a LaTeX document, (33) analyze document statistics (figures, tables, citations), (34) fetch BibTeX from a DOI, (35) convert a Graphviz .dot file to PDF/PNG, (36) convert a PlantUML .puml file to PDF/PNG, (37) create a one-pager/fact sheet/executive summary, (38) create a datasheet or product specification sheet, (39) extract pages from a PDF (page ranges, odd/even), (40) check LaTeX package availability before compiling, (41) analyze citations and cross-reference with .bib files, (42) debug LaTeX compilation errors, (43) make a document accessible (PDF/A, tagged PDF), (44) create lecture notes or course handouts, (45) fill an existing PDF form (fillable fields or non-fillable with annotations), (46) extract text or tables from a PDF (pdfplumber, pypdf), (47) OCR a scanned PDF to text (pytesseract), (48) create a PDF programmatically with reportlab (Canvas, Platypus), (49) rotate or crop PDF pages (pypdf), (50) add a watermark to an existing PDF, (51) extract metadata from a PDF (title, author, subject).

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 to build a multi-element Excel dashboard — Dashboard sheet on open, multiple formula-driven KPI cards, multiple charts, sparklines, and conditional formatting — from CSV or tabular input. Trigger on: 'dashboard', 'KPI dashboard', 'analytics dashboard', 'executive dashboard', 'metrics dashboard', 'CSV to dashboard', 'data visualization'. Output is a single .xlsx. Scene-layer on officecli-xlsx: inherits every xlsx hard rule. DO NOT invoke for: a single budget tracker / one-sheet CSV-with-formatting (use xlsx), a 3-statement / DCF / LBO financial model (use financial-model), a weekly report with ≤ 1 chart and < 10 rows (use xlsx).

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 reading sensor data from CSV files, writing simulation results to CSV, processing time-series data with pandas, or handling missing values in datasets.

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 to build a multi-element Excel dashboard — Dashboard sheet on open, multiple formula-driven KPI cards, multiple charts, sparklines, and conditional formatting — from CSV or tabular input. Trigger on: 'dashboard', 'KPI dashboard', 'analytics dashboard', 'executive dashboard', 'metrics dashboard', 'CSV to dashboard', 'data visualization'. Output is a single .xlsx. Scene-layer on officecli-xlsx: inherits every xlsx hard rule. DO NOT invoke for: a single budget tracker / one-sheet CSV-with-formatting (use xlsx), a 3-statement / DCF / LBO financial model (use financial-model), a weekly report with ≤ 1 chart and < 10 rows (use xlsx).

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 existing brand DNA, keywords.csv, and prompts.csv, then produces a plan.csv — a strictly-schema'd content architecture telling the next pipeline step which pages to create, for which keyword/prompt clusters, and in what build order.

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。

omicsViewer visualizes ExpressionSet (or SummarizedExperiment) in an interactive way. The omicsViewer has a separate back- and front-end. In the back-end, users need to prepare an ExpressionSet that contains all the necessary information for the downstream data interpretation. Some extra requirements on the headers of phenotype data or feature data are imposed so that the provided information can be clearly recognized by the front-end, at the same time, keep a minimum modification on the existin

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。

Universal LaTeX document skill: create, compile, and convert any document to professional PDF with PNG previews. Supports resumes, reports, cover letters, invoices, academic papers, theses/dissertations, academic CVs, presentations (Beamer), scientific posters, formal letters, exams/quizzes, books, cheat sheets, reference cards, exam formula sheets, fillable PDF forms (hyperref form fields), conditional content (etoolbox toggles), mail merge from CSV/JSON (Jinja2 templates), version diffing (latexdiff), charts (pgfplots + matplotlib), tables (booktabs + CSV import), images (TikZ), Mermaid diagrams, AI-generated images, watermarks, landscape pages, bibliography/citations (BibTeX/biblatex), multi-language/CJK (auto XeLaTeX), algorithms/pseudocode, colored boxes (tcolorbox), SI units (siunitx), Pandoc format conversion (Markdown/DOCX/HTML ↔ LaTeX), and PDF-to-LaTeX conversion of handwritten or printed documents (math, business, legal, general). Compile script supports pdflatex, xelatex, lualatex with auto-detection, latexmk backend, texfot log filtering, PDF/A output, and verbosity control (--verbose/--quiet). Empirically optimized scaling: single agent 1-10 pages, split 11-20, batch-7 pipeline 21+. Use when user asks to: (1) create a resume/CV/cover letter, (2) write a LaTeX document, (3) create PDF with tables/charts/images, (4) compile a .tex file, (5) make a report/invoice/presentation, (6) anything involving LaTeX or pdflatex, (7) convert/OCR a PDF to LaTeX, (8) convert handwritten notes, (9) create charts/graphs/diagrams, (10) create slides, (11) write a thesis or dissertation, (12) create an academic CV, (13) create a poster, (14) create an exam/quiz, (15) create a book, (16) convert between document formats (Markdown, DOCX, HTML to/from LaTeX), (17) generate Mermaid diagrams for LaTeX, (18) create a formal business letter, (19) create a cheat sheet or reference card, (20) create an exam formula sheet or crib sheet, (21) condense lecture notes/PDFs into a cheat sheet, (22) create a fillable PDF form with text fields/checkboxes/dropdowns, (23) create a document with conditional content/toggles (show/hide sections), (24) generate batch/mail-merge documents from CSV/JSON data, (25) create a version diff PDF (latexdiff) highlighting changes between documents, (26) create a homework or assignment submission with problems and solutions, (27) create a lab report with data tables, graphs, and error analysis, (28) encrypt or password-protect a PDF, (29) merge multiple PDFs into one, (30) optimize/compress a PDF for web or email, (31) lint or check a LaTeX document for common issues, (32) count words in a LaTeX document, (33) analyze document statistics (figures, tables, citations), (34) fetch BibTeX from a DOI, (35) convert a Graphviz .dot file to PDF/PNG, (36) convert a PlantUML .puml file to PDF/PNG, (37) create a one-pager/fact sheet/executive summary, (38) create a datasheet or product specification sheet, (39) extract pages from a PDF (page ranges, odd/even), (40) check LaTeX package availability before compiling, (41) analyze citations and cross-reference with .bib files, (42) debug LaTeX compilation errors, (43) make a document accessible (PDF/A, tagged PDF), (44) create lecture notes or course handouts, (45) fill an existing PDF form (fillable fields or non-fillable with annotations), (46) extract text or tables from a PDF (pdfplumber, pypdf), (47) OCR a scanned PDF to text (pytesseract), (48) create a PDF programmatically with reportlab (Canvas, Platypus), (49) rotate or crop PDF pages (pypdf), (50) add a watermark to an existing PDF, (51) extract metadata from a PDF (title, author, subject).

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 laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full ASM JSON, flattened CSV for easy import, and exportable Python code for data engineers. Common triggers include converting instrument files, standardizing lab data, preparing data for upload to LIMS/ELN systems, or generating parser code for production 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。

用于读取CSV文件数据，将大量数据点的横坐标映射到指定线性范围（如0-60）进行绘图，并自动标记波峰位置。

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。

编写Matlab脚本，从CSV文件中提取指定列（A、B、C列），保存为新文件，并计算各列最大值和最小值，最后将统计结果输出到Excel表格的新Sheet中。

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 CSV files, generates summary stats, and plots quick visualizations using Python and pandas.

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。