문서·Office 스킬

Extract readable text from PDFs with pdftotext when read_file returns garbled or binary content. Choose page ranges, preserve text layout where needed, and send the extracted content to standard output or a text file for further processing.

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• Recovering text when read_file returns garbled content
• Preparing PDF text for search or processing
• Extracting text from selected pages

Create a related Excel workbook, PNG diagram, and PDF report in one workflow. It allocates execution attempts across stages, checks output files, and provides retries or simpler versions when generation encounters errors.

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• Preparing a comparison table, diagram, and report together
• Creating a PDF that references spreadsheet findings and diagrams
• Allocating execution attempts across several output formats

Resolve Unicode character errors when converting Markdown to PDF with pandoc. Follow a workflow to replace troublesome symbols with ASCII equivalents, regenerate and check the PDF, or consider another PDF engine when preserving characters matters.

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• Resolve Unicode errors during Markdown-to-PDF conversion
• Replace troublesome symbols in a document
• Consider PDF engines that preserve Unicode characters

Diagnose PDF conversion failures in pandoc by checking installed conversion engines, capturing full error logs, and investigating missing fonts or packages. Follow a structured sequence of retries and fallback methods to find a working conversion route.

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• Investigate an unknown error during PDF conversion
• Check which PDF engines are installed
• Find missing fonts or LaTeX packages

Build Excel spreadsheets with merged titles and headers using openpyxl, a Python library for spreadsheet files. Follow a sequence for entering values, merging cells, and applying formatting, with guidance for updating existing merged ranges and checking saved results.

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• Creating report titles that span multiple columns
• Formatting section headers and grouped labels
• Updating values in existing merged ranges

Diagnose failed pandoc PDF conversions by checking installed tools, capturing error logs, and trying alternative PDF engines. The workflow helps identify missing fonts or packages and suggests ways to simplify documents when conversion still fails.

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• Investigating unknown errors during PDF conversion
• Finding missing fonts or LaTeX packages
• Choosing a PDF engine for a document

Recover PDF or DOCX generation when execute_code_sandbox fails with unclear errors. Use run_shell to execute Python directly, check required libraries, report specific failures, and verify that the output file was created.

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• Retry PDF generation after an unclear sandbox error
• Generate DOCX files by running Python through the shell
• Check and install missing document libraries

Troubleshoot PDF creation by trying pandoc, then reportlab, then fpdf2. Check tool availability, install missing Python libraries as needed, run generation with an explicit working directory, and verify that the output file exists.

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• Converting Markdown or HTML to PDF
• Trying another tool after PDF generation fails
• Checking PDF tools and installing missing libraries

Troubleshoot unclear errors when converting documents to PDF with pandoc. Check installation, capture error logs, identify missing fonts or packages, and try alternative PDF engines, the tools that render the final document.

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• Investigating an unknown error during PDF conversion
• Checking missing fonts and LaTeX packages
• Retrying conversion with a different PDF engine

Extract text from difficult PDFs by trying several libraries and command-line tools in sequence, then using OCR, which reads text from images. Record failed attempts and check that extracted content meets the task requirements.

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• Extracting text from scanned PDFs
• Retrying extraction when PDF text is garbled
• Reading PDFs with tables or complex layouts

Build complex Excel files in four stages: extraction, preparation, calculation, and formatted output. Intermediate CSV files let agents and reviewers inspect data, validate forecasts, locate errors, and rerun individual stages without repeating the entire workflow.

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• Combining multiple data sources into an Excel file
• Checking intermediate values in sales forecasts
• Locating errors in data preparation or calculations

Recover from Pandoc PDF generation failures by checking installed PDF engines and retrying alternatives. The guide matches engines to Unicode text, simple Latin documents, or HTML-based layouts, and includes an automated fallback script.

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• Retrying failed Pandoc PDF conversions
• Choosing an engine for Japanese or other Unicode text
• Automating PDF engine fallback in document pipelines

Continue Excel file creation and editing when execute_code_sandbox repeatedly fails with openpyxl errors. Use run_shell to run Python directly, then check that the workbook was saved with the expected sheets and content.

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• Continuing Excel creation after sandbox errors
• Editing existing workbooks and adjusting column widths
• Checking saved workbook sheets and content

Extract readable text from PDFs when normal file reading returns garbled or unusable content. The workflow switches between extraction tools, checks the results, and includes optical character recognition for scanned pages when needed.

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• Recovering readable text from garbled PDF output
• Preparing PDF text for data processing
• Extracting text from scanned PDFs

Extract PDF text using a sequence of tools when one method fails. Validate downloaded files, check whether the extracted text is substantial, record the successful method, and investigate alternative sources if extraction remains unsuccessful.

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• Extracting text from regulatory documents and handbooks
• Checking whether a PDF download returned an error page
• Trying another tool after empty or garbled text extraction

Recover document and PDF generation tasks when sandbox errors provide little detail. Checks Python libraries, runs generation through the shell, captures errors, and verifies output files, with alternative PDF tools and text output as fallback options.

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• Recovering PDF generation after unclear sandbox errors
• Checking required PDF libraries before generation
• Capturing detailed document generation errors

Create PDF checklists, reports, and scorecards with Python in a sandbox, an isolated code execution environment. The workflow covers choosing a library, arranging headings and tables, generating the document, and checking that the output file exists.

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• Creating a PDF checklist for distribution
• Organizing assessment results into a scorecard
• Producing reports with headings and tables

Extract readable PDF text when read_file returns binary or image data. Check the filetype parameter, run pdftotext, a command-line text extractor, and inspect output and errors, with temporary file output as an alternative.

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• Extracting PDF text after binary data is returned
• Checking read_file parameter names during troubleshooting
• Saving extracted text when direct output has issues

Check generated PDFs against a page limit or target count, then adjust layout and regenerate as needed. Provides a repeatable workflow for tuning margins, images, tables, and text while respecting readability limits.

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• Keep a report within a page limit
• Fit a map PDF onto one page
• Correct overflow caused by images or tables

Extract text from PDFs when the first reading attempt fails or produces poor results. The skill tries command-line tools, Python libraries, then OCR, which recognizes text in images, while checking output quality and recording successful methods.

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• Retrying PDF extraction after errors or empty output
• Reading scanned documents with OCR
• Extracting text and tables from structured PDFs

Extract PDF text when read_file returns unreadable binary content or little usable output. Try pdftotext with layout preservation, then use pdfplumber as an alternative when the command is unavailable or produces insufficient text.

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• Extracting text after read_file returns binary content
• Retrying PDF extraction with empty or very short output
• Extracting text while preserving the PDF layout

Organizes creation of a spreadsheet, a diagram, and a summary PDF as a related report package. Allocates attempts across components, checks generated files, and provides fallback methods when a tool or output fails.

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• Preparing a spreadsheet, diagram, and PDF report together
• Documenting equipment choices, layouts, and costs
• Dividing generation attempts across multiple deliverables

Extract text from local PDF files with pdftotext or PyMuPDF, a Python library for reading PDFs. Convert individual files or batches into text files that an agent can read for summarization, analysis, or further data extraction.

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• Converting local PDFs to text for summarization
• Extracting text from multiple PDFs in one batch
• Reading PDFs that appear as binary data in read_file

Extract text from PDFs by checking each tool’s output and switching methods when needed. Guides agents from file reading to pdftotext and PyMuPDF, then checks readability, missing sections, and records extraction failures.

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• Extract text from local or downloaded PDFs
• Switch tools when file reading returns binary data
• Check extracted text for readability and missing sections