문서·Office 스킬

Check generated PDFs with PyPDF2 before reporting completion. A Python script verifies that each file can be opened and has the expected page count, helping identify outputs that need regeneration.

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• Checking a generated one-page summary
• Verifying page counts across multiple PDFs
• Checking PDFs before reporting completion

Extract text from existing PDFs and assemble it into a new PDF report using command-line tools. Choose an available conversion method, combine source content, and check the resulting file’s pages and included text.

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• Combine content from several PDFs into one report
• Extract text from selected PDF pages
• Generate PDF reports without Python PDF libraries

Recover readable text from PDFs when read_file or Python extraction fails. Use pdftotext, a command-line text extractor, with options to preserve layout, specify character encoding, or save extracted content to a file.

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• Recovering text after PDF reading fails
• Extracting text while preserving page layout
• Saving text from large PDFs to a file

Create PowerPoint presentations with shell_agent, then switch to Python and python-pptx if generation fails. The workflow captures error details, locates output files, and checks that the presentation opens and contains the expected slides.

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• Creating slides from a specified outline
• Recovering from presentation generation errors
• Locating PowerPoint files saved in unexpected folders

Extract PDF text when the usual file reader returns errors or unusable output. Choose command-line tools or Python libraries for plain text, metadata, tables, and complex layouts, with checks for scanned or copy-protected documents.

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• Recovering text when PDF reading fails
• Extracting tables and structured data from PDFs
• Inspecting PDF metadata

Create PowerPoint presentations through shell_agent with specified slide counts and content, then locate the resulting files in nested workspace folders. Copy the presentation to the working directory and check that it exists and is not empty.

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• Creating slides with specified content and structure
• Generating presentations when document tools fail
• Locating presentations in nested folders

Check generated PDFs with PyPDF2, a Python library for reading PDF files. Verify that files exist, contain data, open successfully, and match expected page counts, then use failures to guide regeneration and another verification pass.

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• Checking PDFs after generation
• Verifying exact page count requirements
• Validating multiple related PDF outputs

Create PDF reports from existing PDFs using command-line tools. The workflow checks source files, extracts text, organizes report sections, and generates or merges PDFs, with alternative output methods depending on the tools available.

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• Building a report from several source PDFs
• Checking PDF page counts and required terms
• Extracting text from selected PDF pages

Generate PDF checklists, reports, and scorecards with Python. Organizes content into sections and tables, supports scoring criteria and status colors, and includes steps to locate and verify the generated files.

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• Creating PDF checklists with status and notes columns
• Preparing scorecards with weights and scores
• Turning findings into a report with multiple sections

Retrieve PDFs from web sources and extract their text through an ordered sequence: direct reading, pdftotext, then PyMuPDF. Includes file validation, extraction checks, and guidance for documenting inaccessible sources and distinguishing supplementary content.

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• Retrieving and reading PDFs from government websites
• Extracting text from technical manuals
• Handling PDF extraction failures in automated workflows

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

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

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

Generate PDF checklists, reports, and assessments with sections, tables, and scoring criteria using Python. Choose a suitable library, save the document for download, and check the output, with shell execution as an alternative when the sandbox fails.

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• Turn a checklist into a PDF with sections and tables
• Create an assessment report with criteria and scores
• Produce PDF reports containing charts

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

Download PDFs from web URLs or process local files, verify their format, and extract text with pdftotext. If extraction fails or looks poor, try PyMuPDF, check the results, and document any remaining source limitations.

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• Download a PDF from a web URL and extract its text
• Convert a local PDF into a text file
• Try another method after failed or garbled 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

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 local or downloaded PDFs using a sequence of tools. Try file reading, then pdftotext before a Python fallback, check readability, and document failures while clearly separating extracted content from knowledge-based additions.

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• Extract text from a local PDF
• Download a PDF from a URL and extract its text
• Switch tools when PDF reading fails

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

Generate PDF documents when sandbox execution fails with unclear errors. Check available Python libraries, switch to direct shell execution, and verify the resulting file while collecting error details to help diagnose problems.

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• Generating a PDF after sandbox execution fails
• Checking PDF libraries and choosing an alternative
• Verifying generated PDFs and investigating errors

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

Download PDFs or process local files, extract their text, and turn processed data into structured PDF reports with ReportLab. Includes alternative extraction methods and text output when PDF generation fails.

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• Extracting text from technical manuals
• Processing PDFs downloaded from websites
• Creating PDF reports with sections and tables

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