문서·Office 스킬

Validate spreadsheet sources before running Python scripts to transform data, update multiple sheets, or apply formatting. Check required data first, try backup sources when needed, and report errors clearly if processing cannot proceed.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking required columns before processing Excel files
• Transforming data and saving a new workbook
• Updating formatting across multiple sheets

Update or create Excel workbooks with checks against the requested structure. Identify the correct file before editing, then reread the saved workbook to verify sheet names, populated columns, row counts, and selected sample counts.

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• Identify the correct workbook among similarly named files
• Verify required sheets and columns after editing
• Check selected sample counts and required selection criteria

Audit an Excel workbook before editing, then verify the saved file with Python and openpyxl. Each requested requirement receives an explicit status, so completion depends on checks of the actual file.

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• Verify exact sheet names and row counts
• Check sample size and category coverage
• Confirm required source sheets remain after editing

Process complex Excel files by running Python scripts directly through run_shell. Use pandas for data transformations and openpyxl for workbook editing, including multiple sheets, formulas, and formatting, with explicit saving and error reporting.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Processing multiple Excel sheets in one script
• Calculating new columns from spreadsheet data
• Formatting report headers and cells

Create or edit Excel workbooks with checks for sheet names, row counts, formulas, and merged cells. Reopen the saved file and verify each requirement, recording explicit results rather than relying on a completion summary.

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• Create an Excel workbook from a detailed specification
• Verify row counts and formulas after editing
• Identify the correct workbook among similar files

Process Excel workbooks and generate PDF reports by running Python scripts directly. Covers multiple sheets, data transformations, formatting, and error handling, with scripts saved as files for complex tasks.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Transform data across multiple Excel sheets
• Apply consistent formatting to spreadsheet reports
• Generate PDF reports from spreadsheet data

Keep report writing focused on the original request when information retrieval fails. This skill guides agents to use existing knowledge, disclose missing information, create a structured document with write_file, and verify that the file exists.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Drafting a report when web search fails
• Continuing document work after repeated tool errors
• Documenting gaps in available source information

Process Excel workbooks and generate PDF or Word documents by running Python scripts directly through run_shell. The skill covers multi-sheet edits, formatting, data transformations, document layout, and error handling for complex tasks that can exceed agent step limits.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Transform data across multiple Excel sheets
• Apply spreadsheet formulas and formatting
• Generate PDF checklists and reports with tables

Create and edit Excel workbooks by running a complete Python script through the shell. Covers multiple sheets, data entry, formatting, formulas, and saving files when other file-reading or code-execution tools fail.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Create an Excel report with multiple sheets
• Apply data and formatting in one script
• Update cells in an existing XLSX file

Extract data from supplied spreadsheets and documents, check for missing or truncated content, and try alternative reading methods when needed. Results identify source files and clearly separate extracted facts from external information or estimates.

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• Creating reports from attached spreadsheets
• Recovering pricing tables from incomplete Word extraction
• Re-reading missing sections of a PDF

Extract text from PDFs when read_file fails or returns unreadable data. Use dedicated command-line tools or Python libraries to retrieve text and tables, preserve spacing where possible, inspect document properties, and validate the extracted content.

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• Extract text when PDF reading fails
• Retrieve text while preserving layout spacing
• Extract tables as structured data

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

Create PowerPoint presentations with specified slide content and structure. If generation through shell_agent fails, the workflow switches to Python, captures error details, locates the output, and checks the file format, size, and slide count.

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• Create presentations with specified slide counts and topics
• Retry failed PowerPoint generation using Python
• Locate generated files and verify them before delivery

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

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

Inspect PowerPoint files when read_file returns errors or incomplete content. Using python-pptx, a Python library for presentations, the skill extracts slide counts, titles, and text to check whether the deck meets expected structural requirements.

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• Check slide counts in generated presentations
• Compare slide titles with required topics
• Inspect slide structure and text before delivery

Check generated PDFs with Python and PyPDF2 before delivery. Verify expected page counts, detect unreadable or zero-page files, and collect results across multiple documents, with optional file size checks for unusually small outputs.

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• Checking PDFs against required page counts
• Detecting unreadable or zero-page PDFs
• Verifying several generated PDFs together

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 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 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

Provides fallback methods for extracting PDF text when the usual file reader fails or returns incomplete content. Uses command-line tools or Python libraries to retrieve text, preserve spacing, inspect metadata, and extract tables.

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• Recovering PDF text after file reading fails
• Extracting text while preserving layout spacing
• Extracting tables from PDFs

Troubleshoot CSV and XLSX processing when execute_code_sandbox fails. The workflow locates input files, saves processing code as a Python script, captures execution errors, checks dependencies and file access, and confirms output exists before reading it.

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• Recovering spreadsheet processing after sandbox errors
• Locating CSV and XLSX input files
• Diagnosing dependency, path, and encoding errors

Check PDF page counts, document details, and required text using command-line tools. This skill provides a verification workflow for environments without Python PDF libraries, including text extraction from selected pages and searches for expected sections.

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• Checking whether a PDF has the expected number of pages
• Searching for required sections or terms in a PDF
• Extracting text from a selected page range

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.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

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