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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Extract text from downloaded PDFs by checking for invalid files, trying three extraction tools in sequence, and validating the results. This workflow helps identify download errors, empty output, and encoding problems during document retrieval.
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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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
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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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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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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
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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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.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Investigate unclear errors in Python PDF generation by displaying output immediately and inspecting error details. Use the resulting traceback, a record of where execution failed, to identify missing dependencies, font problems, or invalid file paths.
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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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Create spreadsheets, diagrams, and PDF reports in a staged workflow. Allocate execution attempts across deliverables, check generated files, and use simpler methods or alternative formats when tool errors or limited remaining attempts interrupt progress.
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Inspect unfamiliar Excel workbooks before building extraction scripts. Map sheets, headers, columns, and row patterns, then use those findings to distinguish actual records from summaries and blank rows when extracting data.
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Debug repeated execution failures by saving Python code to a script file and running it through run_shell. Keep the script available for inspection, review intermediate output and errors, and edit it for another run.
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Continue file reading and data processing when execute_code_sandbox or read_file fails. This skill runs multiline Python through run_shell, with examples for text, JSON, spreadsheets, PDF and Word documents, plus basic summaries and grouped calculations.
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Run Python through a saved script when execute_code_sandbox or shell_agent repeatedly fails. The workflow writes code to a file, executes it through run_shell, and checks errors and expected outputs such as spreadsheets or documents.
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Recover from failed file and directory operations by switching to run_shell, a shell command tool. Create nested folders, write files, and verify each result before continuing with tasks that depend on those files.
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Create and check files through shell scripts when code execution tools repeatedly fail. The workflow verifies working directories, handles script quoting and permissions, and inspects outputs such as PDFs and DOCX documents for file size, type, and structure.
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Continue Python tasks when the e2b sandbox, an isolated execution environment, is unavailable. Guides switching from execute_code_sandbox to run_shell, preparing dependencies, checking execution results, and saving intermediate data between calls.
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Handle merged cells before filling Excel templates with openpyxl, a Python library for spreadsheets. This skill shows how to inspect merged ranges, unmerge the required areas, write values, and save the workbook without merged-cell write errors.
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Create Excel files with openpyxl, a Python spreadsheet library, by switching to shell execution when sandbox tools fail. Examples cover cell styling, formulas, merged cells, multiple sheets, error reporting, and checking that the output file exists.
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Recover from failed Excel creation or editing by switching from execute_code_sandbox to shell_agent. It guides clear task descriptions so the agent can install missing libraries, run code, retry errors, and confirm file creation.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.