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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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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Locate missing files and verify their full paths before processing them. This workflow checks directory contents, searches by filename, and inspects permissions, size, and modification time to help resolve FileNotFoundError, an error indicating a file could not be found.
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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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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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Find generated files that are missing from their expected locations in isolated or temporary execution environments. Search confirmed directories, identify the right file, copy it to the intended destination, and verify that it is readable and nonempty.
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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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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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Check which H.264 encoders, the components that compress video, are available in FFmpeg before building a conversion script. Choose an encoding approach and test a small sample before processing long videos or batches.
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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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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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Prepare Markdown for pandoc PDF conversion by replacing problematic Unicode symbols with ASCII alternatives. The skill covers reusable substitution scripts, broader character conversion, and alternative PDF engines for documents that need to retain Unicode.
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Check which H.264 video encoders are available before writing FFmpeg scripts. Choose an available encoder or copy an existing video stream when appropriate, then test a short clip to catch compatibility problems before processing the full file.
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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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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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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.
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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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Turn unstructured clinical encounter summaries into SOAP notes, a four-part format for medical records. Organize symptoms and findings, include diagnoses with ICD-10 classification codes, and document treatment steps, follow-up timing, and reasons to return for care.
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Download PDFs, check that the files contain valid content, and try several text extraction tools in sequence. The workflow helps detect downloaded error pages, insufficient text, and extraction failures while recording diagnostic details.
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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.
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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.
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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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