'extraction' 검색 결과

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

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 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

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

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 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

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 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

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 plain text from Word DOCX files using shell commands first, then switch to Python's built-in ZIP reader if extraction fails or returns nothing. Supports text output without requiring the external python-docx package.

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• Extracting Word text without python-docx
• Retrying DOCX extraction after empty shell output
• Saving DOCX text to a separate file

Organize existing code components into business areas to prepare for service separation. Produce domain maps, component assignment tables, and refactoring plans that align namespaces, the naming structure used to organize code, with business responsibilities.

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• Grouping existing components by business responsibility
• Planning service extraction from an existing application
• Aligning code namespaces with business areas

Analyze a monolithic codebase before splitting it into modules or services. The skill inventories components, examines duplication, hierarchy, and dependencies, then proposes groupings aligned with business domains, with optional checks against business terminology and boundaries.

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• Assessing component sizes before splitting a monolith
• Finding duplicated business logic across modules
• Reviewing module hierarchy and dependencies

Check how an agent handles file saves, uploads and archive extraction. Test whether user supplied paths can escape the intended directory, then report confirmed unsafe handling with response evidence and suggested safeguards.

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• Checking whether file saves stay within the intended directory
• Reviewing how uploaded filenames are handled
• Testing archive extraction paths

Extract timestamped text from a YouTube video's transcript panel and turn it into summaries, chapter outlines, X threads, blog articles, or notable quotes. Use existing captions to create readable material from video content.

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• Reviewing a video's main points through a summary
• Creating timestamped chapter outlines
• Turning video content into a blog article or X thread

Collect posts from X search, profile, individual post, and list URLs. Organize text, authors, engagement counts, media, hashtags, and mentions into a consistent dataset, with support for collecting additional pages.

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• Collecting posts from a mixed list of X URLs
• Monitoring posts from selected profiles and lists
• Gathering replies to a specific post

Collect product names, prices, images, ratings, and links from e-commerce listings or keyword searches. Apply filters such as price range and brand, and gather structured product records across multiple pages.

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• Compare products within a price range
• Collect products from a category
• Find products by brand and rating

Search Google Maps by business type and location, collect business details, then visit listed websites to find public emails, phone numbers, and social profiles. Merge the results into a contact dataset for local business research and prospect lists.

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• Build a contact list for businesses in a specific area
• Find public business emails on listed websites
• Collect local competitors' details and opening hours

Collect product details from public shopping pages using a URL, keyword, or product identifier. Extract prices, stock status, images, ratings, and variants into structured data for product research, comparisons, and catalog collection.

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• Comparing product prices and stock across shopping sites
• Finding product details by ASIN or barcode
• Collecting images and descriptions for a product catalog

Automates website navigation, form entry, and information extraction through browser commands. Helps test web applications, reuse saved login state, and capture screenshots, PDFs, or recordings of browser workflows for inspection and documentation.

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• Filling and submitting web forms
• Testing web application behavior
• Extracting text and links from pages

Assess iOS apps from IPA acquisition through file inspection and runtime testing. The skill helps uncover embedded credentials, insecure network settings, and app link handling issues using tools such as Frida, objection, and binary analysis utilities.

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• Assessing an iOS app in a bug bounty program
• Finding credentials and API endpoints inside an IPA
• Reviewing ATS settings and inspecting app traffic

Universal Meta-Analysis Codebook v2.2 - AI-Human collaboration for meta-analysis data extraction. 4-layer design: Identifiers, Statistics, AI Provenance, Human Verification. Integrates with C5/C6/C7 agents and Category I systematic review pipeline. Triggers: meta-analysis, codebook, data extraction, Hedges g, effect size

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Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.

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Extract structured knowledge from source material. Comprehensive extraction is the default — every insight that serves the domain gets extracted. For domain-relevant sources, skip rate must be below 10%. Zero extraction from a domain-relevant source is a BUG. Triggers on "/reduce", "/reduce [file]", "extract insights", "mine this", "process this".

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Azure AI Content Understanding SDK for Python. Use for multimodal content extraction from documents, images, audio, and video. Triggers: "azure-ai-contentunderstanding", "ContentUnderstandingClient", "multimodal analysis", "document extraction", "video analysis", "audio transcription".

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