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Read, extract text from, split, merge, fill, or create PDFs while preserving originals. Check page counts, extracted text, and file sizes, and flag accuracy limits when scanned pages require optical character recognition.
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Examine Outlook PST and OST archives to extract messages, headers, attachments, and recoverable deleted items. Use the extracted records to trace email routing, reconstruct communication patterns, and support incident investigations or legal evidence review.
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Add Tavily web search and URL content extraction to selected NanoClaw agent groups without an API key. Configures MCP, a protocol for connecting agent tools, checks availability, and prepares an upgrade path when the shared allowance runs out.
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Extract code and resources from installed Electron apps to inspect how they are built. Restore original files when source maps contain them, or format compressed JavaScript for easier reading. Supports app discovery on macOS and Windows.
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Read, create, and organize PDF files, including merging documents, splitting pages, extracting tables, and filling forms. It also covers password protection and OCR, which recognizes text in scanned pages for extraction or search.
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Convert an existing frontend into a Stitch design by extracting a standalone HTML file and shared design rules, then uploading both to a project so you can revise the interface in Stitch.
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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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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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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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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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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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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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Extract the full design language from any website URL. Produces 8 output files including AI-optimized markdown, visual HTML preview, Tailwind config, React theme, shadcn/ui theme, Figma variables, W3C design tokens, and CSS variables. Also runs WCAG accessibility scoring. Use when user says 'extract design', 'get design system', 'design language', 'design tokens', 'what colors/fonts does this site use', or '/extract-design'.
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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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Extract pixel-level data from an image of a chart or graph and produce a structured data table. Use when asked to extract data from a chart image, transcribe numbers from a graph, digitise a chart, or turn a screenshot of data into a table. Produces a structured table with extracted values, confidence levels, and a reconstructed chart source. Best used with Claude Opus 4.7 or newer for reliable chart data extraction.
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Crawl websites and extract content from multiple pages via the Tavily CLI. Use this skill when the user wants to crawl a site, download documentation, extract an entire docs section, bulk-extract pages, save a site as local markdown files, or says "crawl", "get all the pages", "download the docs", "extract everything under /docs", "bulk extract", or needs content from many pages on the same domain. Supports depth/breadth control, path filtering, semantic instructions, and saving each page as a local markdown file.
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Upload video/audio media to BytePlus VOD (Video on Demand) storage, returning the Vid and playback references; supports local file upload (ApplyUploadInfo + TOS + CommitUploadInfo) and URL pull upload (UploadMediaByUrl); also submits frame extraction jobs on ingested media (StartExecution / Operation.Task.Snapshot), including specified time, fixed interval, specified frame, scene-change, sprite image, and output index modes. Trigger keywords: VOD frame extraction, frame extraction, extract frames, video snapshot, thumbnail, screenshot from video, StartExecution Snapshot.
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Web search and content extraction with Tavily and Exa via inference.sh CLI. Apps: Tavily Search, Tavily Extract, Exa Search, Exa Answer, Exa Extract. Capabilities: AI-powered search, content extraction, direct answers, research. Use for: research, RAG pipelines, fact-checking, content aggregation, agents. Triggers: web search, tavily, exa, search api, content extraction, research, internet search, ai search, search assistant, web scraping, rag, perplexity alternative
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Refactoring pass — extracts repeated Tailwind class combos and markup into components, and lifts magic values into design tokens. Use when the codebase has obvious duplication, hardcoded hex values or pixel sizes, or when the user says "clean this up" / "extract components" / "tokenize styles". Invoke when the user asks for extract on their UI, or mentions 'extract' alongside design / UI / frontend work.
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Extract structured data from any document format using unified document processing. Use when a user asks to extract data from a document, parse a PDF, pull structured data from files, convert documents to JSON or CSV, extract fields from invoices or forms, or scrape data from documents.
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Parse and extract data from HTML with Cheerio. Use when a user asks to scrape static web pages, parse HTML files, extract data from HTML, build a web scraper for server-rendered pages, extract text or links from HTML documents, parse RSS/XML feeds, transform HTML content, or process HTML emails. Covers jQuery-style selectors, DOM traversal, text extraction, attribute parsing, and integration with HTTP clients for web scraping pipelines.
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Comprehensive patterns for AI-powered document understanding including PDF parsing, OCR, invoice/receipt extraction, table extraction, multimodal RAG with vision models, and structured data output. Use when "document parsing, PDF extraction, OCR, invoice processing, receipt extraction, document understanding, LlamaParse, Unstructured, vision document, table extraction, structured output from PDF, " mentioned.
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AI-powered autonomous data extraction that navigates complex sites and returns structured JSON. Use this skill when the user wants structured data from websites, needs to extract pricing tiers, product listings, directory entries, or any data as JSON with a schema. Triggers on "extract structured data", "get all the products", "pull pricing info", "extract as JSON", or when the user provides a JSON schema for website data. More powerful than simple scraping for multi-page structured extraction.
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Bulk extract content from an entire website or site section. Use this skill when the user wants to crawl a site, extract all pages from a docs section, bulk-scrape multiple pages following links, or says "crawl", "get all the pages", "extract everything under /docs", "bulk extract", or needs content from many pages on the same site. Handles depth limits, path filtering, and concurrent extraction.
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