'documents' 검색 결과

Guides building AI applications that search documents before answering questions, an approach called RAG. Covers importing files and web data, creating searchable indexes, adding conversational interfaces, and evaluating whether answers match the retrieved material.

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• Build a question-answering system for internal documents
• Create a chatbot that remembers conversation context
• Search information across files, web pages, and databases

Use Meta's Prompt Guard to detect malicious instructions in user prompts and external data. This skill guides input filtering, batch checks for retrieved documents, detection threshold adjustments, and splitting long text for inspection.

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• Detecting attempts to override an LLM's instructions
• Checking API responses for embedded malicious instructions
• Batch screening documents retrieved for RAG

Design and implement RAG systems, which retrieve documents to inform AI answers. Get document preparation strategies, vector database comparisons, combined keyword and meaning-based search, result reranking, and an evaluation plan for retrieval quality.

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• Design an AI application that answers using internal documents
• Compare vector databases and document splitting strategies
• Improve search through keyword matching and result reranking

Turn dispute documents into a sourced timeline by extracting dated events and merging duplicates. It highlights significance for the case, records missing source coverage, and supports updated timelines, factual narratives, and timelines focused on a named witness.

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• Building a dispute timeline from emails and contracts
• Organizing events from disclosed litigation documents
• Preparing a sourced narrative of the facts

Prepare an outline for a deposition, a formal session for taking witness testimony. Using case strategy and witness documents, the skill organizes questions, key evidence, inconsistent prior statements, and exhibits, adapting question style to the witness's role.

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• Building a deposition outline for a named witness
• Organizing key documents involving a witness
• Preparing questions suited to the witness's role

Add documents, interview notes, or observations to an open investigation. Process batches against documented selection criteria, surface significant items, and log everything reviewed so the team can verify coverage and update its source checklist.

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• Add interview notes to an open investigation
• Process a newly received batch of documents
• Add an email export to an investigation

Apply OpenClaw’s brand identity to documents, presentations, social graphics, and launch materials. The skill guides color, typography, logo use, imagery, and writing tone, with checks for contrast, cropping, and text readability.

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• Align documents and presentations with the brand
• Unify social graphics and launch materials
• Review logo use, typography, and colors

Convert legal documents in PDF, DOCX, or TXT format into structured Markdown. The workflow organizes legal headings, checks text preservation and formatting, and produces a review report alongside the final document when checks pass.

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• Convert legal PDFs or Word documents to Markdown
• Organize chapter and article headings
• Check whether formatting changes preserved the text

Convert PDF, Word, and Excel documents into structured Markdown for search and knowledge bases. The skill tries three parsers in sequence when needed and returns metadata, a confidence score, and the parser used.

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• Prepare documents for retrieval-augmented generation
• Structure documents for an internal knowledge base
• Extract structured text from contracts

Organize parsed documents into four color-coded cards covering facts, explanations, risks, and actions. Preserve source references and generation details so readers can review evidence, identify uncertainty, and consider next steps in research, financial, or legal analysis.

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• Separating facts from interpretations in financial reports
• Organizing evidence and risks in legal documents
• Turning research documents into evidence-linked analysis cards

Extract text from images and PDFs, including handwriting, tables, invoices, and receipts. Return plain text, Markdown tables, or structured JSON fields, with options to select a recognition provider and specific PDF pages.

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• Extract text from scanned documents
• Convert table images into Markdown
• Extract invoice and receipt fields as JSON

Generate documents through shell scripts when standard tools fail, then locate files saved in nested folders. Covers finding PowerPoint or PDF outputs, copying them to the delivery location, and checking that the resulting files exist and are usable.

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• Generate documents when standard tools fail
• Find PowerPoint or PDF files in nested folders
• Copy generated files to the delivery folder

Extract text from PDFs by trying several methods in sequence and checking the results. When ordinary extraction yields too little text, switch to OCR, which recognizes text in images, to process scanned documents.

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• Extracting text from PDFs of unknown types
• Reading text from scanned documents
• Batch processing PDFs in different formats

Extract edit times from documents, inspect audio for clicks and level issues, and guide production of stems, or separate audio parts. Each stage includes checks, ending with a mixed export verified for duration, format, and audio levels.

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• Editing audio from instructions in DOCX or text documents
• Checking clicks and levels at specified times
• Verifying the duration and sample rate of each stem

Build and maintain business data in iPollo Onto using connected tables and documents. The skill guides agents through creating structures, saving research in batches, updating existing records, and examining relationships with supporting evidence.

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• Build a CRM with linked customers, contacts, and opportunities
• Save prospect research progressively
• Prioritize customers using related business records

Use extracted document content, design evidence, and local assets in iPolloWork video, slide, website, or design templates. Apply confirmed requirements and verify that supplied assets actually appear in the output, without using models to reparse references.

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• Create slides using facts and figures from reference documents
• Apply supported reference styles to a website template
• Reuse document assets in video scenes

Test whether instructions hidden in simulated documents, retrieved passages, or web pages can redirect an agent. The skill checks for unwanted behavior or sensitive disclosures and reports confirmed failures with the test dialogue as evidence.

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• Testing resistance to instructions embedded in uploaded documents
• Checking retrieved passages used to answer questions
• Evaluating hidden instructions in web page content

Clean up DeepChat's specification-driven development documents after implementation and validation. Review feature, issue, and architecture files, remove completed or obsolete material when evidence supports deletion, and preserve maintained specifications while checking references.

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• Remove issue documents after confirming a bug is resolved
• Clear old plans from completed feature work
• Update or remove architecture documents after replacement

Create, edit, and troubleshoot Typst documents, a system for producing formatted documents from text files. Uses bundled documentation to check syntax and styling, with formatting checks and compilation when the required tools are available.

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• Creating a new Typst document
• Adjusting page layout, tables, and heading styles
• Fixing syntax and compilation errors

Continue an existing OpenSpec change by creating one next document. Check progress and dependencies, follow the workflow's template, and report what was completed and which documents are now available to create.

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• Resume documentation for an existing change
• Create and review one document at a time
• Draft specifications or design from earlier documents

Extract text, tables, and images from PDFs, combine or split documents, rotate pages, fill forms, and create new files. It also covers password protection and OCR, which recognizes text in scanned pages for searching and reuse.

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• Extracting text and tables from documents
• Combining PDFs or splitting out selected pages
• Recognizing text in scanned documents

Convert LaTeX papers and reports into Typst documents, including structure, formatting, equations, figures, tables, citations, and cross-references. Reference guides and symbol mappings help translate individual commands or migrate an entire article.

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• Migrate an academic paper from LaTeX to Typst
• Find Typst equivalents for LaTeX commands and math symbols
• Convert tables, citations, and cross-references

Universal LaTeX document skill: create, compile, and convert any document to professional PDF with PNG previews. Supports resumes, reports, cover letters, invoices, academic papers, theses/dissertations, academic CVs, presentations (Beamer), scientific posters, formal letters, exams/quizzes, books, cheat sheets, reference cards, exam formula sheets, fillable PDF forms (hyperref form fields), conditional content (etoolbox toggles), mail merge from CSV/JSON (Jinja2 templates), version diffing (latexdiff), charts (pgfplots + matplotlib), tables (booktabs + CSV import), images (TikZ), Mermaid diagrams, AI-generated images, watermarks, landscape pages, bibliography/citations (BibTeX/biblatex), multi-language/CJK (auto XeLaTeX), algorithms/pseudocode, colored boxes (tcolorbox), SI units (siunitx), Pandoc format conversion (Markdown/DOCX/HTML ↔ LaTeX), and PDF-to-LaTeX conversion of handwritten or printed documents (math, business, legal, general). Compile script supports pdflatex, xelatex, lualatex with auto-detection, latexmk backend, texfot log filtering, PDF/A output, and verbosity control (--verbose/--quiet). Empirically optimized scaling: single agent 1-10 pages, split 11-20, batch-7 pipeline 21+. Use when user asks to: (1) create a resume/CV/cover letter, (2) write a LaTeX document, (3) create PDF with tables/charts/images, (4) compile a .tex file, (5) make a report/invoice/presentation, (6) anything involving LaTeX or pdflatex, (7) convert/OCR a PDF to LaTeX, (8) convert handwritten notes, (9) create charts/graphs/diagrams, (10) create slides, (11) write a thesis or dissertation, (12) create an academic CV, (13) create a poster, (14) create an exam/quiz, (15) create a book, (16) convert between document formats (Markdown, DOCX, HTML to/from LaTeX), (17) generate Mermaid diagrams for LaTeX, (18) create a formal business letter, (19) create a cheat sheet or reference card, (20) create an exam formula sheet or crib sheet, (21) condense lecture notes/PDFs into a cheat sheet, (22) create a fillable PDF form with text fields/checkboxes/dropdowns, (23) create a document with conditional content/toggles (show/hide sections), (24) generate batch/mail-merge documents from CSV/JSON data, (25) create a version diff PDF (latexdiff) highlighting changes between documents, (26) create a homework or assignment submission with problems and solutions, (27) create a lab report with data tables, graphs, and error analysis, (28) encrypt or password-protect a PDF, (29) merge multiple PDFs into one, (30) optimize/compress a PDF for web or email, (31) lint or check a LaTeX document for common issues, (32) count words in a LaTeX document, (33) analyze document statistics (figures, tables, citations), (34) fetch BibTeX from a DOI, (35) convert a Graphviz .dot file to PDF/PNG, (36) convert a PlantUML .puml file to PDF/PNG, (37) create a one-pager/fact sheet/executive summary, (38) create a datasheet or product specification sheet, (39) extract pages from a PDF (page ranges, odd/even), (40) check LaTeX package availability before compiling, (41) analyze citations and cross-reference with .bib files, (42) debug LaTeX compilation errors, (43) make a document accessible (PDF/A, tagged PDF), (44) create lecture notes or course handouts, (45) fill an existing PDF form (fillable fields or non-fillable with annotations), (46) extract text or tables from a PDF (pdfplumber, pypdf), (47) OCR a scanned PDF to text (pytesseract), (48) create a PDF programmatically with reportlab (Canvas, Platypus), (49) rotate or crop PDF pages (pypdf), (50) add a watermark to an existing PDF, (51) extract metadata from a PDF (title, author, subject).

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Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a 'report', 'memo', 'letter', 'template', or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.

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