Results for “document-ingestion”

Data framework for building LLM applications with RAG. Specializes in document ingestion (300+ connectors), indexing, and querying. Features vector indices, query engines, agents, and multi-modal support. Use for document Q&A, chatbots, knowledge retrieval, or building RAG pipelines. Best for data-centric LLM applications.

Ingests case studies, past proposals, and boilerplate from library/inbox into structured indexes. Use when the user requests to 'index proposal library', 're-index case studies', 'ingest inbox docs', or 'validate library'.

Team-Wiki Ingest

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.

Converts raw, unstructured sources into structured wiki pages with YAML frontmatter, Counter-Arguments sections, and bidirectional wikilinks, storing them in MemPalace.

Adversarial one-question-at-a-time questioning to verify deep reading comprehension of alignment pages, specs, or any document

Search archived video using natural language, ingest video files or RTSP streams, and manage ingested sources.

Index folders of PDFs and other documents into LanceDB for vector search, then query them with semantic search, page filters, verbatim quotes, and cross-document aggregation.

Maps, documents, and onboards into an existing codebase by generating seven structured documents covering stack, structure, architecture, conventions, integrations, testing, and concerns.

Wraps the notebooklm-py CLI to ingest sources and generate synthesized artifacts like podcasts, slide decks, and quizzes from Google NotebookLM.

Acquires resources from URLs, PDFs, and local files, categorizes them, and organizes content and media into a structured workspace with a lowercase assets folder.

Imported skill document from anthropic

Detect and defend against prompt injection hidden in documents, web pages, and images consumed by an agent.

Imported skill readme from openai

Feature Intake

Upserts a validated MDX book corpus into Supabase via Drizzle, hydrating books, chapters, sections, and chunks tables while preserving stable bookmark anchors and only re-embedding changed content.

Lossless LLM-optimized compression of source documents. Use when the user requests to 'distill documents' or 'create a distillate'.

Ingest, index, search, edit, and generate video and audio content from files, URLs, live streams, or desktop capture.

Extract project vision and decisions from a user through iterative Q&A, then convert them into clear repo documentation (README, ADRs, lessons). Use when user asks to document ideas in their head.

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.

Creates, edits, and analyzes Word documents (.docx/.dotx) using docx-js, XML manipulation, and conversion tools, including tracked changes and comments.

Place trusted contextual information into prompts or agent state using explicit boundaries, provenance, and templates. Use when relevant context has already been selected and must be inserted safely; use context-retrieval to find it or context-optimization to choose and order it.

Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When Claude needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4) Adding comments, or any other document tasks

Create patient intake forms with history and screening. TRIGGERS - Use when user needs help with intake-form related tasks.

Create, read, edit, and manipulate Word documents (.docx) with formatting, tables, images, headers, footers, tracked changes, and comments.

Ingests video and audio from files, URLs, RTSP feeds, or desktop capture; indexes and searches moments with timestamps; transcodes, edits timelines, generates media assets, and creates real-time alerts for live streams.

Converting repository changes into detailed learning documents. Use when turning diffs into teaching materials, recording design decisions, or creating onboarding materials for new members.

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.

基于用户素材与可选外部发现搭建 ΩmegaWiki，并用并行 `/ingest` 完成最终论文集的消化

把一篇论文 ingest 进 wiki —— 建立 papers + concepts + people + claims 页面，并完成所有双向交叉引用与 graph edge。当用户说 "ingest"、"加入这篇论文"、丢 `.pdf` / `.tex` / arXiv URL 或要求把论文折叠进知识库时触发。

Organizes discovered pathway, portal, and theme content into a docs repository by copying new files, resolving duplicates, updating the README, and generating per-portal indexes.

每日从 arXiv 拉取新论文，过滤相关性，auto-ingest 高优先级论文，检测 SOTA 更新

Ingests music into a LanceDB via ncmdump-rs and sf-cli, searching and downloading from Netease Cloud Music or Bilibili, decrypting local NCM files, and extracting metadata, lyrics, and cover art.