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Found 18 Skills
UiPath IXP (Document Understanding) via `uip ixp` — create projects (with autopilot taxonomy suggestion, an imported taxonomy file, or empty), upload/download/delete documents, author the taxonomy (field groups, fields, data types, per-field and overall extraction instructions), configure the extraction model and pre-processing, review/confirm/unconfirm predictions, mark fields missing, pull metrics and model versions, publish/tag/roll back model versions, deploy a trained version to an Orchestrator folder and move an existing deployment to another version (`deployments create`/`upgrade`/`list`). DO NOT TRIGGER during .flow / Maestro Flow work — discovering or listing IxP / document-extraction models, extractors, or nodes available to Maestro Flow, and adding or wiring an IxP node, belong to uipath-maestro-flow even when they sound like IXP model management.
Chunk a document into provenance-carrying JSONL ready for embedding via the Nutrient Data Extraction API (`/extraction/parse`, spatial output). Every chunk carries element type, page index, bounding box, confidence, and reading order, traceable to a specific page region. Use for grounded or auditable RAG, cited retrieval, confidence-aware ingestion, or any pipeline that must prove which document region a retrieved answer came from. Triggers include grounded RAG, auditable RAG, RAG with provenance, chunk with bounding box, cite page, provenance-carrying chunks, confidence-aware chunking, or embedding pipeline. Not for cheap Markdown — use document-extraction-api with `--output-format markdown` for that. Not for known target fields — if the user wants specific fields ("invoice number and total", "map to my schema", "return these fields cited"), use document-extraction-api's `extract` (one cited call), not whole-document chunking.
Build or update a chronology from declared document sources and uploads — dated events extracted, de-duped, and tagged by significance per the matter theory. Use when the user asks to build a chronology or timeline from a production or matter file, says "chron from the production" or "what happened when", or needs a working, statement-of-facts, or witness-specific timeline.
Azure AI Document Intelligence SDK for .NET. Extract text, tables, and structured data from documents using prebuilt and custom models. Use for invoice processing, receipt extraction, ID document analysis, and custom document models. Triggers: "Document Intelligence", "DocumentIntelligenceClient", "form recognizer", "invoice extraction", "receipt OCR", "document analysis .NET".
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".
Comprehensive PDF Operation Tool: Extraction, Merging, Annotation, Form Processing
PDF 文档离线读写与表单处理：提取文本/表格、合并拆分、生成 PDF、填写表单。适用于“本地处理/读取/生成 PDF 文件”（依赖安装可能需要网络）。
TensorLake SDK for building agentic workflows, sandboxed code execution, and document parsing/extraction. Use when the user mentions tensorlake, or asks about TensorLake APIs/docs/capabilities. Also use when the user is building AI agents or agentic applications that need serverless workflow orchestration (parallel map/reduce DAGs), sandboxed execution of LLM-generated code, or document parsing, structured extraction, and OCR from PDFs/images. Works with any LLM provider (OpenAI, Anthropic), agent framework (LangChain, CrewAI, LlamaIndex), database, or API as the infrastructure layer.
Process and extract information from PDF documents. Use this skill when the user asks to read, analyze, or extract data from PDF files.
Extract text from PDFs as structured, semantic Markdown. Use when converting a PDF to Markdown, extracting text from a PDF, processing one or more PDFs into Markdown output, reading PDF contents for analysis, ingesting documents for RAG pipelines, preparing PDFs for LLM context, or any task where PDF text needs to be in a machine-readable format. ALWAYS use this skill when the user has a PDF and needs its content as text or Markdown — even if they don't explicitly say "convert to markdown".
Quickly screen inbound deal flow — CIMs, teasers, and broker materials — against the fund's investment criteria. Extracts key deal metrics, runs a pass/fail framework, and outputs a one-page screening memo. Use when reviewing new deal flow, triaging inbound materials, or deciding whether to take a first call. Triggers on "screen this deal", "review this CIM", "should we look at this", "triage this teaser", or "deal screening".
Extract text from PDFs for LLM consumption. Use when processing PDFs for RAG, document analysis, or text extraction. Supports API services (Mistral OCR) and local tools (PyMuPDF, pdfplumber). Handles text-based PDFs, tables, and scanned documents with OCR.