'summarization' 검색 결과

"Implement text summarization using extractive and abstractive approaches. Use this skill when the user needs to condense long documents, build an automatic summarization pipeline, or compare summarization strategies — even if they say 'summarize this document', 'TLDR', or 'key points extraction'.".

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Add on-device language model features to iOS 26+ apps with Apple's FoundationModels framework. Covers text generation, summarization, extracting data into Swift types, calling custom app functions, and progressively updating screens as responses are generated.

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• Adding offline text generation and summarization
• Extracting structured data from user input
• Connecting AI responses to custom app functions

Send a single request to DeepSeek for summarization, information extraction, or simple classification. Receive the response and token usage as JSON for further processing, with structured status information when the API is unavailable.

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• Summarizing text in a single request
• Extracting information from text
• Classifying text into simple categories

Add Claude-powered features, such as summarization, to HTML artifacts using a built-in helper. No SDK or API key is needed, and tools defined in the page can run during a request before the final text is returned.

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• Adding text summarization to an HTML prototype
• Trying AI responses with conversation history
• Connecting Claude to tools that run within a page

Design how an AI agent trims long conversations and large tool outputs while retaining decisions, constraints, failed approaches, and sources. Compare summarization strategies, choose compression triggers, and consider separate subagents to keep intermediate information out of the main conversation.

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• Managing large search results and tool outputs
• Preserving decisions and constraints during summarization
• Choosing compression triggers and batch processing

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

Conversation summarization for memory compression and context management

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Integrates Power Pages generative-AI summarization APIs (PREVIEW) into a Single Page Application (SPA) site — the Search Summary API and the Data Summarization API — on any record-detail or list page. Generates per-target service code (CSRF-handled) and AI site settings; delegates Web API settings, table permissions, and web roles to `/integrate-webapi` and `/create-webroles`. Use whenever a user wants AI/Copilot output that condenses Dataverse content on a Power Pages site — an AI summary, AI-generated overview or "key insights" across a record or list, a search-results summary, a case/incident summary, or recommendation-chip refinement — even when phrased as "AI-generated paragraph", "insights", or "overview". Do NOT use for: generative pages in model-driven apps (use the model-apps `genpage` skill), Copilot Studio agents/chatbots, summarizing documents or PDFs, Power BI dashboards, plain keyword search with no AI summary, or plain Dataverse CRUD (use `/integrate-webapi`).

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Use ManagedCode.MarkItDown when a .NET application needs deterministic document-to-Markdown conversion for ingestion, indexing, summarization, or content-processing workflows. USE FOR: ManagedCode.MarkItDown integration; document ingestion flows; Office or rich-text conversion to Markdown; indexing and summarization pipelines. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

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Summarize text using extractive, abstractive, hierarchical, and multi-document techniques, producing concise outputs at configurable detail levels. Use when the user requests summarization or provides relevant inputs for this workflow.

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Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rotUse when "context window, token limit, context management, context engineering, long context, context overflow, llm, context, tokens, memory, summarization, optimization" mentioned.

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Manages context passing between DAG nodes and spawned agents. Handles context summarization, selective forwarding, and token budget optimization. Activate on 'bridge context', 'pass context', 'summarize context', 'context management', 'agent context'. NOT for execution (use dag-parallel-executor) or aggregation (use dag-result-aggregator).

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This skill should be used when the user asks to "proofread", "校正", "誤字脱字チェック", "表記揺れ", "typo check", "文書チェック", "法律文書の確認", "この書面チェックして", "おかしいところない？", "文章確認して", "間違いがないか確認", "書面の確認", or wants to review a Japanese legal document for writing errors. Do NOT trigger for translation, summarization, or content generation requests.

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Integrate single-page extraction into an application using Firecrawl scrape. Retrieve Markdown, HTML, links, screenshots, metadata, or structured data from a known URL, and configure how recently cached content may be reused.

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• Preparing known web pages for summarization
• Enriching records from company or product pages
• Extracting pricing, changelogs, or documentation

Build Claude applications using guidance for the official Anthropic SDK. Choose an integration approach, implement streaming and tool use, and follow workflows for model migration, prompt audits, evaluation, and cost optimization.

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• Build a summarization app with Claude API
• Choose how to run an agent with custom tools
• Migrate existing code to a newer Claude model

Search the web with Exa and retrieve full page text, highlights, or summaries. Choose search modes, narrow results by category and supported filters, and receive structured JSON for research and content collection workflows.

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• Find research papers on a specific topic
• Collect information about companies
• Track news within a publication date range

Create presentation drafts from text, outlines, or documents through the 2slides API. Match a reference image's style, choose themes, add AI voice narration, and export slide images or audio for review and use.

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• Create a presentation from text or an outline
• Summarize a document into slides
• Match slide styling to a reference image

Convert Excel workbooks into Markdown tables organized by sheet, preparing their contents for reading, summarizing, searching, or extracting data. The bundled script also extracts embedded pictures and processes folders of workbooks, including subfolders when requested.

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• Preparing an Excel budget for summarization
• Converting workbooks before searching or extracting values
• Batch converting Excel files across folders

Convert Word documents into Markdown text for summarizing, searching, comparing, or extracting information. The bundled script saves embedded images alongside each document and supports processing entire folders, including subfolders, before the agent analyzes the converted content.

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• Prepare Word reports for summarization
• Extract information from resumes or proposals
• Convert a folder of Word documents in one batch

Manage the limited information an LLM can process at once. Use importance-based summaries, selective trimming, token counting, and content placement to plan what stays in context and address information loss during long conversations.

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• Planning how to handle conversations near the token limit
• Summarizing a long dialogue while preserving key information
• Reviewing the placement of important instructions and facts

Open existing PDFs in an interactive viewer to review pages together, highlight text, add comments or stamps, fill forms, and place signature images. Check changes visually and download the annotated document from the viewer.

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• Reviewing contract terms with highlights and comments
• Filling PDF forms while checking the page
• Placing signature or initials images

Develop applications with the Claude API using examples from Anthropic's official cookbooks. Explore document summarization, image analysis, document retrieval, external tool calls, and prompt caching through practical Python code and implementation guidance.

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• Learning basic Claude API integration
• Building an assistant that searches documents
• Extracting text and information from images

Apply over 240 reusable prompt templates to summarize content, extract insights, improve writing, review code, or analyze security threats. It reads each template directly and returns results in the format defined for that task.

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• Extract ideas and insights from an article
• Create a concise five-sentence summary
• Improve writing or review code with a selected template

Explore how coordinating agents can pass relevant working state to workers through KV cache, a model's internal attention memory. Covers task-specific selection, runtime requirements, and comparisons of accuracy, token use, and processing overhead.

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• Reducing repeated history sent to worker agents
• Comparing internal memory sharing with text summaries
• Assessing runtime support for KV cache compaction