“traction”的搜索结果

帮助设计表单、发票和题集的信息提取流程，先用正则表达式提取并清理文本，再评估置信度，仅将不确定的条目交给LLM检查和修正，同时介绍测试与指标记录。

• 提取题干、选项和答案
• 设计表单或发票提取流程
• 选择正则表达式或LLM

Coordinate bulk contract clause extraction with Luminance or Kira, prepare loading requests, and check returned results according to your team's review settings. Assess flagged clauses against the transaction and organize findings and required consents.

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• Preparing bulk clause extraction requests for contract batches
• Sampling AI extraction results against original clauses
• Checking whether change-of-control clauses apply to a deal

Extracts structured data from large sets of legal documents into tabular format for review, analysis, and reporting. Processes contracts, agreements, correspondence, filings, and other legal documents in bulk — extracting key terms, dates, parties, obligations, risks, and custom fields into organized tables. Use when conducting due diligence document review, bulk contract extraction, compliance audits across document sets, lease portfolio analysis, employment agreement review, regulatory filing review, or any task requiring structured extraction from multiple documents. Trigger keywords: tabular review, bulk extraction, document review table, data room review, batch document analysis, contract extraction, portfolio review, structured extraction, document comparison table.

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Extract PDF text using a sequence of tools when one method fails. Validate downloaded files, check whether the extracted text is substantial, record the successful method, and investigate alternative sources if extraction remains unsuccessful.

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• Extracting text from regulatory documents and handbooks
• Checking whether a PDF download returned an error page
• Trying another tool after empty or garbled text extraction

Download PDFs, check that the files contain valid content, and try several text extraction tools in sequence. The workflow helps detect downloaded error pages, insufficient text, and extraction failures while recording diagnostic details.

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• Extract text from official PDF handbooks
• Check whether a downloaded PDF is actually an error page
• Try another extractor when PDF text extraction fails

Pick the right LLM for LEGAL INFO EXTRACTION — pulling facts, clauses, dates, parties, obligations, and structured fields out of contracts and legal documents. Vendor-neutral routing grounded in mid-2026 benchmarks (legalbenchmarks.ai Info Extraction; CUAD/MAUD/ACORD). Asks up to 4 quick questions (cost, speed, accuracy/stakes, privacy/jurisdiction/language), then recommends a primary model + fallback + what to avoid + what a human must verify. Use when someone asks "which model should I use to extract clauses/data from these documents", "best AI for contract data extraction", "route this extraction task", or is about to pull structured fields from legal docs without a fixed model.

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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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介绍在Claude Code会话结束时提取并保存可复用解决步骤的旧版机制。该版本已弃用，适合检查现有环境的兼容性、提取设置及已保存的学习内容。

• 检查旧版会话结束钩子设置
• 调整提取标准和目标分类
• 复查已保存的学习技能

Keep older web extraction commands working during migration by forwarding a supplied URL to browser-extract after displaying a deprecation notice. This compatibility shim helps existing callers transition to the replacement skill and its template option.

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• Keeping older web extraction commands working during migration
• Switching URL extraction requests to browser-extract
• Moving an expected extraction format into a named template

Add support for a programming language to codegraph, from connecting its parser and implementing code extraction to writing tests. Evaluate extraction quality and compare agent effort with and without codegraph across three real codebases.

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• Adding a new programming language to codegraph
• Testing extraction of functions, imports, and calls
• Comparing agent effort across three real codebases

Extracts, converts, or edits selected parts of spreadsheets, Word documents, PDFs, and PowerPoint files. It creates a separate output file, checks that the selection still matches the source, and verifies the saved result without modifying the original.

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• Export an Excel range as CSV, Markdown, or XLSX
• Extract Word paragraphs or create an edited copy
• Save a selected PDF page as a separate file

Trace uploaded files through extraction, conversion, parsing, and reconstruction of saved objects in a CTF sandbox, an isolated competition environment. Preserve original and derived files, distinguish visible validation from backend behavior, and document the smallest reproducible processing chain.

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• Trace an uploaded file to its backend effect
• Investigate archive extraction and preview generation
• Compare visible validation with backend file handling

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 text from PDFs when the first reading attempt fails or produces poor results. The skill tries command-line tools, Python libraries, then OCR, which recognizes text in images, while checking output quality and recording successful methods.

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• Retrying PDF extraction after errors or empty output
• Reading scanned documents with OCR
• Extracting text and tables from structured PDFs

Extract text from downloaded PDFs by checking for invalid files, trying three extraction tools in sequence, and validating the results. This workflow helps identify download errors, empty output, and encoding problems during document retrieval.

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• Extracting text from government and agency PDFs
• Detecting error pages downloaded as PDFs
• Trying alternative tools after empty or garbled extraction

Inspect unfamiliar Excel workbooks before building extraction scripts. Map sheets, headers, columns, and row patterns, then use those findings to distinguish actual records from summaries and blank rows when extracting data.

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• Inspecting Excel files received from external sources
• Extracting records from sheets with merged cells
• Investigating missing or unexpected extraction results

Make C# code testable when it directly uses static services such as time, files, or processes. It introduces existing abstractions or minimal wrappers, supplies dependency registration, and demonstrates tests with controlled substitutes for real resources.

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• Introducing TimeProvider for time-dependent tests
• Testing file operations with MockFileSystem
• Wrapping Environment, Console, or Process calls

Analyze the photograph uploaded by the user, deconstruct its visual evidence, abstract and distill the essential relationships, then reconstruct them as a new nonliteral lower-panel composition guided by 19 bundled references. Use for CLEAN upper-photo/lower-abstraction editorial artworks with a number, date, and short phrase in the lower panel. This is abstraction and reconstruction, never style conversion or a miniature redraw. Preserve the exact user-uploaded photograph unchanged above.

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Applies the Bullseye Framework from Traction by Gabriel Weinberg and Justin Mares. Use when choosing growth channels, testing customer acquisition strategies, or deciding where to spend marketing effort. Covers all 19 traction channels with selection methodology, testing protocol, and phase-matched channel advice. Triggers include 'how do we get customers', 'which marketing channel should we use', 'we have a product but no users', 'our growth has stalled', 'should we do content marketing or paid ads', 'how do we test traction channels', 'what channels work at our stage'. NOT for product development (use Lean Startup), not for positioning/messaging (use Obviously Awesome), not for pricing (use Monetizing Innovation), not for enterprise sales methodology (use SPIN Selling).

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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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给定 PMID/PMCID 取结构化全文（NLM BioC XML/JSON）。封装 BioC PubMed（标题+摘要）和 BioC PMC OA（开放获取全文）端点，输出按章节切分的段落、表格上下文、RAG 友好 chunk，适合大批量入向量库。Fetches structured fulltext from NLM BioC API for PMID/PMCID, outputs section-segmented paragraphs and RAG-ready chunks. 触发词：全文抽取 / BioC / RAG 入库 / 文献全文 / PMC 开放获取 / structured fulltext / 段落抽取 / 表格抽取 / chunking / fulltext to vector store / paragraph extraction.

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Specialized skill for testing file system operations using System.IO.Abstractions. Use when you need to test File, Directory, Path operations, or simulate file system. Covers IFileSystem, MockFileSystem, file read/write testing, directory operation testing, etc. Keywords: file testing, filesystem, file testing, file system testing, IFileSystem, MockFileSystem, System.IO.Abstractions, File.ReadAllText, File.WriteAllText, Directory.CreateDirectory, Path.Combine, mock file system, file abstraction

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帮助将Firecrawl的`/search`集成到应用或智能体流程中，从搜索词找到候选网页、选择信息来源，并决定是否进一步获取页面正文。

• 为带出处的回答寻找信息来源
• 探索企业、竞争对手或主题
• 筛选值得深入阅读的网页

将业务亮点、发展成果、竞争优势和融资需求整理成面向投资者的HTML幻灯片，并配备演讲者备注，用于融资路演。

• 制作Demo Day融资路演资料
• 向投资者说明发展成果与竞争优势
• 制作带演讲者备注的HTML演示文稿