“structured”的搜索结果

Complete knowledge domain for Firecrawl v2 API - web scraping and crawling that converts websites into LLM-ready markdown or structured data. Use when: scraping websites, crawling entire sites, extracting web content, converting HTML to markdown, building web scrapers, handling dynamic JavaScript content, bypassing anti-bot protection, extracting structured data from web pages, or when encountering "content not loading", "JavaScript rendering issues", or "blocked by bot detection". Keywords: firecrawl, firecrawl api, web scraping, web crawler, scrape website, crawl website, extract content, html to markdown, site crawler, content extraction, web automation, firecrawl-py, firecrawl-js, llm ready data, structured data extraction, bot bypass, javascript rendering, scraping api, crawling api, map urls, batch scraping

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Extract structured data from LLM responses with Pydantic validation, retry failed extractions automatically, parse complex JSON with type safety, and stream partial results with Instructor - battle-tested structured output library

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Generate JSON-LD structured data for AEM Edge Delivery Services pages. Analyzes page content and metadata to determine the appropriate schema.org types, extracts relevant properties, and produces validated JSON-LD snippets ready for implementation in head.html or scripts.js. Use when adding rich results support, improving search appearance, or auditing existing structured data.

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Extracts structured data from LLM responses using JSON schemas, Zod validation, and function calling for reliable parsing. Use when users request "structured output", "JSON extraction", "parse LLM response", "function calling", or "typed responses".

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Enforces consistent structured logging with request correlation IDs, standardized log schema, middleware integration, and best practices. Use for "structured logging", "log standardization", "request tracing", or "log correlation".

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通过多轮访谈梳理品牌目的、定位、客户群、个性和表达风格，整理创始人之间的共识与分歧，最终形成可向设计师、文案及外部协作者共享的品牌手册。

• 确定新品牌的方向
• 重新审视品牌定位
• 统一多位创始人的认识

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

通过多次访谈梳理品牌目的、受众和表达风格，保存回答与进度并汇编为品牌手册，帮助创始人明确想法，向设计师和文案人员共享品牌方向。

• 确定新品牌的方向
• 重新审视品牌定位
• 准备设计师或文案人员的工作简报

在AI代理反复失败或重复操作时，记录错误与环境前提、排查原因，采取影响有限的恢复操作，并汇总结果和证据，为有依据的重试与交接提供支持。

• 排查重复调用工具的原因
• 调查对话膨胀导致的质量下降
• 核对文件路径与环境差异

通过 Claude DevFleet 将开发工作分配给多个 Claude Code 智能体，在独立工作目录中并行执行，并管理任务依赖、进度以及变更、测试和错误报告。

• 将开发计划拆分为带依赖关系的任务
• 在独立工作目录中并行开发
• 检查多个开发任务的进度

帮助将Firecrawl的`/scrape`集成到应用中，从已知网址获取单页正文、链接、图片等信息，并设置复用数据的时效限制。

• 导入已知网页以便生成摘要
• 从企业或产品页面补充信息
• 提取价格、更新记录和文档

通过对话完成提案、规格文档和决策记录，从梳理背景、逐节起草到读者验证。让不了解写作过程的Claude阅读，找出解释不足和含糊之处。

• 将零散背景笔记整理成提案
• 编写规格文档和决策记录
• 逐节推敲结构与文字

从Hacker News首页获取排名前30的文章，以JSON格式汇总每篇文章的排名、标题、链接、积分和评论数，便于查看文章及其互动情况。

• 查看Hacker News前30篇文章
• 比较积分和评论数
• 收集文章标题与链接

Extract a Figma file into local project files containing its element hierarchy, reusable color and typography settings, and exportable assets. The structured snapshot supplies source data for later design mapping and implementation steps.

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• Extract a Figma file's element hierarchy
• Collect color, typography, and spacing settings
• Prepare assets for later implementation steps

Turn patient information into a structured HTML case report for rounds, conferences, or documentation. Choose a full presentation or brief update, with organized findings, diagnostic reasoning, and educational management plans in a printable layout.

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• Preparing a case presentation for a clinical conference
• Summarizing daily changes for rounds or handover
• Organizing findings into a SOAP-format report

Turn document analysis into a structured PPT presentation with images generated in a chosen style. The skill uses the NanoBanana stack to combine document-based content preparation and image generation within a presentation creation workflow.

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• Turning a document into a PPT presentation
• Creating slides with styled, generated images
• Combining document analysis and presentation creation

Turn a design request into a concrete specification covering colors, fonts, layout, mood, spacing, and constraints. Generate DESIGN.md and an HTML preview, with a clear report of defaults applied to unspecified choices.

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• Clarifying vague visual requirements before implementation
• Defining colors, fonts, and spacing for a landing page
• Reviewing design choices through an HTML preview

Create character, scene, and product images from structured descriptions of style, composition, lighting, and color. Guide generation with reference images and aspect ratio settings, using a Python script connected to a supported image generation service.

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• Creating characters with specified clothing, era, and appearance
• Visualizing scenes with a chosen mood, weather, and lighting
• Producing product images with specified materials and viewing angles

Generate videos from structured prompts describing subjects, visual style, camera work, and other scene details. The workflow creates English JSON prompts and runs a Python script, with optional reference images to guide the result.

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• Turn a scene idea into a video
• Generate a video guided by a reference image
• Specify visual style and camera movement

Turn academic papers into structured reviews that explain findings, strengths, weaknesses, and research methods. Assess originality and supporting evidence, compare relevant literature, and provide specific improvement suggestions in a detailed review or brief summary.

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• Understanding a paper's findings and limitations
• Preparing a draft peer review
• Checking experimental design and reproducibility

Create workflows that pause for approval and resume later, or scripts that distribute work across multiple agents. Choose a saved template for ongoing processes or a JavaScript script to collect structured results from parallel tasks.

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• Build a workflow with approval checkpoints
• Split review work across multiple agents
• Collect structured results from research tasks

Turn research findings stored in memory into structured reports with evidence ratings, source references, and practical recommendations. Compare conflicting claims, identify unresolved questions, and explain limitations so accumulated research can support decisions and next steps.

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• Combine findings from several research sessions
• Compare conflicting claims and their supporting evidence
• Prepare a research brief with recommended next steps

Investigate complex topics using web sources, stored knowledge, and relevant code. Break questions into smaller parts, compare evidence, and produce a structured report with confidence assessments, unresolved questions, and next steps.

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• Investigating a complex topic through smaller research questions
• Comparing web sources with stored knowledge and code
• Summarizing evidence quality and conflicting findings

Extract text, tables, and attributes from rendered web pages into structured data. Check extracted content for personal information and malicious instructions, and save reusable extraction templates for pages on the same host.

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• Extracting text and tables from rendered web pages
• Saving templates for recurring extraction tasks
• Applying a saved template to another URL on the same host