“structured”的搜索结果

检查网站的技术问题、页面标题与描述、结构化数据及显示性能，制定具体到页面的SEO改进方案并推进实施，让搜索引擎更容易发现和收录内容。

• 排查页面未被搜索引擎收录的原因
• 改进标题、描述和页面各级标题
• 为文章或商品添加结构化数据

使用JSON、正则表达式、Pydantic类型定义或固定选项约束LLM输出，将文字中提取的信息和分类结果整理为便于后续程序使用的格式。

• 从文字中提取企业和产品信息
• 按固定标签分类评论
• 按字段整理个人资料

从文本中提取所需信息，整理为固定字段，并用Pydantic验证类型和值。涵盖结构化大语言模型输出、验证失败后的重试，以及逐步接收生成中的结果。

• 从文本中提取联系方式或企业信息
• 将文章归入预设类别
• 统一评论分析的字段

Build web search, page content retrieval, structured data extraction, and browser interactions into applications with Firecrawl. The skill guides endpoint selection, credentials, SDK or REST integration, and verification with a real request.

中文简介正在准备中。当前显示英语简介。

• Adding web search to an application
• Extracting structured data from known URLs
• Building website clicks and form filling into a workflow

Turn rough ideas into developed designs through structured questions and exploration of alternatives. Use it early in concept work to clarify an initial idea, consider different directions, and shape a more concrete design.

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• Developing a rough idea into a concrete design
• Exploring alternative directions for a concept
• Clarifying an idea through structured questions

Plan market, competitor, consumer, or financial research with chapter outlines, data requirements, and chart plans. Then turn collected evidence into a structured Markdown report with comparisons, citations, and strategic implications, while clearly identifying missing data.

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• Planning research chapters and data collection requirements
• Turning market and competitor findings into a report
• Organizing consumer insights and brand strategy analysis

Add or review Product structured data, machine-readable product details, on shop pages. Check names, images, prices, availability, and ratings against visible content, then validate the markup for eligibility to show enhanced Google search results.

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• Add Product JSON-LD to product pages
• Check structured prices against displayed prices
• Review availability and rating fields

Audit structured data for businesses serving a physical location or geographic area. Check or add LocalBusiness JSON-LD, a machine-readable format for business details, verify addresses against visible page content, and validate the markup with Google's Rich Results Test.

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• Audit structured data on a local business website
• Add business details to home and contact pages
• Choose a specific type for restaurants or stores

Add FAQ sections to landing pages or blog posts and generate FAQPage structured data, a format search engines can read. Check required question and answer fields, valid syntax, and consistency with content visitors can see.

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• Adding FAQ sections to landing pages or blog posts
• Generating structured data from existing questions and answers
• Checking FAQ markup against visible page content

Audit breadcrumb structured data, a machine-readable description of a page’s navigation path. Check that BreadcrumbList matches the visible trail and site hierarchy, then guide JSON-LD changes using the rendered HTML and HTTP response.

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• Check breadcrumb structured data
• Add JSON-LD for visible breadcrumbs
• Review site hierarchy after template changes

Audit whether author profiles clearly present relevant experience, qualifications, and professional links. Review rendered pages, metadata, structured data, and HTTP responses to identify specific places where author expertise needs clearer presentation and explain how to verify improvements.

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• Check whether article authors have relevant biographies
• Improve profiles with qualifications and professional links
• Audit author information in rendered HTML and structured data

Check a Twenty pull request through real browser scenarios derived from its changes. Verify database effects and server logs alongside visible results, then produce screenshots, a structured verdict, and a report of any failures or uncertainty.

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• Validate user flows before or after merging a Twenty pull request
• Check database writes and timeline activity after saving records
• Investigate backend errors hidden behind a successful screen

Delegate a clearly scoped coding task to Qoder in a specified project without opening its interactive interface. Read the structured JSON response and check its error flag before accepting the result.

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• Ask Qoder to review a specific file without editing
• Delegate a clearly scoped coding task to Qoder
• Check errors in Qoder's structured response

Compare a UI screenshot with reference images and receive a structured JSON assessment. Get a score, pass or revision status, concrete visual differences, and suggested edits for layout, spacing, typography, colors, and visual hierarchy.

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• Checking whether an implemented screen matches its reference
• Finding differences in spacing, typography, and colors
• Prioritizing edits from structured visual feedback

Use Outlines to make language models produce data in a defined format. The skill covers extracting information into JSON, restricting classification labels, and applying Pydantic models, which define fields and data types, with local model backends.

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• Extracting company or profile details into JSON
• Classifying text using a fixed set of labels
• Generating text that matches a specified pattern

Build Python workflows that constrain language model output using text patterns and grammar rules. Generate structured JSON, restrict classifications to allowed labels, extract information, and combine reusable generation steps with loops and tool selection.

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• Generate JSON with a defined structure
• Constrain date, email, and identifier formats
• Classify text using a fixed set of labels

Set up LLM serving with structured responses, including JSON and outputs restricted to specified patterns. Covers reusing shared prompt calculations, tool calling, and multi-turn conversations through SGLang, with examples for server setup and application integration.

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• Extract information into JSON with a defined schema
• Build agents that call tools
• Reuse shared prompts across chat requests

Extract figures and fields from emails, websites, and APIs into source-linked tracking tables. Configurable recipes guide collection, preserve original material, and check duplicates for records such as investor updates, expenses, and company metrics.

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• Track financial metrics from investor update emails
• Collect expenses from receipt emails
• Maintain a table of company updates

Create a structured hiring interview kit with questions tied to job skills, clear scoring criteria, interviewer assignments, and a discussion template. Use shared questions and evidence from candidates’ answers to support consistent evaluations.

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• Planning interviews for a specific role
• Creating questions for each required skill
• Aligning scoring criteria across interviewers

Examine strategic decisions through a structured meeting of AI agents representing executive roles. Gather independent recommendations, challenge assumptions, summarize disagreements, and record approved decisions with action owners and deadlines after the founder reviews the proposal.

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• Evaluate market expansion from several executive perspectives
• Compare views on product direction or pricing
• Review hiring plans and organizational choices

Turn game bug descriptions or suspected code problems into structured reports with reproduction steps, severity, and priority. Follow reported bugs through fix verification and closure, recording test results or manual checks before marking an issue closed.

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• Turning a bug description into a structured report
• Finding potential bugs in a specific file
• Verifying a fix through tests or manual checks

Design AI agents and chatbots in n8n, choosing suitable nodes and connecting models, tools, conversation memory, and structured JSON output. Includes guidance on document retrieval and human approval before tool execution.

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• Building a chatbot with conversation memory
• Connecting external tools to an AI agent
• Returning data in a defined JSON format

Build custom calculation and parsing tools that an n8n AI Agent can call. This skill covers JavaScript or Python inputs, structured arguments, string results, tool descriptions, and fixes for invocation and output errors.

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• Adding a calculation tool to an AI Agent
• Defining typed inputs for multiple arguments
• Fixing tool output type errors

Turn a meeting transcript into structured notes and one Linear ticket per action item. Assign owners from the discussion or the team’s ownership map, and flag unclear assignments in unassigned tickets for follow-up.

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• Turn meeting transcripts into structured notes
• Create Linear tickets for meeting action items
• Assign tasks using the team’s ownership map