“json schema”的搜索结果

When the user wants to add, fix, or optimize schema markup and structured data on their site. Also use when the user mentions "schema markup," "structured data," "JSON-LD," "rich snippets," "schema.org," "FAQ schema," "product schema," "review schema," "breadcrumb schema," "Google rich results," "knowledge panel," "star ratings in search," or "add structured data." Use this whenever someone wants their pages to show enhanced results in Google. For broader SEO issues, see seo-audit. For AI search optimization, see ai-seo.

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When the user wants to add, fix, or optimize schema markup and structured data on their site. Also use when the user mentions "schema markup," "structured data," "JSON-LD," "rich snippets," "schema.org," "FAQ schema," "product schema," "review schema," or "breadcrumb schema." For broader SEO issues, see seo-audit.

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Define a practical KPI dashboard, a view of key business measures, by organizing metric definitions, sources, formulas, periods, targets, and owners. Produces empty CSV, SQL, JSON Schema, or Notion import mappings when requested.

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• Choose metrics for a business decision
• Review an overcrowded KPI dashboard
• Create a CSV register of metric definitions

Design and refine prompts for AI applications using examples, reusable templates, and structured outputs such as JSON. Test variations for accuracy, consistency, response time, and token usage to diagnose unreliable answers and formatting failures.

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• Refine prompts that produce inconsistent answers
• Build reusable prompt templates with variables
• Design JSON outputs that follow a defined schema

Review and shorten tool instructions for AI agents by testing overlap with parameter schemas, the definitions of accepted inputs. It also guides writing clear usage rules while preserving warnings backed by past failures.

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• Audit tool instructions for repeated parameter explanations
• Test schema overlap before removing prompt lines
• Write tool selection rules and practical examples

Recommend where new gbrain pages belong using the active schema pack, a configuration defining page types and storage paths. It also checks existing pages for missing or undeclared types and highlights cases requiring a classification decision.

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• Choose a storage path before creating a brain page
• Check filing rules before a bulk import
• Apply classification settings for a specific source

Helps design and evaluate prompts for more reliable AI responses. Covers clear instructions, input-output examples, task breakdown, and structured formats such as JSON, with guidance on comparing quality, cost, and response time across models.

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• Clarify ambiguous instructions for an AI task
• Specify JSON output using schemas and examples
• Break complex tasks into connected prompts

Turn image briefs into structured prompts for GPT-Image-2 using reusable JSON templates, organized fields for visual requirements. Specify composition, text, lighting, and constraints for product images, posters, infographics, and other design work.

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• Prepare prompts for product images
• Specify poster titles and layouts
• Structure infographic content

Generate complete JSON-LD schema markup for blog posts with Article/BlogPosting, Person, Organization, BreadcrumbList, ImageObject, and optional FAQPage. Validates against Google requirements and warns about deprecated types. Use when user says "schema", "blog schema", "json-ld", "structured data", "schema markup", "generate schema".

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Generate JSON-LD for ONE blog post (BlogPosting with Person, Organization, BreadcrumbList, ImageObject, VideoObject; FAQPage only as optional entity markup) in a single @graph, and check it against Google's current structured data support. Use when the user says "generate schema", "json-ld for this post", "blog schema". Not for auditing schema across a whole site or other schema types (claude-seo seo-schema), not for product pages, and not a promise of rich results: FAQ rich results ended 2026-05-07.

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Tools are how AI agents interact with the world. A well-designed tool is the difference between an agent that works and one that hallucinates, fails silently, or costs 10x more tokens than necessary. This skill covers tool design from schema to error handling. JSON Schema best practices, description writing that actually helps the LLM, validation, and the emerging MCP standard that's becoming the lingua franca for AI tools. Key insight: Tool descriptions are more important than tool implementations. The LLM never sees your code - it only sees the schema and description. Use when "agent tool, function calling, tool schema, tool design, mcp server, mcp tool, tool use, build tool for agent, define function, input_schema, tool_use, tool_result, agents, tools, function-calling, mcp, json-schema, anthropic, openai, llm-tools" mentioned.

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Generate complete JSON-LD schema markup for blog posts including BlogPosting, Person, Organization, BreadcrumbList, FAQPage, and ImageObject. Validates against Google requirements and warns about deprecated types. Use when user says "schema", "blog schema", "json-ld", "structured data", "schema markup", "generate schema".

中文简介正在准备中。当前显示原文说明。

Generate JSON-LD for ONE blog post (BlogPosting with Person, Organization, BreadcrumbList, ImageObject, VideoObject; FAQPage only as optional entity markup) in a single @graph, and check it against Google's current structured data support. Use when the user says "generate schema", "json-ld for this post", "blog schema". Not for auditing schema across a whole site or other schema types (claude-seo seo-schema), not for product pages, and not a promise of rich results: FAQ rich results ended 2026-05-07.

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先确定前后端或服务间共享的API与事件数据规范，再生成类型，并按同一规范验证测试数据和实际响应，通过共同审查变更，减少并行开发中的字段偏差与兼容性问题。

• 并行开发前端和后端
• 统一服务间的API与事件格式
• 核对模拟响应与生产响应

Dry-run one cycle of a sales agent workflow without calling language models. Validate the template and agent types, check budget reservations, generate agent prompts, and record a structured status summary for downstream automation.

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• Demonstrating one cycle of a sales agent workflow
• Checking template validity and agent types
• Verifying budget caps and reservations

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 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

Consult a field reference for slide JSON, the structured data behind each page. It explains where content and styling live, how edits are validated, and why a saved change may display differently or have no visible effect.

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• Finding the field that controls text color or fonts
• Investigating rejected slide edits
• Diagnosing saved changes with no visible effect

Create and manage subscriptions that receive Google Workspace event notifications. Stream events as NDJSON, a format with one JSON record per line, and inspect, renew, reactivate, or delete subscriptions through the available commands.

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• Receiving Google Workspace event notifications
• Listing subscriptions and inspecting their details
• Renewing subscriptions or reactivating suspended ones

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

Manage shared iii configuration with JSON Schema, a definition of allowed value structures. Covers validated settings, automatic change notifications, YAML edits, temporary overrides, and default initialization that preserves existing values.

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• Sharing validated settings between workers
• Reacting to manual YAML configuration edits
• Initializing defaults while preserving existing values

Guide SQLite database design and performance tuning for applications. Covers concurrent reads and writes, indexes that speed up queries, full-text search, JSON processing, analytical queries, and versioned changes to database structure.

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• Investigating slow SQLite queries
• Reducing contention between database reads and writes
• Designing full-text search and JSON queries

Create, update, or review Bifrost feature documentation for Mintlify using MDX, a format combining Markdown and components. Research the interface and backend, validate configuration examples, and organize pages with screenshot placeholders and navigation entries.

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• Write documentation for a new Bifrost feature
• Update guides after interface or API changes
• Validate config.json examples against the schema

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.

中文简介正在准备中。当前显示英语简介。

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