'json schema' 검색 결과

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".

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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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프런트엔드와 백엔드 또는 서비스 간 API와 이벤트 명세를 먼저 정합니다. 타입을 생성하고 같은 명세로 테스트 데이터와 실제 응답을 검증해 병렬 개발 중 불일치를 줄입니다.

• 프런트엔드와 백엔드 병렬 개발
• 서비스 간 API와 이벤트 형식 통일
• 모의 응답과 운영 응답 비교

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.

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

onboarding workflow for creating datasets and applications in Viking AI Search. Supports one-time import from local files (JSON, JSONL, CSV) and MySQL databases, plus scheduled incremental sync for append-only JSONL files and MySQL. All sources are first exported to a bootstrap JSONL file; backend-driven schema inference handles detection, and optional background sync keeps the dataset up to date as new data arrives.

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🇺🇸 SEO & GEO Dual-Engine Playbook 2026 — Rank on Google AND get cited by AI search (ChatGPT, Perplexity, Claude, Gemini). Battle-tested from AFFiNE (60k GitHub stars in 24 months) and 150+ AI startup consultations. E-E-A-T writing voice system, keyword funnel strategy, JSON-LD schema templates, comparison page SOP, IndexNow setup, Generative Engine Optimization content patterns. **Optimized for dev tools / OSS / B2B SaaS. 2C products (education, apps, games): see 2c-adaptation guide in references/.** 🇨🇳 SEO & GEO 双引擎增长手册 —— 同时拿下 Google 排名和 AI 搜索引用（ChatGPT、Perplexity、Claude、文心一言）的完整方法论。AFFiNE 60k stars 与 150+ AI 创业公司咨询实战验证。E-E-A-T 写作声音系统、关键词漏斗、JSON-LD 结构化数据、竞品对比页 SOP、IndexNow 推送、生成式引擎优化内容模式。**默认适用于开发者工具 / 开源项目 / B2B SaaS，2C 产品（教育/应用/游戏）请参考 references/2c-adaptation.md。** 🇯🇵 SEO & GEO デュアルエンジングロースプレイブック — Google検索とAI検索（ChatGPT、Perplexity、Claude）の両方で評価される手法。AFFiNE 60k starsと150社以上のAIスタートアップコンサルティングで検証。E-E-A-Tライティング、キーワードファネル、Schema.org構造化データ、比較ページSOP。**デフォルトは開発者ツール／OSS／B2B SaaS向け。2C製品（教育・アプリ・ゲーム）はreferences/2c-adaptation.mdを参照。** 🇰🇷 SEO & GEO 듀얼 엔진 성장 플레이북 — 구글 검색과 AI 검색(ChatGPT, Perplexity, Claude) 양쪽 모두에서 인용되는 방법론. AFFiNE 60k 스타와 150+ AI 스타트업 컨설팅으로 검증. E-E-A-T 글쓰기, 키워드 퍼널, Schema.org 구조화 데이터, 비교 페이지 SOP. **기본값은 개발자 도구/OSS/B2B SaaS용. 2C 제품(교육·앱·게임)은 references/2c-adaptation.md 참조.** Triggers: "SEO" | "GEO" | "Generative Engine Optimization" | "AI search optimization" | "ChatGPT SEO" | "Perplexity SEO" | "Claude SEO" | "search optimization" | "content SEO" | "technical SEO" | "schema markup" | "JSON-LD" | "structured data" | "IndexNow" | "E-E-A-T" | "keyword strategy" | "keyword funnel" | "comparison page" | "programmatic SEO" | "SaaS SEO" | "搜索优化" | "AI 搜索" | "内容 SEO" | "GEO 优化" | "生成式引擎优化"

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Research-backed JSON Schema refresh workflow for updating existing schemas with validation checkpoints and cross-reference verification.

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