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Create output schemas, definitions of result fields and display settings, for an Apify Actor by inspecting its source code. Generate dataset and output files, add key-value storage definitions when needed, and update actor.json to reference them.
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Add or repair structured data, labels that help search engines understand page content. The skill selects suitable schema types, prepares JSON-LD code, and provides validation checks while distinguishing supported Google search features from retired ones.
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Detect and check structured data, machine-readable descriptions of page content, and generate suitable Schema.org JSON-LD snippets. Get a report of missing fields, syntax errors, and markup issues, plus code prepared for implementation.
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Create or fix structured data, code that describes page content to search engines. The skill selects suitable schema.org types, prepares JSON-LD markup, and provides placement instructions and validation checks for products, articles, FAQs, and other pages.
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Audit website structured data, the markup that describes businesses and content to machines. Detect errors and missing details, then generate JSON-LD code and a report with recommendations for improving AI readability.
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Create and audit JSON-LD, structured data that describes page content to search engines. Check JSON syntax, schema types, and required fields for articles, products, FAQs, and breadcrumbs, then guide validation for enhanced search results.
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Inspect JSON files or API responses with jq and produce a compact map of keys and value types. Use the result to understand nested data before writing queries or processing the full dataset.
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Plan a 360-degree or peer feedback process and create empty response templates from confirmed requirements. Produces consistent CSV, SQL, JSON Schema, or Notion property mappings while keeping visibility choices and scoring configuration separate.
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Audit, create, and fix structured data, the labels that help search systems understand web pages. Get JSON-LD code for articles, products, and other page types, plus validation findings and guidance on where to place it.
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Define the structure and available components for AI-generated JSON screens or videos. Build generation prompts, process incremental updates, connect values to application state, and validate or repair definitions before passing them to a renderer.
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Prepare a ChatGPT Apps submission JSON file by inspecting an MCP server, which exposes tools to AI agents. Generate app details, tool behavior justifications, and test cases, then report review findings and missing output schemas.
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Adjust how AI agents generate workflows in cc-wf-studio by reviewing node descriptions, examples, and misleading constraints. The skill guides minimal schema edits, format regeneration, and testing to address biased node choices.
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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。
通过正则表达式和语法规则约束本地语言模型的输出，生成符合指定格式的JSON、日期和固定分类标签，并用Python构建可重复使用的多阶段生成流程。
Turn work history, education, and skills into a complete resume for Reactive Resume. Gather missing facts through conversation and produce JSON, a structured data format, with the chosen template and layout.
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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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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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Review PostgreSQL code for database design, performance, and security issues. Get improvement suggestions covering JSONB, a binary JSON format, arrays, indexes, custom data types, functions, extensions, and rules that control access to individual rows.
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When the user wants to add or optimize structured data (Schema.org, JSON-LD). Also use when the user mentions "schema," "structured data," "JSON-LD," "rich results," "rich snippets," "Google rich snippets," "featured snippet schema," "add schema to page," "missing structured data," "schema validation error," "Schema Markup Validator," "Google Rich Results Test," "FAQ schema," "Article schema," "Organization schema," "JobPosting," "HowTo," "Event," "SoftwareApplication," "BreadcrumbList," "WebSite," "Recipe," "Product," or "Dataset." For SERP feature types and zero-click patterns, use serp-features. For AI search visibility strategy (not markup), use generative-engine-optimization. For HowTo step sections (placement, copy, vs FAQ), use howto-section-generator.
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Generate Schema.org structured data (JSON-LD) for any page type. Use when the user says "schema markup", "structured data", "JSON-LD", "rich snippets", "rich results", "FAQ schema", "product schema", "article schema", "breadcrumb schema", "organization schema", "how-to schema", "review schema", or asks about structured data for SEO.
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Create consistent records for evaluating AI agents, including task success, invalid tool calls, token use, and actual costs. Produce CSV tables, database definitions, and JSON validation schemas to support reproducible comparisons and checks for performance declines.
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Design tools that AI agents can understand and call correctly. Covers JSON Schema, a format for defining inputs, along with clear descriptions, input examples, validation, and error responses that help agents recover from failures.
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Define custom entities and relationships in cognee, a memory system for AI applications. This skill guides model design, identity matching, searchable fields, and troubleshooting when entities are duplicated or relationships are missing.
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Design and improve prompts for language models, then test their accuracy and consistency. Create reusable templates, JSON output schemas that define response structure, evaluation criteria, and test cases while considering token use and model differences.
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