“json validation”的搜索结果

Build Vue 3 interfaces from JSON specifications, including AI-generated layouts. The skill covers component registration, named content areas, synchronized form values, conditional visibility, validation, actions, and connections to external state management.

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• Display AI-generated JSON interfaces in Vue 3
• Build forms with synchronized values and validation
• Switch visible content based on application state

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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• Creating structured data for articles and products
• Checking FAQ and breadcrumb structured data
• Finding JSON syntax errors and missing required fields

Turn json-render specifications into SolidJS interfaces. This skill guides component registration, connects inputs to application state, handles actions and validation, and helps troubleshoot how changing values update the screen, including streamed UI generation.

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• Build SolidJS interfaces from JSON specifications
• Connect form inputs to application state
• Troubleshoot values that fail to update the screen

Review JavaScript JSON parsing for malformed input and unexpected data structures. Add error handling and validate parsed data before use, helping prevent failures when reading API responses, browser storage, or user-provided content.

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• Reviewing JSON parsing in API response handling
• Handling malformed data from localStorage
• Validating data structures before accessing properties

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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• Check existing structured data for errors
• Generate markup for products, articles, or businesses
• Review deprecated schema types

结合应用中的实际显示位置和项目术语更新JSON翻译文件，检查缺失翻译及原文改动，保留现有结构、动态值占位符和复数语法，并汇总修改与验证结果供审查。

• 翻译新增界面文案
• 为应用增加支持语言
• 原文修改后复查译文

Convert SKILL.md files into SSL JSON, a structured format describing invocation conditions, workflow stages, and individual actions. Receive a validation report covering format errors, invalid references, and rejected outputs.

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• Converting skill documents into structured JSON
• Reviewing skill stages and individual actions
• Checking workflow references and transitions

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

Build json-render interfaces with 36 ready-made UI components, including forms, tables, and navigation. This skill guides component selection, connects definitions to React implementations, and explains custom components and input validation.

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• Add standard components to a json-render interface
• Build forms with input validation
• Combine ready-made and custom components

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.

中文简介正在准备中。当前显示英语简介。

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

Review custom dotnet new templates before publishing. Check required fields, parameter types and defaults, command name conflicts, and constraints, then receive findings grouped by severity with concrete fixes for errors and warnings.

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• Checking template.json before publishing
• Investigating templates missing after installation
• Reviewing parameter types and default values

Create, design, and validate agents for Microsoft 365 Copilot. The skill guides JSON configuration or TypeSpec definitions, a typed alternative, alongside local testing, enterprise requirements, and deployment planning with Microsoft 365 Agents Toolkit.

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• Build a prototype agent for Microsoft 365 Copilot
• Plan enterprise features and multilingual support
• Validate an existing agent's configuration

Build Svelte interfaces for json-render using 36 ready-made components. This skill guides component selection, connects component definitions to implementations, and explains form validation settings for apps using Svelte 5 and Tailwind CSS.

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• Add standard UI components to a Svelte app
• Build forms with configurable validation
• Prepare component definitions for server-side prompts

Turn an existing .NET project into a reusable dotnet new template while preserving its settings and conventions. Create parameters and conditional content, test generated projects, and prepare the packaging files needed for NuGet distribution.

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• Turn an existing project into a reusable template
• Add template parameters and conditional files
• Validate template installation and generated builds

Design PostgreSQL tables by choosing data types, validation rules, and indexes that match actual queries. The skill also guides JSONB usage, partitioning large tables, and planning schema changes with attention to read and write workloads.

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• Designing tables for users and orders
• Reviewing indexes against actual queries
• Choosing between relational columns and JSONB

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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• Add structured data to product pages
• Describe articles and FAQs for search engines
• Fix errors in existing structured data

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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• Designing inputs for an AI agent tool
• Improving tool descriptions and input examples
• Reviewing validation and error responses

Implement or modify GitButler’s but commands using its established structure. It covers typed arguments, input validation, execution, and human-readable, shell, or JSON output, while keeping operations usable from the terminal interface.

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• Add a new but command
• Define arguments for branches and commits
• Separate input validation from execution

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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• Add structured data to product or article pages
• Find and fix errors in existing markup
• Implement breadcrumb structured data

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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• Recording agent evaluation results in a shared format
• Comparing a candidate agent with a baseline
• Tracking actual cost per solved task

Translate selected FastGPT interface text files from Simplified Chinese into every supported target locale. Check product terminology and interface context, preserve JSON structure and placeholders, and validate the translated files for consistency.

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• Translating a selected interface text file into all supported locales
• Updating several translation files together
• Translating every namespace from completed Chinese source text

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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• Adding structured data to articles or product pages
• Investigating structured data errors in Search Console
• Auditing existing markup and prioritizing fixes

Create realistic sample data for testing, development, and demos. Specify fields, record counts, value ranges, and business rules, then receive CSV, JSON, SQL INSERT statements, or a Python generator script with validation and usage instructions.

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• Creating test data that follows business rules
• Preparing realistic sample data for demos
• Populating a test database

Prepare a structured JSON handoff for feature work, bringing together requirements, design decisions, key user journeys, tests, demo recordings, and pull request status. Clearly distinguish completed work from missing validation, publication steps, and other remaining tasks.

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• Preparing a final handoff for feature development
• Linking key user journeys to tests and demo recordings
• Reporting unpublished work and remaining validation