'json schema' 검색 결과

Render a crouton collection schema (the field-definition JSON) into a human-readable field table + relationships sketch (HTML + PNG + a terse Markdown table), so a human can sign off on the DATA MODEL before any code is generated. Use when an agent drafts or changes a collection schema (before `crouton config` / `generate_collection`), or when asked to "review a schema", "show the data model", "check these fields".

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Detect, validate, and generate Schema.org structured data. JSON-LD format preferred. Use when user says "schema", "structured data", "rich results", "JSON-LD", or "markup".

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Automate Safari on macOS from the command line while retaining browser logins. Read pages, fill forms, save PDFs, inspect network activity, and return structured JSON results through the tools exposed by safari-mcp.

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• Read pages using Safari's existing login state
• Fill multiple form fields in one operation
• Save web pages as PDFs or screenshots

Design a business change log that records who changed what, when, and why. Get a focused recommendation first, then request empty templates in CSV, SQL table definitions, JSON Schema, or a Notion property mapping.

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• Designing a record of expense approvals
• Moving spreadsheet change logs into a structured register
• Preparing log fields for an audit review

Designs an audit document register to track required records, reporting periods, requests, receipt dates, reviewers, queries, and adjustments. Provides recommendations and, on request, empty templates in CSV, SQL, JSON Schema, or Notion mappings.

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• Preparing a year-end audit document checklist
• Designing a document request and receipt tracker
• Keeping audit queries and adjustments together

Generate an MCP server, a service exposing tools to AI agents, and a Power Platform custom connector for Copilot Studio. Outputs include connector definitions, authentication settings, request handling, individual tools, and deployment configuration.

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• Connect a Copilot Studio agent to an external API
• Create tools for customer search and analysis
• Generate connector files and authentication settings

Work with BigQuery to create datasets and tables, run SQL queries, ingest data, and manage processing jobs. The skill also covers connections to BigQuery ML and Gemini for machine learning and AI analysis.

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• Creating datasets and tables
• Analyzing data with SQL queries
• Ingesting data and managing processing jobs

Inspect database connections and table structures configured in DBX, run read-only queries with row and time limits, and generate schema documentation or DBML, a text format for describing database structures.

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• Explore tables and columns in a DBX database
• Check data with bounded read-only queries
• Generate database structure documentation

Create a Wren MDL project, a model layer for database queries, from an existing database. Discover tables and relationships, normalize column types, generate YAML files, and validate and build the project before indexing its schema.

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• Create a Wren project from an existing database
• Add selected schemas and tables as a new data source
• Define model relationships from database constraints

Update Bifrost Helm charts, the packages used to configure deployments, while keeping settings, schemas, templates, and documentation aligned. Check the published release and group changes into the next unreleased version.

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• Add Bifrost settings to the Helm chart
• Check configuration fields missing from the chart
• Combine changes into one unreleased version

Update the gh-aw-firewall version used by gh-aw, rebuild generated files, and review release notes and configuration schemas, which define valid settings. It guides related code and test updates while identifying follow-up work that remains.

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• Updating the firewall version used by gh-aw
• Reviewing release notes for integration changes
• Checking configuration schema differences

Add a new safe-output message type to gh-aw, connecting configuration validation, Go parsing, and JavaScript rendering. Follow the required updates through tests, exports, documentation, and generated action bundles so the message reaches workflow output.

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• Add a new safe-output message type to gh-aw
• Support custom templates with placeholders
• Test default and customized message output

Use when the user asks to "optimize meta tags", "write title tags / meta descriptions", "add Open Graph or Twitter cards", or "generate schema / JSON-LD" for FAQ, HowTo, Article, Product, or LocalBusiness rich-result candidates. Produces title/description options, an OG+Twitter block, and validated JSON-LD for the document head. Not for body copy — use content-writer; not for crawl/index technical issues — use technical-seo-checker. 标题优化/元描述/Schema标记/结构化数据

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Define a dataset's metadata profile — infer a Frictionless Table Schema from its data, add Data Package metadata (license, sources, keywords), and write it into datasets.json so the showcase renders a typed field table. Extend or customize via the L0-L3 profile ladder. Use when a registered dataset needs field types, constraints, or catalog metadata before publishing.

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Generate JSON Schema definitions for MCP tool input parameters. Creates well-documented, AI-consumable schemas with proper types, descriptions, and validation rules.

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Choose the right serialization format for .NET applications. Prefer schema-based formats (Protobuf, MessagePack) over reflection-based (Newtonsoft.Json). Use System.Text.Json with AOT source generators for JSON scenarios.

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Query UniProt's REST API (post-2022 endpoint at rest.uniprot.org) for protein sequences, annotations, GO terms, cross-references, ID mappings, and proteomes. Use when fetching UniProtKB entries, navigating the JSON schema, choosing between UniProtKB/UniRef/UniParc/Proteomes resources, deciding stream vs search endpoint for batch retrieval, running ID-mapping jobs with the async pattern, handling isoform suffixes, or filtering reviewed Swiss-Prot vs auto-annotated TrEMBL. Encodes the legacy URL migration (2022), the new JSON schema layout, and bulk-pull patterns.

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Generate complete SEO setup for local business websites — HTML head tags, JSON-LD LocalBusiness schema, robots.txt, sitemap.xml. Australian-optimised with +61 phone, ABN, suburb patterns. Use whenever the user wants SEO for a local business (tradesman, café, clinic, agency, retailer), needs JSON-LD structured data, asks for LocalBusiness schema, or wants meta tags / robots.txt / sitemap for a suburb-serving business.

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Format reference for Power BI Enhanced Report (PBIR) JSON schemas and patterns. Automatically invoke when the user asks about PBIR JSON structure, visual.json properties, PBIR expressions, objects vs visualContainerObjects, theme inheritance, conditional formatting patterns, extension measures, bookmarks, field references, filter formatting, query roles, PBIR page structure, report wallpaper, or any PBIR metadata format question.

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根据用户提供的优惠活动详细介绍文本，按照预定义的JSON Schema提取活动基本信息（如时间、银行、卡类型、支付方式、优惠力度、次数限制等），并应用特定的格式化规则和逻辑计算（如状态判断、次数统计）。

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Use when you need framework-agnostic MongoDB and non-relational database query guidance — document schema design, collection modeling, JSON Schema validation, indexes, aggregation pipelines, query performance, consistency trade-offs, transactions, and operational safety — without choosing Spring Boot, Quarkus, or Micronaut. This should trigger for requests such as Design MongoDB document schemas; Review MongoDB queries and indexes; Improve aggregation pipeline performance; Model non-relational data access patterns; Review NoSQL consistency and transaction trade-offs. Part of Plinth Toolkit

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Create dynamic schema-based forms using @delon/form (SF component). Use this skill when building complex forms with validation, conditional rendering, async data loading, custom widgets, and multi-step workflows. Ensures forms follow JSON Schema standards, integrate with Angular reactive forms, support internationalization, and maintain consistent validation patterns across the application.

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Analyze C++ build performance using vcperf.exe and ETL traces. Use this skill when the user wants to profile a build, understand compile bottlenecks, identify expensive headers or templates, generate JSON analysis reports, or interpret vcperf output. Covers tracing workflows, the /jsonAnalysis flag, reading the resulting JSON schema, and actionable remediation strategies for each bottleneck category.

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TypeScript-first schema validation and type inference. Use for validating API requests/responses, form data, env vars, configs, defining type-safe schemas with runtime validation, transforming data, generating JSON Schema for OpenAPI/AI, or encountering missing validation errors, type inference issues, validation error handling problems. Zero dependencies, compact core (~5kb gzipped; zod/mini ~1.9kb).

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