Results for “schema”

Full SEO audit: Google Search Console data + URL Inspection API + PageSpeed Insights API + technical crawl + keyword research + metadata audit + schema markup audit + search intent analysis + Core Web Vitals monitoring. Feeds real GSC data and PageSpeed metrics into AI to surface quick wins, diagnose traffic drops, find content gaps, identify metadata mismatches, detect schema gaps, monitor page performance, and produce an actionable 30-day plan. Use this skill whenever the user asks about SEO, search rankings, organic traffic, Google Search Console, keyword performance, traffic drops, content gaps, search visibility, technical SEO, meta tags, schema markup, structured data, URL indexing, keyword research, indexing issues, page speed, performance, Core Web Vitals, LCP, INP, CLS, or Lighthouse scores. Also trigger on: "why is my traffic down", "what keywords am I ranking for", "improve my rankings", "check my search console", "SEO audit", "analyze my SEO", "technical SEO", "meta tags", "indexing issues", "crawl errors", "content strategy", "keyword cannibalization", "search intent", "schema markup", "structured data", "URL inspection", "page speed", "performance score", "core web vitals", "lighthouse", or any organic search question. If in doubt, trigger. This skill handles everything from quick GSC checks to deep technical audits with performance monitoring.

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Document and type a Sentry API endpoint. Write or fix @extend_schema decorators, specify response TypedDicts, type request parameters, correct type drift between the declared schema and the runtime response, and validate the generated spec. Use when asked to "document an endpoint", "add OpenAPI docs", "add/fix @extend_schema", "type an endpoint response", "fix the response type", "fix type drift", "reuse a response type", "split an overloaded endpoint", "specify the response schema", "add a TypedDict response", "migrate a legacy api-docs path", "fix a parameter type", or "make an endpoint public" / "promote an endpoint" (promotion is one section here).

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Zod (TypeScript-first スキーマバリデーションライブラリ) v4 リファレンス。 z.object / z.string / z.number / z.array / z.union / z.enum 等のスキーマ定義、 parse, safeParse, z.infer (型推論)、refine, transform, pipe、 default, optional, nullable、z.compile (AOT)・validate、z.toZod、 エラー処理、Zod 4 移行・Zod Mini (@zod/mini)。 createInsertSchema / createSelectSchema (drizzle-zod、Drizzle テーブルからのスキーマ生成) は別スキル drizzle。

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KiCad 10.0 (オープンソース EDA スイート) リファレンス。 Project Manager、Schematic Editor (Eeschema)、PCB Editor (PCBnew)、 Gerber Viewer (GerbView)、Drawing Sheet Editor (pl_editor)、 PCB Calculator、Command-Line Interface (kicad-cli)。 回路図設計、基板設計、ガーバー出力、フットプリント、シンボル、3D ビューア。

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Relocating a live, still-used table to another Postgres schema with every reference intact. Use when asked to move or rehome a table into a schema, or to pull a table out of public into a domain schema. NOT for retiring a table (use db-deprecate-table).

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Review database schema design and detect anti-patterns. Based on common RDB design knowledge and best practices. Supports Prisma, Drizzle, Rails, Django, Laravel, TypeORM, Sequelize, SQLAlchemy, and raw SQL (DDL). Use when the user says "review DB design", "check schema", "review table design", "review migration", "check for anti-patterns", "DB設計をレビューして", "スキーマを見て", "テーブル設計を確認して", "マイグレーションをレビューして", "アンチパターンがないか調べて", "この設計で問題ないか見て".

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Use when GitHub may have shipped a GraphQL schema update affecting timeline event unions (PullRequestTimelineItems / IssueTimelineItems), when the gh-timeline dispatcher fallback is hitting more than expected, before a gh-timeline release, or when the user requests phrases like "verify timeline coverage", "audit gh-timeline schema", "check for new timeline events", "GitHub schema changed". Walks through schema diff → patch → test update → live verification → optional fixture refresh, marking each spot where a human decision is required.

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Audits database schemas for naming conventions, type consistency, nullability patterns, and missing constraints. Provides violations report with recommended fixes. Use for "schema validation", "database linting", "schema standards", or "consistency checks".

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Plan a practical equipment register for tracking serial numbers, assignees, locations, purchase values, warranties, and returns. On request, create empty CSV templates, SQL table definitions, JSON Schema, or Notion mappings from a shared field list.

• Setting up a laptop and equipment register
• Planning equipment returns when employees leave
• Reviewing fields needed for an asset audit

Plan a simple daily attendance register covering check-in, check-out, hours, absences, and correction requests. When requested, generate empty templates in CSV, SQL, JSON Schema, or Notion mappings to prepare records for payroll input.

• Designing a daily check-in and check-out register
• Clarifying late arrival and half-day recording rules
• Creating empty attendance templates for payroll input

Plan a central board for internal announcements, with fields for authors, audiences, publication dates, expiry dates, and acknowledgements. On request, generate empty templates in CSV, SQL, JSON Schema, or a Notion property mapping.

• Organizing company news that gets lost in chat
• Preparing an announcement board template
• Defining publication, acknowledgement, and expiry steps

Plan a former employee register covering previous roles, departure dates, rehire eligibility, and future contact dates. Receive a simple workflow recommendation, with empty CSV templates, SQL table definitions, JSON Schema, or Notion mappings available on request.

• Planning a former employee register
• Preparing a template for rehire candidates
• Organizing fields for future contact dates

Design a role permission matrix showing which business areas each role should view or edit, including confidentiality levels. Get a review workflow and, on request, empty CSV templates, SQL table definitions, JSON Schema, or Notion mappings.

• Defining viewing and editing permissions by role
• Planning access rules for confidential records
• Preparing a quarterly access review template

Organize primary and backup administrators, two-factor authentication, shared logins, and access review dates for each system. Get a practical register design or request empty templates in CSV, SQL, JSON Schema, or a Notion property mapping.

• Reviewing administrator access each quarter
• Checking accounts left behind by former employees
• Creating an administrator register template

Structure an evidence-based comparison of shortlisted accounting packages using 57 fields for capabilities, costs, and evaluator judgments. Request empty templates in CSV, SQL DDL, JSON Schema, or Notion mapping while keeping the final decision with the business.

• Prepare a common comparison template for accounting packages
• Define shared tests for vendor demonstrations
• Organize quoted costs for first-year and three-year comparisons

Helps contributors develop and fix Airflow’s Java SDK for JVM tasks. Explains public API boundaries, JAR packaging, Python coordination, communication schema updates, and the test commands used to validate changes.

• Adding features or fixing bugs in the Java SDK
• Reviewing public API and internal implementation boundaries
• Investigating JAR discovery and JVM startup failures

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.

• Create a new resume through conversation
• Convert work history into Reactive Resume JSON
• Choose a resume template and section order

Generate database relationship diagrams from Entity Framework Core models, mappings, and migrations. Produce D2 diagram source showing tables, keys, relationships, and constraints, with display options for columns and grouping. The d2 CLI can render SVG or PNG images.

• Document an EF Core project's database structure
• Review primary keys and foreign key relationships
• Visualize owned types and many-to-many join tables

Design PostgreSQL tables around actual queries and data volumes. Choose data types, validation rules, and indexes, then plan large table partitioning, access rules for individual rows, and schema changes with migration and rollback considerations.

• Designing tables for users, orders, and related data
• Reviewing data types, constraints, and indexes
• Planning large tables and frequent update workloads

Guides Postgres query writing, schema design, and configuration reviews using Supabase's prioritized rules. Helps identify improvements in query performance, connection management, and row-level security, which controls access to individual rows.

• Review slow SQL queries and index usage
• Check table and schema designs
• Review connection pooling and scaling settings

Write complex SQL, improve slow queries, and design database schemas for transaction processing and analytics. Uses schema details and query execution plans to guide indexing, validate results, and assess performance with realistic data volumes.

• Investigate and improve slow analytical queries
• Design a database schema for a SaaS application
• Write customer retention and cohort analysis queries

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.

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

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.

• Extracting company or profile details into JSON
• Classifying text using a fixed set of labels
• Generating text that matches a specified pattern

Develop and review FastGPT APIs with consistent input and output checks, TypeScript types, and OpenAPI documentation. It guides the use of Zod schemas, definitions that describe and validate data, alongside permission checks and reusable structures.

• Adding a new FastGPT API route
• Changing API inputs or responses
• Reviewing API validation and documentation