Explore skills

把一条 AI 视频提示词从源模型(如 Sora 2)的写法风格转换为目标模型(如 Kling 3.0 / Wan 2.7 / Veo 3.1 等)的最佳实践写法。基于 110 条 10 场景 × 11 模型对照基准数据(prompts/data/cross-model-matrix.json),不是凭直觉重写,而是查表式 in-context learning。10 场景:产品 / 双人对话 / 物理动作 / 图生视频 / 多人会议 / 恐怖 / 自然延时 / 抽象 / 武侠 / 萌宠。用于"Sora 已 EOL 帮我把这条提示词改成 Veo"、"我有 Kling 提示词想跑 Wan"、"跨模型 A/B 测试"、"把英文 prompt 优化成 Kling 中文版"等触发场景。

An operating system for Threads growth, facilitating topic selection, drafting, analysis, prediction, review, and tracker refresh, all based on the user's own post history.

Expert data science covering machine learning, statistical modeling, experimentation, predictive analytics, and advanced analytics. Use when selecting ML algorithms, engineering features, designing A/B tests, evaluating model performance, or building predictive pipelines.

Expert analytics engineering covering data modeling, dbt development, data transformation, and semantic layer management. Use when building dbt models, designing star schemas, writing staging or mart SQL, configuring data tests, defining semantic-layer metrics, or optimizing warehouse query performance.

Expert business intelligence covering dashboard design, data visualization, reporting automation, and executive insights delivery. Use when designing dashboards, building KPI frameworks, automating scheduled reports, creating data stories for stakeholders, or optimizing BI tool performance.

Expert data analysis covering SQL querying, data visualization, statistical analysis, business reporting, and data storytelling. Use when writing SQL queries, building dashboards, performing cohort or funnel analysis, running hypothesis tests, or presenting data-driven recommendations to stakeholders.

Audit data quality across pipelines, warehouses, and operational stores. Use when designing a DQ program from scratch, defining DQ dimensions (completeness, accuracy, consistency, timeliness, validity, uniqueness) for a dataset, building rule-based checks (Great Expectations / dbt tests / Soda / custom), detecting schema drift, monitoring freshness SLAs, responding to a DQ incident, or auditing an

Provides expert-level database design with schema analysis, index optimization, and migration generation. Supports PostgreSQL, MySQL, MongoDB, and DynamoDB. Use when designing schemas, optimizing queries, planning migrations, or analyzing database performance.

Design, review, and validate Azure cloud architectures. Use when picking the right Azure compute (AKS / App Service / Container Apps / Functions / VMs / VMSS), data store (SQL DB / Cosmos / Postgres Flexible / Storage), networking (VNet / Private Endpoint / Front Door / Application Gateway), identity (Entra ID / Managed Identity / RBAC scopes), or applying the Azure Well-Architected Framework (Rel

Design relational database schemas from requirements with normalization, migration planning, ERD generation, RLS policies, index strategies, and type generation. Supports PostgreSQL, MySQL, and SQLite with Drizzle, Prisma, and Alembic migrations. Use when designing new features, reviewing schemas, or adding multi-tenancy.

This skill should be used when the user asks to "design REST APIs", "optimize database queries", "implement authentication", "build microservices", "review backend code", "set up GraphQL", "handle database migrations", or "load test APIs". Use for Node.js/Express/Fastify development, PostgreSQL optimization, API security, and backend architecture patterns.

This skill should be used when the user asks to "optimize SQL queries", "explore database schemas", "generate migration SQL", "analyze query performance", or "document database structure".