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convex-schema-validator凸模式验证器

Agent Skill

convex-schema-validator 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

3

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:convex-schema-validator(凸模式验证器)
来源仓库:https://github.com/waynesutton/convexskills
仓库路径:skills/convex-schema-validator
安装命令:
npx skills add https://github.com/waynesutton/convexskills --skill convex-schema-validator
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/waynesutton/convexskills --skill convex-schema-validator

简介

具有 Convex 索引、验证和迁移策略的类型安全数据库模式定义。

  • 支持 13 种以上验证器类型,包括字符串、数字、布尔值、文档引用、数组、对象、联合和可区分联合,以实现灵活的数据建模
  • 启用单字段和复合索引以及全文搜索索引以优化查询性能
  • Provides optional and nullable field patterns with clear migration paths for adding required fields and backfilling data
  • 包括具有完整 TypeScript 类型推断的复杂数据结构的嵌套对象、对象数组和记录类型

SKILL.md

Convex Schema Validator

Define and validate database schemas in Convex with proper typing, index configuration, optional fields, unions, and strategies for schema migrations.

Documentation Sources

Before implementing, do not assume; fetch the latest documentation:

Instructions

Basic Schema Definition

// convex/schema.ts
import { defineSchema, defineTable } from "convex/server";
import { v } from "convex/values";

export default defineSchema({
  users: defineTable({
    name: v.string(),
    email: v.string(),
    avatarUrl: v.optional(v.string()),
    createdAt: v.number(),
  }),

  tasks: defineTable({
    title: v.string(),
    description: v.optional(v.string()),
    completed: v.boolean(),
    userId: v.id("users"),
    priority: v.union(
      v.literal("low"),
      v.literal("medium"),
      v.literal("high")
    ),
  }),
});

Validator Types

ValidatorTypeScript TypeExample
v.string()string"hello"
v.number()number42, 3.14
v.boolean()booleantrue, false
v.null()nullnull
v.int64()bigint9007199254740993n
v.bytes()ArrayBufferBinary data
v.id("table")Id<"table">Document reference
v.array(v)T[][1, 2, 3]
v.object({}){...}{name: "..."}
v.optional(v)`T \undefined`Optional field
v.union(...)`T1 \T2`Multiple types
v.literal(x)"x"Exact value
v.any()anyAny value
v.record(k, v)Record<K, V>Dynamic keys

Index Configuration

export default defineSchema({
  messages: defineTable({
    channelId: v.id("channels"),
    authorId: v.id("users"),
    content: v.string(),
    sentAt: v.number(),
  })
    // Single field index
    .index("by_channel", ["channelId"])
    // Compound index
    .index("by_channel_and_author", ["channelId", "authorId"])
    // Index for sorting
    .index("by_channel_and_time", ["channelId", "sentAt"]),

  // Full-text search index
  articles: defineTable({
    title: v.string(),
    body: v.string(),
    category: v.string(),
  })
    .searchIndex("search_content", {
      searchField: "body",
      filterFields: ["category"],
    }),
});

Complex Types

export default defineSchema({
  // Nested objects
  profiles: defineTable({
    userId: v.id("users"),
    settings: v.object({
      theme: v.union(v.literal("light"), v.literal("dark")),
      notifications: v.object({
        email: v.boolean(),
        push: v.boolean(),
      }),
    }),
  }),

  // Arrays of objects
  orders: defineTable({
    customerId: v.id("users"),
    items: v.array(v.object({
      productId: v.id("products"),
      quantity: v.number(),
      price: v.number(),
    })),
    status: v.union(
      v.literal("pending"),
      v.literal("processing"),
      v.literal("shipped"),
      v.literal("delivered")
    ),
  }),

  // Record type for dynamic keys
  analytics: defineTable({
    date: v.string(),
    metrics: v.record(v.string(), v.number()),
  }),
});

Discriminated Unions

export default defineSchema({
  events: defineTable(
    v.union(
      v.object({
        type: v.literal("user_signup"),
        userId: v.id("users"),
        email: v.string(),
      }),
      v.object({
        type: v.literal("purchase"),
        userId: v.id("users"),
        orderId: v.id("orders"),
        amount: v.number(),
      }),
      v.object({
        type: v.literal("page_view"),
        sessionId: v.string(),
        path: v.string(),
      })
    )
  ).index("by_type", ["type"]),
});

Optional vs Nullable Fields

export default defineSchema({
  items: defineTable({
    // Optional: field may not exist
    description: v.optional(v.string()),

    // Nullable: field exists but can be null
    deletedAt: v.union(v.number(), v.null()),

    // Optional and nullable
    notes: v.optional(v.union(v.string(), v.null())),
  }),
});

Index Naming Convention

Always include all indexed fields in the index name:

export default defineSchema({
  posts: defineTable({
    authorId: v.id("users"),
    categoryId: v.id("categories"),
    publishedAt: v.number(),
    status: v.string(),
  })
    // Good: descriptive names
    .index("by_author", ["authorId"])
    .index("by_author_and_category", ["authorId", "categoryId"])
    .index("by_category_and_status", ["categoryId", "status"])
    .index("by_status_and_published", ["status", "publishedAt"]),
});

Schema Migration Strategies

Adding New Fields

// Before
users: defineTable({
  name: v.string(),
  email: v.string(),
})

// After - add as optional first
users: defineTable({
  name: v.string(),
  email: v.string(),
  avatarUrl: v.optional(v.string()), // New optional field
})

Backfilling Data

// convex/migrations.ts
import { internalMutation } from "./_generated/server";
import { v } from "convex/values";

export const backfillAvatars = internalMutation({
  args: {},
  returns: v.number(),
  handler: async (ctx) => {
    const users = await ctx.db
      .query("users")
      .filter((q) => q.eq(q.field("avatarUrl"), undefined))
      .take(100);

    for (const user of users) {
      await ctx.db.patch(user._id, {
        avatarUrl: `https://api.dicebear.com/7.x/initials/svg?seed=${user.name}`,
      });
    }

    return users.length;
  },
});

Making Optional Fields Required

// Step 1: Backfill all null values
// Step 2: Update schema to required
users: defineTable({
  name: v.string(),
  email: v.string(),
  avatarUrl: v.string(), // Now required after backfill
})

Examples

Complete E-commerce Schema

// convex/schema.ts
import { defineSchema, defineTable } from "convex/server";
import { v } from "convex/values";

export default defineSchema({
  users: defineTable({
    email: v.string(),
    name: v.string(),
    role: v.union(v.literal("customer"), v.literal("admin")),
    createdAt: v.number(),
  })
    .index("by_email", ["email"])
    .index("by_role", ["role"]),

  products: defineTable({
    name: v.string(),
    description: v.string(),
    price: v.number(),
    category: v.string(),
    inventory: v.number(),
    isActive: v.boolean(),
  })
    .index("by_category", ["category"])
    .index("by_active_and_category", ["isActive", "category"])
    .searchIndex("search_products", {
      searchField: "name",
      filterFields: ["category", "isActive"],
    }),

  orders: defineTable({
    userId: v.id("users"),
    items: v.array(v.object({
      productId: v.id("products"),
      quantity: v.number(),
      priceAtPurchase: v.number(),
    })),
    total: v.number(),
    status: v.union(
      v.literal("pending"),
      v.literal("paid"),
      v.literal("shipped"),
      v.literal("delivered"),
      v.literal("cancelled")
    ),
    shippingAddress: v.object({
      street: v.string(),
      city: v.string(),
      state: v.string(),
      zip: v.string(),
      country: v.string(),
    }),
    createdAt: v.number(),
    updatedAt: v.number(),
  })
    .index("by_user", ["userId"])
    .index("by_user_and_status", ["userId", "status"])
    .index("by_status", ["status"]),

  reviews: defineTable({
    productId: v.id("products"),
    userId: v.id("users"),
    rating: v.number(),
    comment: v.optional(v.string()),
    createdAt: v.number(),
  })
    .index("by_product", ["productId"])
    .index("by_user", ["userId"]),
});

Using Schema Types in Functions

// convex/products.ts
import { query, mutation } from "./_generated/server";
import { v } from "convex/values";
import { Doc, Id } from "./_generated/dataModel";

// Use Doc type for full documents
type Product = Doc<"products">;

// Use Id type for references
type ProductId = Id<"products">;

export const get = query({
  args: { productId: v.id("products") },
  returns: v.union(
    v.object({
      _id: v.id("products"),
      _creationTime: v.number(),
      name: v.string(),
      description: v.string(),
      price: v.number(),
      category: v.string(),
      inventory: v.number(),
      isActive: v.boolean(),
    }),
    v.null()
  ),
  handler: async (ctx, args): Promise<Product | null> => {
    return await ctx.db.get(args.productId);
  },
});

Best Practices

  • Never run npx convex deploy unless explicitly instructed
  • Never run any git commands unless explicitly instructed
  • Always define explicit schemas rather than relying on inference
  • Use descriptive index names that include all indexed fields
  • Start with optional fields when adding new columns
  • Use discriminated unions for polymorphic data
  • Validate data at the schema level, not just in functions
  • Plan index strategy based on query patterns

Common Pitfalls

  1. Missing indexes for queries - Every withIndex needs a corresponding schema index
  2. Wrong index field order - Fields must be queried in order defined
  3. Using v.any() excessively - Lose type safety benefits
  4. Not making new fields optional - Breaks existing data
  5. Forgetting system fields - _id and _creationTime are automatic

References

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