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Get Started Free →Design and generate Convex database schemas with proper validation, indexes, and relationships. Use when creating schema.ts or modifying table definitions.
.claude/skills/kunanonj-cursor-plugin-convex-schema-builder/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-20 | ✗→✓ | ▲ Improved | 50% | 0% |
| case-01 | ✓→✓ | = Same ✓ | 109% | 0% |
| case-02 | ✓→✓ | = Same ✓ | 84% | 0% |
| case-03 | ✓→✓ | = Same ✓ | 71% | 0% |
| case-04 | ✓→✓ | = Same ✓ | 29% | 0% |
Build well-structured Convex schemas following best practices for relationships, indexes, and validators.
convex/schema.ts filev.* typestypescriptimport { defineSchema, defineTable } from "convex/server"; import { v } from "convex/values"; export default defineSchema({ tableName: defineTable({ // Required fields field: v.string(), // Optional fields optional: v.optional(v.number()), // Relations (use IDs) userId: v.id("users"), // Enums with union + literal status: v.union( v.literal("active"), v.literal("pending"), v.literal("archived") ), // Timestamps createdAt: v.number(), updatedAt: v.optional(v.number()), }) // Index for queries by this field .index("by_user", ["userId"]) // Compound index for common query patterns .index("by_user_and_status", ["userId", "status"]) // Index for time-based queries .index("by_created", ["createdAt"]), });
typescriptexport default defineSchema({ users: defineTable({ name: v.string(), email: v.string(), }).index("by_email", ["email"]), posts: defineTable({ userId: v.id("users"), title: v.string(), content: v.string(), }).index("by_user", ["userId"]), });
typescriptexport default defineSchema({ users: defineTable({ name: v.string(), }), projects: defineTable({ name: v.string(), }), projectMembers: defineTable({ userId: v.id("users"), projectId: v.id("projects"), role: v.union(v.literal("owner"), v.literal("member")), }) .index("by_user", ["userId"]) .index("by_project", ["projectId"]) .index("by_project_and_user", ["projectId", "userId"]), });
typescriptexport default defineSchema({ comments: defineTable({ postId: v.id("posts"), parentId: v.optional(v.id("comments")), // null for top-level userId: v.id("users"), text: v.string(), }) .index("by_post", ["postId"]) .index("by_parent", ["parentId"]), });
typescriptexport default defineSchema({ users: defineTable({ name: v.string(), // Small, bounded collections are fine roles: v.array(v.union( v.literal("admin"), v.literal("editor"), v.literal("viewer") )), tags: v.array(v.string()), // e.g., max 10 tags }), });
typescript// Primitives v.string() v.number() v.boolean() v.null() v.id("tableName") // Optional v.optional(v.string()) // Union types (enums) v.union(v.literal("a"), v.literal("b")) // Objects v.object({ key: v.string(), nested: v.number(), }) // Arrays v.array(v.string()) // Records (arbitrary keys) v.record(v.string(), v.boolean()) // Any (avoid if possible) v.any()
by_user: ["userId"]by_email: ["email"]by_user_and_status: ["userId", "status"]by_team_and_created: ["teamId", "createdAt"]by_a_and_b usually covers by_av.union(v.literal(...)) patternv.number() (milliseconds since epoch)If converting from nested structures:
Before:
typescriptusers: defineTable({ posts: v.array(v.object({ title: v.string(), comments: v.array(v.object({ text: v.string() })), })), })
After:
typescriptusers: defineTable({ name: v.string(), }), posts: defineTable({ userId: v.id("users"), title: v.string(), }).index("by_user", ["userId"]), comments: defineTable({ postId: v.id("posts"), text: v.string(), }).index("by_post", ["postId"]),
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | pass→pass | 5,692 | 4,973 | -13% | 1 | 1 | 0% | 1,175 | 2,458 | +109% | 0 | 0 | — |
case-02 | pass→pass | 6,967 | 6,161 | -12% | 1 | 1 | 0% | 1,447 | 2,669 | +84% | 0 | 0 | — |
case-03 | pass→pass | 9,555 | 9,810 | +3% | 1 | 1 | 0% | 2,118 | 3,631 | +71% | 0 | 0 | — |
case-04 | pass→pass | 8,715 | 4,982 | -43% | 1 | 1 | 0% | 1,871 | 2,418 | +29% | 0 | 0 | — |
case-05 | pass→pass | 10,283 | 7,988 | -22% | 1 | 1 | 0% | 2,287 | 3,216 | +41% | 0 | 0 | — |
case-06 | pass→pass | 4,099 | 3,605 | -12% | 1 | 1 | 0% | 879 | 1,932 | +120% | 0 | 0 | — |
case-07 | pass→pass | 6,066 | 5,409 | -11% | 1 | 1 | 0% | 1,210 | 2,324 | +92% | 0 | 0 | — |
case-08 | pass→pass | 13,338 | 9,172 | -31% | 1 | 1 | 0% | 2,613 | 3,087 | +18% | 0 | 0 | — |
case-09 | pass→pass | 6,414 | 3,149 | -51% | 1 | 1 | 0% | 1,227 | 2,005 | +63% | 0 | 0 | — |
case-10 | pass→pass | 11,938 | 5,621 | -53% | 1 | 1 | 0% | 2,056 | 2,248 | +9% | 0 | 0 | — |
case-11 | pass→pass | 9,050 | 6,172 | -32% | 1 | 1 | 0% | 1,889 | 2,571 | +36% | 0 | 0 | — |
case-12 | pass→pass | 8,005 | 6,250 | -22% | 1 | 1 | 0% | 1,554 | 2,600 | +67% | 0 | 0 | — |
case-13 | pass→pass | 10,696 | 8,208 | -23% | 1 | 1 | 0% | 1,984 | 2,849 | +44% | 0 | 0 | — |
case-14 | pass→pass | 12,042 | 8,559 | -29% | 1 | 1 | 0% | 2,236 | 3,012 | +35% | 0 | 0 | — |
case-15 | pass→pass | 3,907 | 1,967 | -50% | 1 | 1 | 0% | 669 | 1,709 | +155% | 0 | 0 | — |
case-16 | pass→pass | 5,133 | 3,259 | -37% | 1 | 1 | 0% | 1,040 | 2,070 | +99% | 0 | 0 | — |
case-17 | pass→pass | 2,601 | 2,066 | -21% | 1 | 1 | 0% | 401 | 1,737 | +333% | 0 | 0 | — |
case-18 | pass→pass | 7,098 | 3,117 | -56% | 1 | 1 | 0% | 1,499 | 1,991 | +33% | 0 | 0 | — |
case-19 | pass→pass | 5,000 | 4,365 | -13% | 1 | 1 | 0% | 974 | 2,072 | +113% | 0 | 0 | — |
case-20 | fail→pass | 12,258 | 10,990 | -10% | 1 | 1 | 0% | 2,265 | 3,391 | +50% | 0 | 0 | — |
case-21 | pass→pass | 9,811 | 6,982 | -29% | 1 | 1 | 0% | 2,107 | 2,814 | +34% | 0 | 0 | — |
case-22 | pass→pass | 6,860 | 5,644 | -18% | 1 | 1 | 0% | 1,402 | 2,568 | +83% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +5 percentage points is the difference between those two pass rates over the 22 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.