agentleFS
waynesuttonwaynesutton/markdown-site/.claude/schema-builder/SKILL.md

schema-builder

Skill628 starsChanged 7 months agoMITView on GitHub

Design and generate Convex database schemas with proper validation, indexes, and relationships. Use when creating schema.ts or modifying table definitions.

2 other projects use a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Document-Relational: Use flat documents with ID references, not deep nesting

    line 20
  2. Distinctive:

    Index Foreign Keys: Always index fields used in lookups (userId, teamId, etc.)

    line 21
  3. Distinctive:

    Limit Arrays: Only use arrays for small, bounded collections (<8192 items)

    line 22
  4. Very specific:

    Type Safety: Use strict validators with v.* types

    line 23

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Convex Schema Builder

Build well-structured Convex schemas following best practices for relationships, indexes, and validators.

When to Use

  • Creating a new convex/schema.ts file
  • Adding tables to existing schema
  • Designing data model relationships
  • Adding or optimizing indexes
  • Converting nested data to relational structure

Schema Design Principles

  1. Document-Relational: Use flat documents with ID references, not deep nesting
  2. Index Foreign Keys: Always index fields used in lookups (userId, teamId, etc.)
  3. Limit Arrays: Only use arrays for small, bounded collections (<8192 items)
  4. Type Safety: Use strict validators with v.* types

Schema Template

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

export default defineSchema({
  tableName: defineTable({
    field: v.string(),
    optional: v.optional(v.number()),
    userId: v.id("users"),
    status: v.union(
      v.literal("active"),
      v.literal("pending"),
      v.literal("archived")
    ),
    createdAt: v.number(),
    updatedAt: v.optional(v.number()),
  })
    .index("by_user", ["userId"])
    .index("by_user_and_status", ["userId", "status"])
    .index("by_created", ["createdAt"]),
});

Common Patterns

One-to-Many Relationship

export 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"]),
});

Many-to-Many with Junction Table

export 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"]),
});

Hierarchical Data

export default defineSchema({
  comments: defineTable({
    postId: v.id("posts"),
    parentId: v.optional(v.id("comments")),
    userId: v.id("users"),
    text: v.string(),
  })
    .index("by_post", ["postId"])
    .index("by_parent", ["parentId"]),
});

Validator Reference

v.string()
v.number()
v.boolean()
v.null()
v.id("tableName")
v.optional(v.string())
v.union(v.literal("a"), v.literal("b"))
v.object({ key: v.string(), nested: v.number() })
v.array(v.string())
v.record(v.string(), v.boolean())
v.any()

Index Strategy

  1. Single-field indexes: For simple lookups (by_user: ["userId"])
  2. Compound indexes: For filtered queries (by_user_and_status: ["userId", "status"])
  3. Remove redundant: by_a_and_b usually covers by_a

Checklist

  • All foreign keys have indexes
  • Common query patterns have compound indexes
  • Arrays are small and bounded (or converted to relations)
  • All fields have proper validators
  • Enums use v.union(v.literal(...)) pattern
  • Timestamps use v.number() (milliseconds since epoch)

Source: https://github.com/get-convex/convex-agent-plugins

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.