d1-drizzle-schema

jezweb/claude-skills · updated Apr 8, 2026

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$npx skills add https://github.com/jezweb/claude-skills --skill d1-drizzle-schema
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summary

Generate Drizzle ORM schemas for Cloudflare D1 with D1-specific SQLite patterns and constraints.

  • Handles D1 quirks: enforced foreign keys, no native BOOLEAN/DATETIME types, 100 bound parameter limit, and JSON stored as TEXT
  • Produces schema files, type exports, migration commands, and DATABASE_SCHEMA.md documentation
  • Includes bulk insert batching logic and D1 runtime query patterns for Workers
  • Reference guides cover D1 vs standard SQLite differences, column type patterns, and migra
skill.md

D1 Drizzle Schema

Generate correct Drizzle ORM schemas for Cloudflare D1. D1 is SQLite-based but has important differences that cause subtle bugs if you use standard SQLite patterns. This skill produces schemas that work correctly with D1's constraints.

Critical D1 Differences

Feature Standard SQLite D1
Foreign keys OFF by default Always ON (cannot disable)
Boolean type No No — use integer({ mode: 'boolean' })
Datetime type No No — use integer({ mode: 'timestamp' })
Max bound params ~999 100 (affects bulk inserts)
JSON support Extension Always available (json_extract, ->, ->>)
Concurrency Multi-writer Single-threaded (one query at a time)

Workflow

Step 1: Describe the Data Model

Gather requirements: what tables, what relationships, what needs indexing. If working from an existing description, infer the schema directly.

Step 2: Generate Drizzle Schema

Create schema files using D1-correct column patterns:

import { sqliteTable, text, integer, real, index, uniqueIndex } from 'drizzle-orm/sqlite-core'

export const users = sqliteTable('users', {
  // UUID primary key (preferred for D1)
  id: text('id').primaryKey().$defaultFn(() => crypto.randomUUID()),

  // Text fields
  name: text('name').notNull(),
  email: text('email').notNull(),

  // Enum (stored as TEXT, validated at schema level)
  role: text('role', { enum: ['admin', 'editor', 'viewer'] }).notNull().default('viewer'),

  // Boolean (D1 has no BOOL — stored as INTEGER 0/1)
  emailVerified: integer('email_verified', { mode: 'boolean' }).notNull().default(false),

  // Timestamp (D1 has no DATETIME — stored as unix seconds)
  createdAt: integer('created_at', { mode: 'timestamp' }).notNull().$defaultFn(() => new Date()),
  updatedAt: integer('updated_at', { mode: 'timestamp' }).notNull().$defaultFn(() => new Date()),

  // Typed JSON (stored as TEXT, Drizzle auto-serialises)
  preferences: text('preferences', { mode: 'json' }).$type<UserPreferences>(),

  // Foreign key (always enforced in D1)
  organisationId: text('organisation_id').references(() => organisations.id, { onDelete: 'cascade' }),
}, (table) => ({
  emailIdx: uniqueIndex('users_email_idx').on(table.email),
  orgIdx: index('users_org_idx').on(table.organisationId),
}))

See references/column-patterns.md for the full type reference.

Step 3: Add Relations

Drizzle relations are query builder helpers (separate from FK constraints):

import { relations } from 'drizzle-orm'

export const usersRelations = relations(users, ({ one, many }) => ({
  organisation: one(organisations, {
    fields: [users.organisationId],
    references: [organisations.id],
  }),
  posts: many(posts),
}))

Step 4: Export Types

export type User = typeof users.$inferSelect
export type NewUser = typeof users.$inferInsert

Step 5: Set Up Drizzle Config

Copy assets/drizzle-config-template.ts to drizzle.config.ts and update the schema path.

Step 6: Add Migration Scripts

Add to package.json:

{
  "db:generate": "drizzle-kit generate",
  "db:migrate:local": "wrangler d1 migrations apply DB --local",
  "db:migrate:remote": "wrangler d1 migrations apply DB --remote"
}

Always run on BOTH local AND remote before testing.

Step 7: Generate DATABASE_SCHEMA.md

Document the schema for future sessions:

  • Tables with columns, types, and constraints
  • Relationships and foreign keys
  • Indexes and their purpose
  • Migration workflow

Bulk Insert Pattern

D1 limits bound parameters to 100. Calculate batch size:

const BATCH_SIZE = Math.floor(100 / COLUMNS_PER_ROW)
for (let i = 0; i < rows.length; i += BATCH_SIZE) {
  await db.insert(table).values(rows.slice(i, i + BATCH_SIZE))
}

D1 Runtime Usage

import { drizzle } from 'drizzle-orm/d1'
import * as schema from './schema'

// In Worker fetch handler:
const db = drizzle(env.DB, { schema })

// Query patterns
const all = await db.select().from(schema.users).all()           // Array<User>
const one = await db.select().from(schema.users).where(eq(schema.users.id, id)).get()  // User | undefined
const count = await db.select({ count: sql`count(*)` }).from(schema.users).get()

Reference Files

When Read
D1 vs SQLite, JSON queries, limits
how to use d1-drizzle-schema

How to use d1-drizzle-schema on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/jezweb/claude-skills --skill d1-drizzle-schema

The skills CLI fetches d1-drizzle-schema from GitHub repository jezweb/claude-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/d1-drizzle-schema

Reload or restart Cursor to activate d1-drizzle-schema. Access the skill through slash commands (e.g., /d1-drizzle-schema) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.667 reviews
  • Dhruvi Jain· Dec 24, 2024

    d1-drizzle-schema reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Zara Shah· Dec 20, 2024

    Keeps context tight: d1-drizzle-schema is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Hana Li· Dec 16, 2024

    d1-drizzle-schema reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Henry Abbas· Dec 16, 2024

    Registry listing for d1-drizzle-schema matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Noah Gonzalez· Dec 8, 2024

    Registry listing for d1-drizzle-schema matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Aarav Desai· Dec 4, 2024

    Useful defaults in d1-drizzle-schema — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Fatima Choi· Nov 27, 2024

    Useful defaults in d1-drizzle-schema — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Fatima Farah· Nov 23, 2024

    Registry listing for d1-drizzle-schema matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Oshnikdeep· Nov 15, 2024

    I recommend d1-drizzle-schema for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Rahul Santra· Nov 11, 2024

    We added d1-drizzle-schema from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

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