Document modeling, aggregation pipeline, indexing strategy, change streams, and multi-document transactions.
npx skills add https://github.com/vibeeval/vibecosystem --skill mongodb-patterns
Document database design and query optimization for MongoDB.
// EMBED when: 1:1 or 1:few, data read together, child has no independent lifecycle
interface Order {
_id: ObjectId
customerId: ObjectId
status: 'pending' | 'paid' | 'shipped'
items: OrderItem[] // Embedded - always read with order
shippingAddress: Address // Embedded - 1:1
createdAt: Date
}
interface OrderItem {
productId: ObjectId
name: string // Denormalized - avoid join at read time
price: number // Snapshot at purchase time
quantity: number
}
// REFERENCE when: 1:many (unbounded), independent queries, shared across documents
interface Product {
_id: ObjectId
name: string
price: number
categoryId: ObjectId // Reference - category queried independently
reviews: never // DON'T embed - unbounded array
}
// Bucket pattern: group time-series data into fixed-size documents
interface SensorBucket {
_id: ObjectId
sensorId: string
startTime: Date
endTime: Date
count: number // Track bucket fullness
measurements: { // Embed up to 200 per bucket
timestamp: Date
value: number
}[]
}
// Compound index: field order matters (ESR rule)
// Equality → Sort → Range
db.orders.createIndex({
status: 1, // Equality: exact match filter
createdAt: -1, // Sort: avoid in-memory sort
total: 1 // Range: price > 100
})
// Partial index: only index documents matching filter (smaller index)
db.orders.createIndex(
{ customerId: 1, createdAt: -1 },
{ partialFilterExpression: { status: 'pending' } }
)
// Text index for search
db.products.createIndex({ name: 'text', description: 'text' })
// TTL index for auto-expiration
db.sessions.createIndex(
{ createdAt: 1 },
{ expireAfterSeconds: 86400 } // Auto-delete after 24h
)
// Wildcard index for dynamic schemas
db.events.createIndex({ 'metadata.$**': 1 })
// Sales analytics: top products by revenue per category
const pipeline = [
// Stage 1: Filter date range
{ $match: {
createdAt: { $gte: new Date('2025-01-01'), $lt: new Date('2025-02-01') },
status: 'paid'
}},
// Stage 2: Unwind embedded items array
{ $unwind: '$items' },
// Stage 3: Group by product
{ $group: {
_id: '$items.productId',
productName: { $first: '$items.name' },
totalRevenue: { $sum: { $multiply: ['$items.price', '$items.quantity'] } },
totalSold: { $sum: '$items.quantity' },
orderCount: { $addToSet: '$_id' }
}},
// Stage 4: Add computed fields
{ $addFields: {
orderCount: { $size: '$orderCount' },
avgOrderValue: { $divide: ['$totalRevenue', { $size: '$orderCount' }] }
}},
// Stage 5: Sort by revenue descending
{ $sort: { totalRevenue: -1 } },
// Stage 6: Limit to top 20
{ $limit: 20 },
// Stage 7: Lookup category details
{ $lookup: {
from: 'products',
localField: '_id',
foreignField: '_id',
pipeline: [{ $project: { categoryId: 1 } }],
as: 'product'
}}
]
const results = await db.orders.aggregate(pipeline).toArray()
async function watchOrderChanges(): Promise<void> {
const pipeline = [
{ $match: {
operationType: { $in: ['insert', 'update'] },
'fullDocument.status': 'paid'
}}
]
// resumeAfter enables resuming from last processed change (crash recovery)
const changeStream = db.orders.watch(pipeline, {
fullDocument: 'updateLookup', // Include full document on updates
resumeAfter: await getLastResumeToken()
})
changeStream.on('change', async (event) => {
try {
await processOrderPayment(event.fullDocument!)
await saveResumeToken(event._id) // Persist for crash recovery
} catch (err) {
console.error('Change stream processing failed:', err)
}
})
changeStream.on('error', (err) => {
console.error('Change stream error:', err)
// Reconnect with resume token
setTimeout(() => watchOrderChanges(), 5000)
})
}
async function transferFunds(
fromAccountId: string,
toAccountId: string,
amount: number
): Promise<void> {
const session = client.startSession()
try {
await session.withTransaction(async () => {
const from = await db.accounts.findOne(
{ _id: new ObjectId(fromAccountId) },
{ session }
)
if (!from || from.balance < amount) {
throw new Error('Insufficient funds')
}
await db.accounts.updateOne(
{ _id: new ObjectId(fromAccountId) },
{ $inc: { balance: -amount } },
{ session }
)
await db.accounts.updateOne(
{ _id: new ObjectId(toAccountId) },
{ $inc: { balance: amount } },
{ session }
)
await db.transactions.insertOne({
from: fromAccountId,
to: toAccountId,
amount,
createdAt: new Date()
}, { session })
})
} finally {
await session.endSession()
}
}
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Query NCBI Gene via E-utilities/Datasets API. Search by symbol/ID, retrieve gene info (RefSeqs, GO, locations, phenotypes), batch lookups, for gene annotation and functional analysis.
Take vibeeval/mongodb-patterns from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.