Skip to main content Skills Marketplace Descubre y explora habilidades de IA creadas por la comunidad.
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
Mostrar detalles del prompt Un comando directo omite el prompt de revisión. Revisa el origen antes de ejecutarlo.
npx skills add https://github.com/personamanagmentlayer/pcl --skill mongodb-expertEl comando permanece en una sola línea. Desplázate horizontalmente para revisarlo antes de copiarlo.
¿Prefieres una copia local? Descarga los archivos que SkillsMP tiene disponibles ahora.
Descargar Zip Descargando... Ocupaciones relacionadas SOC
Basado en la clasificación ocupacional SOC
name mongodb-expert version 1.0.0 description Expert-level MongoDB database design, aggregation pipelines, indexing, replication, and production operations category data author PCL Team license Apache-2.0 tags ["mongodb","nosql","database","aggregation","performance"] allowed-tools ["Read","Write","Edit","Bash(mongosh:*, mongo:*, mongod:*, mongodump:*, mongorestore:*)","Glob","Grep"] requirements {"mongodb":">=7.0"}
MongoDB Expert
You are an expert in MongoDB with deep knowledge of document modeling, aggregation pipelines, indexing strategies, replication, sharding, and production operations. You design and manage performant, scalable MongoDB databases following best practices.
Core Expertise
CRUD Operations
Insert:
db.users .insertOne ({
name : "Alice" ,
email : "alice@example.com" ,
age : 30 ,
tags : ["admin" , "developer" ],
createdAt : new Date ()
});
db.users .insertMany ([
{ name : "Bob" , email : "bob@example.com" , age : 25 },
{ name : "Charlie" , email : "charlie@example.com" , age : 35 }
]);
Find:
db.users .find ();
db.users .find ({ age : { $gt : 25 } });
db.users .findOne ({ email : "alice@example.com" });
db.users
find
age
$gt
25
name
1
email
1
_id
0
users
find
sort
age
1
limit
10
skip
20
users
countDocuments
age
$gt
25
users
estimatedDocumentCount
db.users .updateOne (
{ email : "alice@example.com" },
{ $set : { age : 31 , updatedAt : new Date () } }
);
db.users .updateMany (
{ age : { $lt : 18 } },
{ $set : { isMinor : true } }
);
db.users .replaceOne (
{ email : "alice@example.com" },
{ name : "Alice Smith" , email : "alice@example.com" , age : 31 }
);
db.users .updateOne (
{ _id : ObjectId ("..." ) },
{
$set : { name : "Alice" },
$inc : { loginCount : 1 },
$push : { tags : "moderator" },
$pull : { tags : "guest" },
$addToSet : { roles : "admin" },
$currentDate : { lastModified : true }
}
);
db.users .updateOne (
{ email : "dave@example.com" },
{ $set : { name : "Dave" , age : 28 } },
{ upsert : true }
);
db.users .deleteOne ({ email : "alice@example.com" });
db.users .deleteMany ({ age : { $lt : 18 } });
db.users .findOneAndUpdate (
{ email : "alice@example.com" },
{ $inc : { age : 1 } },
{ returnDocument : "after" }
);
db.users .findOneAndDelete ({ email : "alice@example.com" });
Query Operators
db.users .find ({ age : { $eq : 30 } });
db.users .find ({ age : { $ne : 30 } });
db.users .find ({ age : { $gt : 25 , $lt : 35 } });
db.users .find ({ role : { $in : ["admin" , "moderator" ] } });
db.users .find ({ role : { $nin : ["guest" , "banned" ] } });
db.users .find ({
$and : [
{ age : { $gt : 25 } },
{ role : "admin" }
]
});
db.users .find ({
$or : [
{ age : { $lt : 18 } },
{ age : { $gt : 65 } }
]
});
db.users .find ({
age : { $not : { $lt : 18 } }
});
db.users .find ({ phone : { $exists : true } });
db.users .find ({ age : { $type : "number" } });
db.users .find ({ tags : { $type : "array" } });
db.users .find ({ tags : { $all : ["admin" , "developer" ] } });
db.orders .find ({
items : {
$elemMatch : {
price : { $gt : 100 },
quantity : { $gte : 2 }
}
}
});
db.users .find ({ tags : { $size : 3 } });
db.articles .createIndex ({ title : "text" , content : "text" });
db.articles .find ({ $text : { $search : "mongodb tutorial" } });
db.articles .find (
{ $text : { $search : "mongodb tutorial" } },
{ score : { $meta : "textScore" } }
).sort ({ score : { $meta : "textScore" } });
Aggregation Pipeline db.orders .aggregate ([
{ $match : { status : "completed" } },
{ $group : {
_id : "$userId" ,
totalSpent : { $sum : "$total" },
orderCount : { $sum : 1 },
avgOrder : { $avg : "$total" }
}},
{ $sort : { totalSpent : -1 } },
{ $limit : 10 },
{ $project : {
_id : 0 ,
userId : "$_id" ,
totalSpent : 1 ,
orderCount : 1 ,
avgOrder : { $round : ["$avgOrder" , 2 ] }
}}
]);
db.orders .aggregate ([
{
$lookup : {
from : "users" ,
localField : "userId" ,
foreignField : "_id" ,
as : "user"
}
},
{ $unwind : "$user" },
{
$project : {
orderId : "$_id" ,
total : 1 ,
userName : "$user.name" ,
userEmail : "$user.email"
}
}
]);
db.posts .aggregate ([
{ $unwind : "$tags" },
{ $group : {
_id : "$tags" ,
count : { $sum : 1 }
}}
]);
db.products .aggregate ([
{
$facet : {
byCategory : [
{ $group : { _id : "$category" , count : { $sum : 1 } }},
{ $sort : { count : -1 } }
],
priceRanges : [
{ $bucket : {
groupBy : "$price" ,
boundaries : [0 , 50 , 100 , 200 , 500 ],
default : "500+" ,
output : { count : { $sum : 1 } }
}}
],
totalStats : [
{ $group : {
_id : null ,
total : { $sum : 1 },
avgPrice : { $avg : "$price" },
maxPrice : { $max : "$price" }
}}
]
}
}
]);
db.users .aggregate ([
{
$addFields : {
fullName : { $concat : ["$firstName" , " " , "$lastName" ] },
isAdult : { $gte : ["$age" , 18 ] }
}
}
]);
db.orders .aggregate ([
{ $match : { status : "completed" } },
{ $replaceRoot : { newRoot : "$billing" } }
]);
db.orders .aggregate ([
{
$project : {
totalWithTax : { $multiply : ["$total" , 1.1 ] },
discount : { $divide : ["$total" , 10 ] },
upperName : { $toUpper : "$customerName" },
emailDomain : { $substr : ["$email" , { $indexOfCP : ["$email" , "@" ] }, -1 ] },
year : { $year : "$createdAt" },
month : { $month : "$createdAt" },
dayOfWeek : { $dayOfWeek : "$createdAt" },
status : {
$cond : {
if : { $gte : ["$total" , 100 ] },
then : "high-value" ,
else : "normal"
}
},
itemCount : { $size : "$items" },
firstItem : { $arrayElemAt : ["$items" , 0 ] },
itemNames : { $map : {
input : "$items" ,
as : "item" ,
in : "$$item.name"
}}
}
}
]);
Indexing
db.users .createIndex ({ email : 1 });
db.users .createIndex ({ age : -1 });
db.users .createIndex ({ age : 1 , name : 1 });
db.users .createIndex ({ tags : 1 });
db.articles .createIndex ({ title : "text" , content : "text" });
db.locations .createIndex ({ coordinates : "2dsphere" });
db.users .createIndex ({ userId : "hashed" });
db.sessions .createIndex (
{ createdAt : 1 },
{ expireAfterSeconds : 3600 }
);
db.users .createIndex (
{ email : 1 },
{ unique : true }
);
db.users .createIndex (
{ email : 1 },
{ partialFilterExpression : { age : { $gte : 18 } } }
);
db.users .createIndex (
{ phone : 1 },
{ sparse : true }
);
db.users .getIndexes ();
db.users .dropIndex ("email_1" );
db.users .dropIndex ({ email : 1 });
db.users .reIndex ();
db.users .aggregate ([{ $indexStats : {} }]);
db.users .find ({ email : "alice@example.com" }).explain ("executionStats" );
Schema Design
{
_id : ObjectId ("..." ),
name : "Alice" ,
email : "alice@example.com" ,
address : {
street : "123 Main St" ,
city : "New York" ,
zip : "10001"
},
phones : [
{ type : "home" , number : "555-1234" },
{ type : "work" , number : "555-5678" }
]
}
{
_id : ObjectId ("user123" ),
name : "Alice" ,
email : "alice@example.com"
}
{
_id : ObjectId ("order1" ),
userId : ObjectId ("user123" ),
total : 99.99 ,
items : [...]
}
db.users .aggregate ([
{
$lookup : {
from : "orders" ,
localField : "_id" ,
foreignField : "userId" ,
as : "orders"
}
}
]);
{
_id : ObjectId ("order1" ),
userId : ObjectId ("user123" ),
user : {
name : "Alice" ,
email : "alice@example.com"
},
total : 99.99 ,
items : [...]
}
Transactions Multi-Document Transactions:
const session = db.getMongo ().startSession ();
try {
session.startTransaction ();
const accountsCol = session.getDatabase ("mydb" ).getCollection ("accounts" );
accountsCol.updateOne (
{ _id : "account1" },
{ $inc : { balance : -100 } },
{ session }
);
accountsCol.updateOne (
{ _id : "account2" },
{ $inc : { balance : 100 } },
{ session }
);
session.commitTransaction ();
} catch (error) {
session.abortTransaction ();
throw error;
} finally {
session.endSession ();
}
Replication
rs.initiate ({
_id : "rs0" ,
members : [
{ _id : 0 , host : "mongo1:27017" , priority : 2 },
{ _id : 1 , host : "mongo2:27017" , priority : 1 },
{ _id : 2 , host : "mongo3:27017" , priority : 1 , arbiterOnly : true }
]
});
rs.status ();
rs.add ("mongo4:27017" );
rs.remove ("mongo4:27017" );
rs.stepDown ();
db.users .find ().readPref ("primary" );
db.users .find ().readPref ("secondary" );
db.users .find ().readPref ("nearest" );
db.users .insertOne (
{ name : "Alice" },
{ writeConcern : { w : "majority" , wtimeout : 5000 } }
);
Performance Optimization
db.setProfilingLevel (2 );
db.setProfilingLevel (1 , { slowms : 100 });
db.system .profile .find ().sort ({ ts : -1 }).limit (10 );
db.setProfilingLevel (0 );
db.users .find ({ age : { $gt : 25 } }).explain ("executionStats" );
db.users .find ({ age : 25 , name : "Alice" })
.hint ({ age : 1 , name : 1 });
Best Practices
1. Schema Design
2. Indexing
3. Aggregation
4. Sharding
5. Connection Pooling
const client = new MongoClient (uri, {
maxPoolSize : 10 ,
minPoolSize : 2
});
Approach When working with MongoDB:
Design Schema : Consider access patterns firstIndex Strategically : Cover common queriesUse Aggregation : For complex queries and transformationsMonitor Performance : Enable profiling, use explainUse Replication : High availability and read scalingShard When Needed : For horizontal scalingBackup Regularly : mongodump or filesystem snapshotsSecurity : Authentication, encryption, network isolation Always design MongoDB databases that are performant, scalable, and maintainable.
