MongoDB AI Skill: Aggregation Pipelines, Schemas & Indexes

Name: AI Skill for MongoDB
Brand: KissMySkills
Price: 19 USD
Availability: InStock

AI Skill for MongoDB

Turn Claude into a senior MongoDB engineer who writes your pipelines, indexes and schemas.

$19 this skill one payment yours forever

Prompt file instant downloadai-skill-for-mongodb.txt

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How it works

Ask it something hard.

📎 ai-skill-for-mongodb.txtLOADED ✓

This orders query filters on customerId and status, sorts by createdAt desc, limit 20, and explain shows COLLSCAN. Which index do I need?

CLAUDE · WITH THIS SKILL You get: the compound index definition ordered by the ESR rule (customerId, status, createdAt descending) as a ready createIndex command -> a one-line why explaining that equality fields come first and the sort field last so the planner avoids an in-memory sort -> an explain("executionStats") call to run afterwards with the two values to check (IXSCAN and totalDocsExamined close to nReturned) -> a caveat on build time and write cost on large collections with the Atlas Performance Advisor check -> the next action: run the index build and paste the executionStats if a sort stage remains.

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Questions before you buy? A person answers, usually the same day: hello@kissmyskills.com

// the file itself

Read it before you buy it.

The first lines of the file your AI will read, exactly as delivered. Nothing rewritten for the page.

// the skill your AI runs on

You are a senior MongoDB practitioner with schemas, pipelines, indexes and Atlas clusters behind you in production, shaping documents around the access pattern. You have been activated to write the query, propose the compound index and prove it with explain.

KissMySkills.com | Install: paste this whole file into Claude Projects (Project instructions), a custom GPT (Instructions), a Gemini Gem, or your AI's system prompt. Then just ask questions the way you normally would. You are a senior MongoDB practitioner embedded in the user's daily development and operations work, with schemas, pipelines, indexes and Atlas clusters behind you in production. You optimise for queries that use indexes, documents shaped for the access pattern, and safe operations on live data. Tone: direct, practical, step-by-step when needed. · Core objects: databases, collections, BSON documents, the _id field and ObjectId, embedded documents and arrays. · CRUD: insertMany, find with projection, sort, limit and skip, updateOne, updateMany, deleteMany, findOneAndUpdate, bulkWrite, upsert. · Query operators: $eq, $gt, $lt, $in, $and, $or, $exists, $regex, $elemMatch; update operators $set, $unset, $inc, $push, $pull, $addToSet, array filters. · Aggregation stages: $match, $project, $group, $sort, $limit, $unwind, $lookup, $addFields, $facet, $bucket, $replaceRoot, $merge, $out, plus $expr and accumulators. · Indexes: single field, compound (ESR rule: equality, sort, range), multikey, text, wildcard, 2dsphere, TTL, partial, unique. · explain() output: COLLSCAN versus IXSCAN, totalDocsExamined versus nReturned, executionStats. · Schema design: embedding versus referencing, bucket, outlier and extended reference patterns, unbounded arrays, the 16 MB document limit, JSON Schema validation. · Tools: mongosh, Compass (Aggregations tab, Explain Plan, Schema tab), Atlas (Atlas Search, Vector Search, Data Explorer, Performance Advisor, backups, triggers), mongodump and mongorestore. · Drivers: Node.js, PyMongo and Motor, Java, C#, Go; Mongoose; connection strings, pooling, read and write concerns. · Transactions: multi-document ACID transactions, and why single-document atomicity usually removes the need for them. · Deployment: replica sets (primary, secondaries, elections), sharding (shard key, chunks, balancer), Change Streams. · Security: SCRAM and x.509 authentication, role-based access control, Atlas network access lists, encryption in transit and at rest.

85 lines · .txt · instant download

// what's inside

What's inside this skill

Aggregation pipelines in mongosh or your driver, stage by stage
Compound index recommendations from explain() using the ESR rule
Document schema design with sample documents and JSON Schema validation
Batched updateMany and bulkWrite migrations with dry-run and backup steps

Backend developers, DevOps engineers and data engineers who query, model or operate MongoDB every day.

// two ways to get it

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// ask your assistant

Or let your AI set up this skill for you.

Go to kissmyskills.com/pages/connector and set up the "AI Skill for MongoDB" skill (handle: ai-skill-for-mongodb) for me

Paste it into Claude, ChatGPT, Claude Code, Cursor or Codex. Your AI walks you through connecting KissMySkills (about 3 minutes, 7-day free trial) and loads the skill. What your AI will read →

What you're actually buying

This Claude/ChatGPT skill works as a MongoDB AI pair programmer inside your daily database work: it writes find queries and aggregation pipelines in mongosh or your driver, designs document schemas with embed-versus-reference decisions and JSON Schema validation, turns a COLLSCAN in explain() into the right compound index using the ESR rule, and drafts batched updateMany or bulkWrite migrations with a dry-run count first.

It knows the query and update operators, every common aggregation stage, index types, Compass and Atlas panels (Aggregations, Explain Plan, Performance Advisor, Atlas Search), replica sets, sharding, transactions and driver patterns in Node.js, Python and Java. It does not connect to your cluster or run anything; it prepares the commands, the index definitions and the click path so you can execute them safely.

Works the same way in Claude, ChatGPT and Gemini. One purchase, download the file, install in under 2 minutes, then paste a sample document or a slow query and get MongoDB code back. Pairs with Oleg, Database Engineer, the persona skill; this one is the helper inside MongoDB.

// how to install Under 2 minutes

Four steps. Any AI chat.

01
Download the file
After checkout, the download link lands in your inbox. Save the .txt file anywhere on your device.
02
Open your AI chat
Any AI chat you already use: Claude, ChatGPT, Gemini, Grok, Copilot or another.
03
Paste the prompt
Open the .txt file, copy the prompt section and paste it into Claude or ChatGPT - or add it to a Project so it is always there.
04
Start working
Your AI is now configured as a specialist. Ask it anything inside its domain.

No technical knowledge required.

With Library there is nothing to download. Connect your AI once, then ask for any skill by name.

Setup guide → Library · $9/mo →

// faq

Questions about this product

What does the AI Skill for MongoDB do?+

It turns Claude or ChatGPT into a MongoDB AI assistant that writes queries and aggregation pipelines, designs and reviews document schemas, recommends indexes from explain() output, drafts migration scripts, writes driver code with proper connection handling and explains Atlas features like Atlas Search, Change Streams and backups.

Does it operate MongoDB for me?+

No. It does not connect to your cluster, run queries or build indexes. It writes the mongosh commands, the driver code and the Compass or Atlas click path, and you run them against your own MongoDB deployment after checking them.

Can the MongoDB skill help with schema design decisions?+

Yes. Describe your entities and how the application reads and writes them, and it proposes document shapes, explains when to embed and when to reference, applies patterns such as bucket, outlier and extended reference, and warns about unbounded arrays and the 16 MB document limit in MongoDB.

Which MongoDB versions and deployments does it cover?+

It covers MongoDB Atlas and self-managed replica sets and sharded clusters, and it asks for your version when a stage, operator or Atlas feature depends on it rather than assuming. It never invents operators or version numbers.