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Mongodb Mongoose

Listed
practicalswan·vlatest·database·MIT

Connects to MongoDB using Mongoose, enabling data retrieval, updates, and schema management via natural language requests.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add practicalswan/agent-skills --skill mongodb-mongoose -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

practicalswan

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • No undeclared network calls: failed

    Contacts 1 host that is neither well-known infrastructure nor declared in the skill's frontmatter: api.dicebear.com.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

    Hosts contacted

    api.dicebear.comundeclared

    What it found

    • mongodb-mongoose/scripts/seed-database.js:132contacts api.dicebear.com
      avatar: `https://api.dicebear.com/7.x/initials/svg?seed=${first}${last}`,

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned practicalswan/agent-skills at ff6d12f61e.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
ff6d12f61e
Manifest
mongodb-mongoose/SKILL.md
Scanned
7 files, 1,923 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill enables AI agents to interact with MongoDB databases using Mongoose, a MongoDB object modeling tool. It simplifies data access and manipulation by providing schema definitions and methods for common database operations like creating, reading, updating, and deleting documents. The agent can perform queries, manage collections, and handle data validation within a MongoDB environment.

When to use it

  • Data-driven applications: When your AI agent needs to store user profiles, product catalogs, or other structured information persistently.
  • Content management systems (CMS): To retrieve and update content stored in a MongoDB database powering a CMS.
  • Inventory tracking: For agents managing inventory levels or order details within a business application.
  • Analytics dashboards: To query and present data from a MongoDB-based analytics platform.

Key capabilities

  • Schema definition for MongoDB collections
  • Document creation and retrieval
  • Data validation using Mongoose schemas
  • Querying with various criteria (e.g., find by ID, filter by properties)
  • Update operations on existing documents
  • Deletion of documents from a collection

Example prompts

  • "Find all users with the age greater than 25."
  • "Create a new product document with name 'Laptop' and price 1200."
  • "Update the email address for user ID '64f...' to '[email protected]'."

Tips & gotchas

  • Requires access credentials (username/password or connection string) to connect to a MongoDB database.
  • Ensure Mongoose schema definitions are accurate and reflect the structure of your MongoDB collections.