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Object

Checked
simhacker·vlatest·other·MIT

This skill allows you to manipulate and interact with objects in the environment, crucial for realistic simulations and gameplay control.

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 simhacker/moollm --skill object -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

simhacker

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 passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • 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 undeclared network calls: passed

    Makes no network calls.

    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.

  • 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 simhacker/moollm at 8f6d840b2f.

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

Scanned
1 file, 321 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 allows AI agents to interact with and manipulate objects in a virtual environment. It facilitates tasks such as identifying, grasping, moving, and placing objects based on textual instructions. The agent can understand object properties like size, shape, and material to perform actions effectively.

When to use it

  • Robotics simulations: To control a simulated robot arm for picking and placing items in a warehouse environment.
  • Virtual assistant tasks: To instruct an AI assistant to organize virtual objects on a desktop or within a 3D workspace.
  • Game development: To enable non-player characters (NPCs) to interact realistically with the game world's objects.
  • Educational applications: To create interactive learning experiences involving object manipulation and problem-solving.

Key capabilities

  • Object identification
  • Grasping
  • Movement
  • Placement
  • Understanding of object properties (size, shape, material)

Example prompts

  • "Pick up the red block and place it on top of the blue one."
  • "Move the sphere to the left side of the table."
  • "Identify all objects that are larger than 10cm."

Tips & gotchas

The skill's performance depends heavily on the accuracy of object recognition within the virtual environment. Ensure clear visual data and well-defined object models for optimal results.