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Society Of Mind

Listed
simhacker·vlatest·other·MIT

Simhacker’s “Society of Mind” skill simulates complex cognitive processes, offering insights into how ideas connect and evolve for richer conversations.

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 simhacker/moollm --skill society-of-mind -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 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.

  • Declares what it does: failed

    No SKILL.md was found in the skill's directory.

    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.

Commit
8f6d840b2f
Manifest
skills/society-of-mind/SKILL.md
Scanned
0 files
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 an AI agent to reason about and simulate interactions between multiple "agents," each with their own goals and beliefs, inspired by Marvin Minsky's Society of Mind theory. It can model complex behaviors arising from the interaction of simple agents, allowing for exploration of emergent properties and system-level understanding. The skill facilitates analyzing scenarios where individual motivations lead to unexpected collective outcomes.

When to use it

  • Simulating group dynamics: Model how a team might react to a new policy or change in leadership by representing each member as an agent.
  • Understanding market behavior: Simulate the actions of buyers and sellers to predict price fluctuations based on individual decision-making processes.
  • Exploring social phenomena: Analyze how rumors spread through a population by representing individuals with varying levels of trust and susceptibility.
  • Designing complex systems: Prototype and test the interactions within a system (like traffic flow or resource allocation) before implementation.

Key capabilities

  • Agent creation and definition: Define agents with specific goals, beliefs, and actions.
  • Interaction modeling: Simulate communication and influence between agents.
  • Emergent behavior analysis: Identify unexpected outcomes arising from agent interactions.
  • Scenario exploration: Test different initial conditions and observe the resulting system-level changes.

Example prompts

  • "Simulate a group of five agents, each wanting to maximize their own profit in a marketplace."
  • "Model how rumors spread through a network of 10 agents with varying levels of trust."
  • “Create two agents: one representing a customer and the other a salesperson. Simulate a negotiation.”

Tips & gotchas

The skill's effectiveness depends on clearly defining agent goals and behaviors; vague or conflicting objectives can lead to unpredictable results. Start with simple scenarios and gradually increase complexity as you become more familiar with the skill’s capabilities.