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Agentation Self Driving

Checked
benjitaylor·vlatest·productivity

Agentation Self Driving automates complex workflows by intelligently routing tasks to the best AI agents, boosting efficiency and productivity.

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 benjitaylor/agentation --skill agentation-self-driving -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

benjitaylor

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 benjitaylor/agentation at 0e3236eb1a.

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

Commit
0e3236eb1a
Manifest
skills/agentation-self-driving/SKILL.md
Scanned
2 files, 241 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

The agentation-self-driving skill enables AI agents to autonomously navigate and interact with environments, making decisions based on real-time data without direct human input. It includes features for pathfinding, obstacle detection, and adaptive behavior in dynamic settings.

When to use it

  • Simulating autonomous vehicles in a virtual environment for testing purposes.
  • Creating AI-driven characters in games that can move and react independently.
  • Developing robotic systems that need to operate in unpredictable physical spaces.
  • Training AI agents to perform complex navigation tasks in real-world applications like delivery drones or warehouse automation.

Key capabilities

  • Real-time pathfinding and obstacle avoidance
  • Adaptive decision-making based on environmental changes
  • Integration with sensor data for autonomous navigation

Example prompts

  • "Navigate through a maze while avoiding obstacles."
  • "Simulate an autonomous car driving in a busy city environment."
  • "Create an AI agent that can explore a 3D map and return to its starting point."

Tips & gotchas

  • Ensure the environment has accurate sensor data for reliable navigation.
  • Performance may degrade in highly complex or unpredictable scenarios without proper tuning.