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Accurate Environment Model

Checked
marius-townhouse·vlatest·other

Creates a precise, up-to-date digital representation of the environment, enabling informed planning and navigation.

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 marius-townhouse/effective-typescript-skills --skill accurate-environment-model -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

marius-townhouse

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 marius-townhouse/effective-typescript-skills at d754db2077.

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

Commit
d754db2077
Manifest
skills/accurate-environment-model/SKILL.md
Scanned
1 file, 46 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 accurately model and reason about environments. It provides a framework for representing spatial relationships, object properties, and environmental constraints. The agent can use this model to plan actions, predict outcomes, and adapt to changes in the environment with increased precision.

When to use it

  • Robotics Navigation: Enable a robot to navigate complex indoor spaces by understanding room layouts and obstacle locations.
  • Game AI: Create more realistic and believable non-player characters (NPCs) that interact intelligently with their game world.
  • Virtual Assistants: Allow virtual assistants to understand the context of user requests related to physical environments, like "turn on the light in the kitchen."
  • Simulations: Build accurate simulations for training AI agents in realistic scenarios.

Key capabilities

  • Spatial reasoning
  • Object property representation
  • Environmental constraint modeling
  • Action planning and prediction

Example prompts

  • "Describe the layout of this room, including furniture placement."
  • "If I move forward five steps, will I collide with anything?"
  • "What is the shortest path to the window?"
  • “Create a model of my living room based on this image.”

Tips & gotchas

The accuracy of the environment model depends heavily on the quality and completeness of input data. Consider providing detailed descriptions or visual references for optimal results.