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Dart Python

Checked
dartsim·vlatest·backend·BSD-2-Clause

Helps with Dart, Python as part of developing backend services and APIs workflows.

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 dartsim/dart --skill dart-python -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

dartsim

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 dartsim/dart at d63fe1fd8b.

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

Commit
d63fe1fd8b
Manifest
.agents/skills/dart-python/SKILL.md
Scanned
2 files, 130 lines
Copies in repo
2 — all of them scanned
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 dart-python skill allows AI agents to execute Python code within a Dart environment. This enables the agent to leverage Python's extensive libraries and tooling for tasks like data analysis, scientific computing, or interacting with specific APIs that have robust Python bindings. The integration provides a bridge between Dart’s performance and Python’s ecosystem.

When to use it

  • Data Processing: When an agent needs to perform complex calculations or transformations on datasets where existing Dart libraries are insufficient.
  • API Interaction: To interact with APIs that have better support or more comprehensive client libraries in Python.
  • Scientific Computing: For tasks involving numerical computation, simulations, or data visualization using Python's scientific computing stack (e.g., NumPy, SciPy).
  • Prototyping: Quickly prototype and test solutions leveraging existing Python code before potentially porting them to Dart.

Key capabilities

  • Python execution within a Dart environment
  • Access to Python libraries
  • Data transfer between Dart and Python environments
  • Integration with Dart’s performance characteristics

Example prompts

  • "Run this Python script: print(2+2)"
  • "Use Python to calculate the average of these numbers: [1, 2, 3, 4, 5]"
  • "Execute this Python code and return the result as a JSON object."

Tips & gotchas

  • Ensure that necessary Python dependencies are installed within the environment accessible to the agent.
  • Be mindful of potential performance overhead when transferring data between Dart and Python.