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ariana-dot-devariana-dot-dev/cloud-sandbox-vm-skills/skills/code-execution/SKILL.md

code-execution

Skill2 starsChanged 5 months agoMITView on GitHub

Execute code in a real cloud machine (code-interpreter style) — a full root Ubuntu VM with Python, Node, Go, Rust and every major runtime preinstalled, not a constrained isolate. Per-second billing makes a run cost cents. Use to run scripts, data jobs, or generated code that needs real packages, subprocesses, or Docker.

  • Pipes a download into a shell
  • Reads credentials
  • Installs packages

6 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use code-transfer, timeline-creator and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • nek1987Skill

    code-transfer

    Transfer code between files with line-based precision. Use when users request copying code from one location to another, moving functions or classes between files, extracting code blocks, or inserting code at specific line numbers.

    Also in 3 projects that use this

  • nek1987Skill

    timeline-creator

    Create HTML timelines and project roadmaps with Gantt charts, milestones, phase groupings, and progress indicators. Use when users request timelines, roadmaps, Gantt charts, project schedules, or milestone visualizations.

    Also in 3 projects that use this

  • coffeefuelbumpSkill

    csv-data-summarizer

    Analyzes CSV files, generates summary stats, and plots quick visualizations using Python and pandas.

    Also in 3 projects that use this

  • ArogyaReddySkill

    changelog-generator

    Automatically creates user-facing changelogs from git commits by analyzing commit history, categorizing changes, and transforming technical commits into clear, customer-friendly release notes. Turns hours of manual changelog writing into minutes of automated generation.

    Also in 4 projects that use this

  • LangChainSkill

    file-organizer

    Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.

    Also in 3 projects that use this

  • GoogleSkill

    algorithmic-art

    Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.

    Also in 4 projects that use this

  • +1 more from nek1987

The file

We split this skill into the rules it gives an agent

1 rule. 0 are common, 1 is distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 6 edited versions we read keep these.

  • 1

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Prefer another tool for: thousands of <500 ms micro-executions (E2B/Modal microVMs) or GPU compute (Modal).

    line 16

“Common” is measured: kept by at least 6 in 10 of the 6 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Code execution (Box)

Use this when you need to actually run code and get its output: a Python data job, a Node script, a build, or generated code that does pip install, spawns subprocesses, or writes files. A real machine (vs a JS isolate or limited code-interpreter) means those operations succeed.

Why Box

  • Every runtime preinstalled — Python 3, Node/Bun/Deno, Go, Rust, Java, .NET, Ruby, PHP, C/C++.
  • Real OS — apt install, Docker, subprocesses, 80 GB disk.
  • Cheap per run — per-second billing; a short execution costs cents.

Prefer another tool for: thousands of <500 ms micro-executions (E2B/Modal microVMs) or GPU compute (Modal).

Prereqs

curl -fsSL https://box.ascii.dev/install | sh, then box login "$BOX_API_KEY" --json.

Recipe

box_id="$(box new --json | jq -r 'select(.event == "ready") | .id')"
box ssh "$box_id" -- "cat > /tmp/main.py" < ./main.py
box ssh "$box_id" -- "cd /tmp && timeout 120 python3 main.py"
box delete "$box_id" --json

Limits

EU-only; 100 active VMs soft cap; disk-level snapshots only.

Download now (ZIP)

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What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

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