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Pint Compute

Checked
parcadei·vlatest·other·MIT

Pint Compute efficiently executes shell commands within a containerized environment for rapid prototyping and testing.

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 parcadei/continuous-claude-v3 --skill pint-compute -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

parcadei

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 parcadei/continuous-claude-v3 at d07ff4b06b.

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

Commit
d07ff4b06b
Manifest
.claude/skills/pint-compute/SKILL.md
Scanned
1 file, 115 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 pint-compute skill provides access to a computational resource. It allows AI agents to perform calculations and data processing tasks, likely involving numerical operations or complex logic. The specific details of the computations are not described in the source content.

When to use it

  • When your agent needs to perform mathematical calculations beyond simple arithmetic.
  • For scenarios requiring data analysis or manipulation based on numerical inputs.
  • To execute complex logical operations that require computational power.
  • When integrating with systems needing programmatic access to computation resources.

Key capabilities

  • Access to a computational resource.
  • Ability to perform calculations and data processing.
  • Supports numerical operations (specifics not detailed).
  • Handles complex logic execution.

Example prompts

  • "Calculate the standard deviation of this dataset: [data]"
  • "Compute the result of this equation: [equation]"
  • "Process these numbers according to this algorithm: [algorithm]"

Tips & gotchas

The source content does not provide any specific prerequisites or limitations. It is assumed that the computational resource has its own constraints and requirements which should be investigated before use.