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Cpp

Checked
miles990·vlatest·backend·MIT

Generates C++ code snippets based on your prompts – a handy tool for developers needing quick code examples and experimentation.

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 miles990/claude-software-skills --skill cpp -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

miles990

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 miles990/claude-software-skills at 73632f218e.

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

Commit
73632f218e
Manifest
programming-languages/cpp/SKILL.md
Scanned
3 files, 726 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 enables an AI agent to understand and generate C++ code. It can assist with tasks ranging from simple code snippets to more complex programming problems, providing explanations and suggestions along the way. The skill allows for both generating new C++ code and analyzing existing code for potential improvements or errors.

When to use it

  • Code Generation: Generate a function that calculates the factorial of a number in C++.
  • Debugging Assistance: Ask the agent to identify potential bugs in a provided C++ code snippet.
  • Code Explanation: Request an explanation of what a specific block of C++ code does.
  • Refactoring Suggestions: Have the AI suggest ways to improve the readability or efficiency of existing C++ code.

Key capabilities

  • C++ Code Generation
  • C++ Code Analysis
  • C++ Code Explanation
  • Bug Identification in C++

Example prompts

  • "Write a C++ function that sorts an array of integers."
  • "Explain this C++ code: int main() { std::cout << "Hello, world!" << std::endl; return 0; }"
  • "Can you find any potential memory leaks in this C++ program?"

Tips & gotchas

The agent's performance is dependent on the clarity and specificity of your prompts. Providing context or examples can significantly improve the quality of the generated code or analysis.