Skip to content
TrustedSkillsbeta
Back to all skills

Argument Audit

Checked
mrilikecoding·vlatest·other

Analyzes arguments for logical fallacies, biases, and weaknesses, providing a structured critique and improvement suggestions.

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 mrilikecoding/dotfiles --skill argument-audit -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

mrilikecoding

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 mrilikecoding/dotfiles at 1d20ece182.

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

Commit
1d20ece182
Manifest
home/.vibe/skills/argument-audit/SKILL.md
Scanned
2 files, 443 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 argument-audit skill analyzes arguments provided to a function or piece of code, identifying potential issues like incorrect data types, missing parameters, or logical flaws. It can help debug existing code and proactively prevent errors by flagging suspicious argument combinations before execution. This skill aims to improve the robustness and reliability of software systems.

When to use it

  • Debugging: When a function consistently produces unexpected results, use argument-audit to examine the input arguments for inconsistencies or invalid values.
  • Code Review: Integrate into code review processes to identify potential argument-related vulnerabilities before they reach production.
  • API Design: Validate and refine API designs by testing various argument combinations and ensuring expected behavior.
  • Automated Testing: Incorporate argument-audit into automated test suites to proactively catch errors related to function arguments.

Key capabilities

  • Argument validation
  • Data type checking
  • Parameter completeness verification
  • Logical flaw detection in argument combinations

Example prompts

  • "Analyze the arguments passed to this Python function: def calculate_area(length, width): ..."
  • "Check if these parameters are valid for a user registration API call: name=John Doe, email=invalid-email, age=-5."
  • “Can you audit the arguments being sent to this Javascript function and tell me what could go wrong?”

Tips & gotchas

The effectiveness of argument-audit depends on having access to the code or API definition being analyzed. It's most useful when combined with clear documentation about expected argument types and constraints.