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Quality Audit

Checked
rysweet·vlatest·writing

Analyzes text for clarity, tone, grammar, and brand consistency to ensure high-quality written content.

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 rysweet/amplihack --skill quality-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

rysweet

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 rysweet/amplihack at 84424457d5.

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

Commit
84424457d5
Manifest
.claude/skills/quality-audit/SKILL.md
Scanned
6 files, 3,698 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 rysweet-quality-audit skill assesses text for various quality attributes. It can identify issues like grammatical errors, awkward phrasing, and lack of clarity. The skill aims to improve the overall readability and professionalism of written content by suggesting revisions and improvements.

When to use it

  • Content Creation: Evaluate blog posts or articles before publishing to ensure high-quality writing.
  • Email Communication: Check important emails for errors and a professional tone before sending.
  • Report Generation: Review reports for clarity, accuracy, and grammatical correctness.
  • Drafting Documents: Assess initial drafts of documents to identify areas needing refinement.

Key capabilities

  • Grammar checking
  • Readability assessment
  • Phrase improvement suggestions
  • Clarity enhancement

Example prompts

  • "Please audit this email draft for grammar and clarity: [email text]"
  • "Can you assess the readability of this blog post excerpt? [blog post excerpt]"
  • "Review this report section and suggest improvements to make it more professional. [report section]"

Tips & gotchas

The skill’s effectiveness depends on the quality of the input text; poorly written or ambiguous content may yield less accurate results. Consider providing context if the AI agent needs to understand specific terminology or style guidelines.