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Ai Generated Business Code Review

Checked
openharmonyinsight·vlatest·backend

Helps with AI, code review as part of developing backend services and APIs workflows.

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 openharmonyinsight/openharmony-skills --skill ai-generated-business-code-review -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

openharmonyinsight

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 openharmonyinsight/openharmony-skills at 5ae988cab6.

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

Commit
5ae988cab6
Manifest
skills/ai-generated-business-code-review/SKILL.md
Scanned
1 file, 84 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 analyzes business code and provides reviews, identifying potential issues and suggesting improvements. It can assess code for correctness, efficiency, and adherence to best practices. The AI agent leverages this skill to ensure higher quality code output and reduce the risk of errors in production environments.

When to use it

  • Reviewing newly written backend code before merging into a main branch.
  • Analyzing existing codebases to identify areas for refactoring or optimization.
  • Ensuring compliance with specific coding standards within an organization.
  • Automating the initial stages of code review, freeing up human reviewers for more complex tasks.

Key capabilities

  • Code analysis
  • Issue identification
  • Suggestion generation
  • Best practice adherence assessment

Example prompts

  • "Review this Python function and identify any potential performance bottlenecks: [code snippet]"
  • "Analyze this Java class for code smells and suggest improvements."
  • "Check this Go module against our company's coding standards."

Tips & gotchas

The quality of the review depends on the clarity and completeness of the provided code. Providing context about the purpose and expected behavior of the code can improve the accuracy of the analysis.