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Code Review

Checked
agno-agi·vlatest·backend·Apache-2.0

Automated code review focusing on performance, security, and best practices within agno-agi's backend systems.

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 agno-agi/agno --skill 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

agno-agi

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 agno-agi/agno at 8c3d8ec52b.

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

Commit
8c3d8ec52b
Manifest
cookbook/02_agents/16_skills/sample_skills/code-review/SKILL.md
Scanned
3 files, 240 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 perform automated code reviews for agno-agi's backend systems, focusing on performance, security, and adherence to best practices. The review process involves checking code style against a defined guide, running automated style checks using a provided script, identifying potential issues like bugs or vulnerabilities, and providing structured feedback with severity levels. The skill aims to improve code quality and reduce the risk of introducing errors into production.

When to use it

  • Before merging new code changes into agno-agi's backend systems.
  • To proactively identify and address potential security vulnerabilities in existing code.
  • When refactoring or optimizing code for improved performance.
  • As part of a continuous integration/continuous delivery (CI/CD) pipeline to ensure consistent code quality.

Key capabilities

  • Style Guide Reference: Accesses a style guide (style-guide.md) using get_skill_reference.
  • Automated Style Checking: Executes a script (check_style.py) for automated style checks.
  • Issue Identification: Identifies potential bugs, security issues, and performance problems.
  • Structured Feedback: Provides feedback categorized by severity: Critical, Important, and Suggestion.
  • Checklist Enforcement: Verifies adherence to a checklist including naming conventions, secret handling, error handling, function length limits (under 50 lines), security vulnerabilities, and test coverage.

Example prompts

  • "Review this code snippet for potential performance issues."
  • "Can you check this file for any security vulnerabilities?"
  • "Perform a full code review of this pull request, focusing on style and best practices."

Tips & gotchas

  • The skill relies on the style-guide.md document and check_style.py script provided by agno-agi. Ensure these are accessible for accurate results.
  • Feedback is categorized based on severity levels (Critical, Important, Suggestion), which should be considered when addressing review comments.
  • The skill specifically targets agno-agi's backend systems and may not be applicable to other codebases.