Skip to content
TrustedSkillsbeta
Back to all skills

Deepagents Code Review

Checked
existential-birds·vlatest·backend·Apache-2.0

Automated code review identifies bugs, security vulnerabilities, and style inconsistencies in Python/Java backend projects.

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 existential-birds/beagle --skill deepagents-code-review --full-depth -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

existential-birds

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 existential-birds/beagle at d1a74899fb.

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

Commit
d1a74899fb
Manifest
plugins/beagle-ai/skills/deepagents-code-review/SKILL.md
Scanned
2 files, 481 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

The deepagents-code-review skill enables AI agents to analyze codebases for security vulnerabilities, logical errors, and adherence to best practices. It provides automated feedback on pull requests or specific files to improve software quality before deployment.

When to use it

  • Reviewing third-party contributions in open-source projects to ensure alignment with project standards.
  • Validating complex backend logic changes before merging into the main branch.
  • Identifying potential security flaws or injection points in new API endpoints.
  • Enforcing consistent coding conventions across a growing team of developers.

Key capabilities

  • Automated static analysis of code for bugs and inefficiencies.
  • Security-focused scanning to detect common vulnerabilities.
  • Context-aware suggestions for refactoring and optimization.
  • Integration with version control workflows for seamless PR reviews.

Example prompts

  • "Analyze the new authentication module in src/auth.py for security vulnerabilities and logic errors."
  • "Review this pull request to ensure all changes follow our team's backend coding standards."
  • "Identify any potential race conditions or memory leaks in the provided database connection handler code."

Tips & gotchas

Ensure the AI agent has read access to the repository or file system where the code resides before initiating a review. While effective at spotting common issues, complex architectural decisions may still require human oversight.