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Code Review

Checked
letta-ai·vlatest·backend·Apache-2.0

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 letta-ai/letta-code-action --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

letta-ai

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 letta-ai/letta-code-action at fe18cbf70b.

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

Commit
fe18cbf70b
Manifest
skills/code-review/SKILL.md
Scanned
1 file, 164 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

The letta-ai-code-review skill provides automated code review capabilities. It analyzes provided code snippets, identifies potential bugs, style issues, and areas for improvement based on established coding standards. The tool aims to improve code quality and reduce the time spent in manual code reviews.

When to use it

  • Before submitting a pull request: Quickly identify and fix common errors before sharing your code with others.
  • During pair programming: Get an automated second opinion while collaborating on code.
  • For onboarding new developers: Ensure consistency with existing coding standards within a project.
  • To review legacy code: Identify potential issues in older codebases that may require refactoring.

Key capabilities

  • Automated bug detection
  • Style guide enforcement
  • Code improvement suggestions
  • Adherence to established coding standards

Example prompts

  • "Review this Python function for potential errors and style violations: [code snippet]"
  • "Can you check this JavaScript code against the Airbnb style guide? [code snippet]"
  • "Analyze this Go code for performance bottlenecks. [code snippet]"

Tips & gotchas

The skill's effectiveness depends on the clarity of the coding standards it’s using. Providing context about project-specific guidelines can improve review accuracy.