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Receiving Code Review

Checked
davila7·vlatest·backend·MIT

Analyzes code reviews submitted to davila7, identifying potential bugs, style issues, and areas for improvement based on established best practices.

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 davila7/claude-code-templates --skill receiving-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

davila7

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 davila7/claude-code-templates at 79182c51fb.

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

Commit
79182c51fb
Manifest
cli-tool/components/skills/development/receiving-code-review/SKILL.md
Scanned
1 file, 190 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 AI agents to actively receive and process code reviews, allowing them to analyze feedback on their implementations and adjust their work accordingly. It facilitates a collaborative loop where the agent can understand critique and refine its output based on reviewer input.

When to use it

  • You need an agent to simulate a peer review process by analyzing comments on generated code.
  • You want the agent to iterate on a solution after receiving specific constraints or bug reports from a human or another system.
  • You are building a workflow where code quality is validated through automated feedback loops before deployment.
  • You require the agent to explain how it addressed specific suggestions made during a review session.

Key capabilities

  • Accepts and parses structured feedback regarding code logic, style, or security.
  • Integrates review comments directly into the agent's context for immediate action.
  • Generates revised code blocks that explicitly address identified issues.
  • Summarizes changes made in response to specific review points.

Example prompts

  • "Here is a code review comment stating my function lacks error handling; please revise the implementation to include try-catch blocks."
  • "Analyze this feedback on my database query optimization and provide an updated version of the SQL script."
  • "I received a suggestion to refactor this loop for better performance; show me how you applied that change."

Tips & gotchas

Ensure the code review input is clearly formatted, as vague feedback may result in generic revisions. The agent relies on the specificity of the critique to make targeted improvements rather than broad rewrites.