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Codebase Analyzer

Checked
d-o-hub·vlatest·backend·MIT

Analyzes your codebase to identify potential vulnerabilities and code quality issues, boosting security and maintainability.

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 d-o-hub/rust-self-learning-memory --skill codebase-analyzer -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

d-o-hub

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 d-o-hub/rust-self-learning-memory at da7210f59b.

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

Commit
da7210f59b
Manifest
.agents/skills/codebase-analyzer/SKILL.md
Scanned
5 files, 2,027 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 codebase-analyzer skill analyzes Rust codebases to identify potential issues and areas for improvement. It can detect common coding errors, suggest optimizations, and provide insights into the codebase's structure and dependencies. This helps developers understand complex projects more quickly and improve code quality.

When to use it

  • Onboarding new team members: Quickly familiarize them with a large or unfamiliar Rust project by generating summaries of its components and potential pitfalls.
  • Code review assistance: Identify common errors and suggest improvements during the code review process, accelerating feedback loops.
  • Refactoring existing code: Get suggestions for optimizing performance or improving maintainability within an established codebase.
  • Understanding dependencies: Analyze project dependencies to identify potential conflicts or outdated libraries.

Key capabilities

  • Error detection
  • Optimization suggestions
  • Codebase structure analysis
  • Dependency analysis

Example prompts

  • "Analyze this Rust code for potential memory safety issues: [code snippet]"
  • "Provide a summary of the dependencies in this project."
  • "Suggest optimizations for this function: [function code]"

Tips & gotchas

The skill's effectiveness depends on providing clear and concise code snippets or file paths. Large, complex projects may require iterative analysis to avoid overwhelming the AI agent.