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Code Metrics Analysis

Checked
aj-geddes·vlatest·devops·MIT

Analyzes codebases to identify complexity, maintainability issues, and potential performance bottlenecks using established metrics.

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 aj-geddes/useful-ai-prompts --skill code-metrics-analysis -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

aj-geddes

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 aj-geddes/useful-ai-prompts at 3f5182cfd7.

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

Commit
3f5182cfd7
Manifest
skills/code-metrics-analysis/SKILL.md
Scanned
7 files, 565 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

code-metrics-analysis

What it does

This skill enables AI agents to analyze software codebases for quality and complexity metrics. It helps identify potential bottlenecks, technical debt, and areas requiring refactoring by evaluating structural characteristics of the code.

When to use it

  • Before starting a major feature implementation to understand existing codebase health.
  • During code reviews to objectively assess complexity beyond human intuition.
  • When planning refactoring efforts to prioritize high-risk or overly complex modules.
  • To generate baseline metrics for tracking code quality improvements over time.

Key capabilities

  • Calculates cyclomatic complexity to measure decision density in functions.
  • Identifies code duplication patterns across the repository.
  • Assesses maintainability based on metric thresholds.
  • Provides actionable insights into architectural weaknesses.

Example prompts

  • "Analyze this Python module and report its cyclomatic complexity along with specific lines that exceed recommended limits."
  • "Identify duplicated code blocks in this JavaScript project and suggest refactoring strategies to reduce redundancy."
  • "Evaluate the maintainability score of this microservice architecture and highlight dependencies that may cause future bottlenecks."

Tips & gotchas

Ensure your codebase is properly indexed before running analysis, as missing files can skew metric accuracy. Focus on interpreting high-complexity scores in context rather than treating them as absolute failure indicators.