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Analyze Codebase Workflow

Listed
pjt222·vlatest·backend·MIT

Quickly identifies dependencies, potential bottlenecks, and optimization opportunities within a codebase's workflow.

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 pjt222/agent-almanac --skill analyze-codebase-workflow -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

pjt222

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • Declares what it does: failed

    No SKILL.md was found in the skill's directory.

    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 pjt222/development-guides at bcca822c1c.

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

Scanned
0 files
Copies in repo
3 — all of them scanned
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 allows an AI agent to analyze a codebase, identifying key components and dependencies. It can generate documentation summaries from code comments and identify potential areas for refactoring or improvement based on established coding patterns. The workflow is designed to provide developers with insights into unfamiliar projects quickly.

When to use it

  • Onboarding to a new project: Quickly understand the structure and purpose of an existing codebase.
  • Code review preparation: Identify potential issues and areas for discussion before a formal code review.
  • Refactoring planning: Get suggestions on how to improve code quality and maintainability.
  • Documentation generation: Automatically create initial documentation based on code comments.

Key capabilities

  • Codebase structure analysis
  • Dependency identification
  • Comment-based documentation summarization
  • Potential refactoring suggestion

Example prompts

  • "Analyze this codebase and tell me about the main modules."
  • "Summarize the purpose of each class in this file."
  • "Identify any potential code smells or areas for improvement in this function."

Tips & gotchas

The skill's effectiveness depends on clear and consistent code comments within the codebase. Larger codebases may require more processing time.