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Analyzing Projects

Checked
cloudai-x·vlatest·backend·MIT

Analyzes project details to identify key risks, timelines, and resources, boosting efficiency and informed decision-making.

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 cloudai-x/claude-workflow-v2 --skill analyzing-projects -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

cloudai-x

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 cloudai-x/claude-workflow-v2 at 4c242af16f.

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

Commit
4c242af16f
Manifest
skills/analyzing-projects/SKILL.md
Scanned
1 file, 151 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 analyzes project details to help AI agents understand unfamiliar codebases and workflows. It systematically explores a project's structure, identifies its technology stack (including programming languages, frameworks, and infrastructure), and maps out key patterns like architecture and API style. The analysis follows a six-step checklist designed for efficient onboarding and comprehension of new projects.

When to use it

  • When starting work on a new project where the codebase is unfamiliar.
  • To quickly understand the technology stack used in an existing project.
  • During code exploration or when needing to grasp the overall structure of a project.
  • To answer "how does this work" questions about a project's functionality.

Key capabilities

  • Tech Stack Detection: Identifies programming languages, package managers (e.g., package.json, requirements.txt), frameworks (e.g., React, Django), and infrastructure components (e.g., Dockerfiles, Kubernetes).
  • Project Structure Mapping: Presents a tree-like representation of the project's directory structure with annotations describing each section’s purpose.
  • Pattern Identification: Recognizes architectural patterns (Monolith, Microservices) and API styles (REST, GraphQL).
  • Progress Tracking: Uses a checklist to guide the analysis process, ensuring all key areas are examined.

Example prompts

  • "Analyze this project and tell me what technologies it uses."
  • "Can you map out the structure of this codebase?"
  • "What is the architecture of this project?"
  • "Walk me through a quick overview of this project, starting with the README."

Tips & gotchas

  • The skill relies on common file markers like README.md, package.json, and Dockerfiles to identify key aspects of the project. Ensure these files are present for optimal results.
  • This skill is designed for understanding existing projects, not for creating new ones or contributing directly to development.