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analyzing-projects

Analyzes codebases to understand structure, tech stack, patterns, and conventions

Install / Use

npx skills add CloudAI-X/claude-workflow-v2 --skill analyzing-projects

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

86/100

Category

Automation

Supported Platforms

Universal

Tags

Our assessment of analyzing-projects

analyzing-projects scores 86/100 on our quality scale, 1485th of 2,703 Automation skills we index.

Its SKILL.md is 3.7 KB long, well organised into 22 sections with 5 code examples: a solid amount of guidance for an agent.

With 1,416 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
20/20
Description
12/15
Adoption
13/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 36 days ago, so analyzing-projects is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

No issues found

Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.

Automated pattern scan on 2026-10-01. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

analyzing-projects compared with similar skills

All 4 of these similar skills score higher than analyzing-projects; compare them before choosing.

SkillScoreStarsUpdatedFormat
analyzing-projects (this skill)by CloudAI-X861.4k36d agoSKILL.md
Agent-Reachby Panniantong10086.6k15d agoCLAUDE.md
rufloby ruvnet10073.6ktodayCLAUDE.md
Scraplingby D4Vinci10084.8ktodayMCP Server
algorithmic-artby anthropics100177.9k8d agoSKILL.md

Frequently asked questions

How do I install analyzing-projects?
Run npx skills add CloudAI-X/claude-workflow-v2 --skill analyzing-projects. The install tabs above show the steps for each supported agent.
Which AI agents does analyzing-projects work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is analyzing-projects safe to use?
Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is analyzing-projects still maintained?
The repository was last updated 36 days ago, so analyzing-projects is actively maintained.

name: analyzing-projects description: Analyzes codebases to understand structure, tech stack, patterns, and conventions. Use when onboarding to a new project, exploring unfamiliar code, or when asked "how does this work?" or "what's the architecture?"

Analyzing Projects

When to Load

  • Trigger: Onboarding to a new project, "how does this work" questions, codebase exploration, understanding unfamiliar code
  • Skip: Already familiar with the project structure and patterns

Project Analysis Workflow

Copy this checklist and track progress:

Project Analysis Progress:
- [ ] Step 1: Quick overview (README, root files)
- [ ] Step 2: Detect tech stack
- [ ] Step 3: Map project structure
- [ ] Step 4: Identify key patterns
- [ ] Step 5: Find development workflow
- [ ] Step 6: Generate summary report

Step 1: Quick Overview

# Check for common project markers
ls -la
cat README.md 2>/dev/null | head -50

Step 2: Tech Stack Detection

Package Managers & Dependencies

  • package.json → Node.js/JavaScript/TypeScript
  • requirements.txt / pyproject.toml / setup.py → Python
  • go.mod → Go
  • Cargo.toml → Rust
  • pom.xml / build.gradle → Java
  • Gemfile → Ruby

Frameworks (from dependencies)

  • React, Vue, Angular, Next.js, Nuxt
  • Express, FastAPI, Django, Flask, Rails
  • Spring Boot, Gin, Echo

Infrastructure

  • Dockerfile, docker-compose.yml → Containerized
  • kubernetes/, k8s/ → Kubernetes
  • terraform/, .tf files → IaC
  • serverless.yml → Serverless Framework
  • .github/workflows/ → GitHub Actions

Step 3: Project Structure Analysis

Present as a tree with annotations:

project/
├── src/              # Source code
│   ├── components/   # UI components (React/Vue)
│   ├── services/     # Business logic
│   ├── models/       # Data models
│   └── utils/        # Shared utilities
├── tests/            # Test files
├── docs/             # Documentation
└── config/           # Configuration

Step 4: Key Patterns Identification

Look for and report:

  • Architecture: Monolith, Microservices, Serverless, Monorepo
  • API Style: REST, GraphQL, gRPC, tRPC
  • State Management: Redux, Zustand, MobX, Context
  • Database: SQL, NoSQL, ORM used
  • Authentication: JWT, OAuth, Sessions
  • Testing: Jest, Pytest, Go test, etc.

Step 5: Development Workflow

Check for:

  • .eslintrc, .prettierrc → Linting/Formatting
  • .husky/ → Git hooks
  • Makefile → Build commands
  • scripts/ in package.json → NPM scripts

Step 6: Output Format

Generate a summary using this template:

# Project: [Name]

## Overview

[1-2 sentence description]

## Tech Stack

| Category  | Technology |
| --------- | ---------- |
| Language  | TypeScript |
| Framework | Next.js 14 |
| Database  | PostgreSQL |
| ...       | ...        |

## Architecture

[Description with simple ASCII diagram if helpful]

## Key Directories

- `src/` - [purpose]
- `lib/` - [purpose]

## Entry Points

- Main: `src/index.ts`
- API: `src/api/`
- Tests: `npm test`

## Conventions

- [Naming conventions]
- [File organization patterns]
- [Code style preferences]

## Quick Commands

| Action  | Command         |
| ------- | --------------- |
| Install | `npm install`   |
| Dev     | `npm run dev`   |
| Test    | `npm test`      |
| Build   | `npm run build` |

Analysis Validation

After completing analysis, verify:

Analysis Validation:
- [ ] All major directories explained
- [ ] Tech stack accurately identified
- [ ] Entry points documented
- [ ] Development commands verified working
- [ ] No assumptions made without evidence

If any items cannot be verified, note them as "needs clarification" in the report.

Related Skills

View on GitHub
GitHub Stars1.4k
CategoryAutomation
Updated1mo ago
Forks190

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions