analyzing-projects
Analyzes codebases to understand structure, tech stack, patterns, and conventions
Install / Use
npx skills add CloudAI-X/claude-workflow-v2 --skill analyzing-projectsInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
AutomationSupported Platforms
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.
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 foundOur 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.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| analyzing-projects (this skill)by CloudAI-X | 86 | 1.4k | 36d ago | SKILL.md |
| Agent-Reachby Panniantong | 100 | 86.6k | 15d ago | CLAUDE.md |
| rufloby ruvnet | 100 | 73.6k | today | CLAUDE.md |
| Scraplingby D4Vinci | 100 | 84.8k | today | MCP Server |
| algorithmic-artby anthropics | 100 | 177.9k | 8d ago | SKILL.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.
Skill content
View source on GitHubname: 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/TypeScriptrequirements.txt/pyproject.toml/setup.py→ Pythongo.mod→ GoCargo.toml→ Rustpom.xml/build.gradle→ JavaGemfile→ Ruby
Frameworks (from dependencies)
- React, Vue, Angular, Next.js, Nuxt
- Express, FastAPI, Django, Flask, Rails
- Spring Boot, Gin, Echo
Infrastructure
Dockerfile,docker-compose.yml→ Containerizedkubernetes/,k8s/→ Kubernetesterraform/,.tffiles → IaCserverless.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 hooksMakefile→ Build commandsscripts/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.
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
