analyzing-projects
Analyzes project structure and tech stacks to provide summary reports. Ideal for developers onboarding to new or complex repositories.
Install
mkdir -p .claude/skills/analyzing-projects && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/1689" && unzip -o skill.zip -d .claude/skills/analyzing-projects && rm skill.zipInstalls to .claude/skills/analyzing-projects
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
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?Key capabilities
- →Detects project tech stack from manifests
- →Maps directory structures
- →Identifies architectural patterns
- →Summarizes project workflows
How it works
Systematically crawls file manifests and structure to generate a high-level overview of project organization.
Inputs & outputs
When to use analyzing-projects
- →Onboarding to a new codebase
- →Understanding project architecture
- →Identifying tech stack components
- →Mapping project structure
About this skill
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.
When not to use it
- →Known, well-documented projects
- →Single-script files with no dependencies
Limitations
- →Requires read access to project root
- →Summary may drift if project structure changes
How it compares
Provides an architectural summary rather than just a simple file list.
Compared to similar skills
analyzing-projects side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| analyzing-projects (this skill) | 3 | 6mo | Review | Beginner |
| cursor-explorer-mcp | 6 | 8mo | No flags | Intermediate |
| octocode-research | 0 | 2mo | Review | Advanced |
| research-engineer | 2 | 6mo | No flags | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
More by CloudAI-X
View all by CloudAI-X →You might also like
cursor-explorer-mcp
sepiabrown
Use for token-expensive operations requiring multi-file analysis - codebase exploration, broad searches, architecture understanding, tracing flows, finding implementations across files. Uses MCP cursor-agent server (company pays) with clean async interface. Do NOT use for single-file analysis, explaining code already in immediate context, or pure reasoning tasks.
octocode-research
bgauryy
This skill should be used when the user asks to "research code", "how does X work", "where is Y defined", "who calls Z", "trace code flow", "find usages", "review a PR", "explore this library", "understand the codebase", or needs deep code exploration. Handles both local codebase analysis (with LSP semantic navigation) and external GitHub/npm research using Octocode tools.
research-engineer
davila7
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
analyse
eschaar
Cross-cutting technical analysis. Investigates impact, tradeoffs, root causes, or feasibility without implementing changes. Use when asked to "analyse this", "investigate the impact", "what are the tradeoffs", "root cause analysis", "is this feasible?", or "compare these approaches". Produces an ana
grill-me
onsenturk
Adversarial Socratic interrogation of an idea, design, plan, or PR. You challenge the user''s assumptions, probe edge cases, and stress-test their reasoning before they commit. Use when the user says "grill me", "challenge this", "poke holes", "play devil''s advocate", "stress-test this", or wants t
architect-review
sickn33
Master software architect specializing in modern architecture patterns, clean architecture, microservices, event-driven systems, and DDD. Reviews system designs and code changes for architectural integrity, scalability, and maintainability. Use PROACTIVELY for architectural decisions.