Claude Code Guide: From Installation to Project Collaboration
One-sentence takeaway: Claude Code is best suited for tasks that involve an existing code repository — reading a project, locating bugs, refactoring modules, writing tests, and creating documentation. It's not a simple chat window; it's a programming collaboration partner that requires you to manage permissions, context, and verification workflows.
Who this is for: Independent developers, engineers maintaining legacy projects, and product/tech leads who need to break requirements into code tasks.
This article addresses three questions:
- What is Claude Code good at, and what is it not good at?
- What environment preparations do developers need before using it?
- How do you let it safely modify code without messing up your project?
What Is Claude Code
Claude Code is an AI programming agent for developers. Unlike the web version of Claude, its core strength isn't "answering questions" — it's understanding file structures within a project directory, reading code, proposing modification plans, and assisting with code changes once you authorize them.
Think of it as a senior engineer sitting next to you:
- Can quickly grasp the general structure of an unfamiliar repository;
- Can break vague requirements into implementation steps;
- Can locate errors, explain call chains, and supplement tests;
- Can modify files, but needs you to review and verify the results.
If you just want to write some copy or summarize a PDF, the web version of Claude is sufficient; if you're working with a real code repository, Claude Code's value becomes much more apparent.
Pre-Use Preparations
1. Check Your Network Environment First
When using Claude services, the most common issue isn't the installation commands — it's that the terminal network isn't going through a proxy. Just because your browser can open Claude doesn't mean commands in PowerShell, Terminal, or Git Bash can connect.
If you're using a local proxy, set the proxy environment variables in your current terminal first:
$env:http_proxy="http://127.0.0.1:7890"
$env:https_proxy="http://127.0.0.1:7890"For macOS / Linux, use:
export http_proxy=http://127.0.0.1:7890
export https_proxy=http://127.0.0.1:7890The port number depends on your proxy client. Common cases: Clash uses 7890, V2Ray-based tools may use 10809.
2. Protect Your Current Project First
Before letting AI modify code, do three things:
- Confirm the project can start or tests can run normally;
- Save the current state with git;
- Clearly tell Claude Code which directories or files it's allowed to modify.
If the project isn't under git, at least make a backup copy. The worst thing in AI-assisted programming is "modifying while guessing" — having no rollback point causes troubleshooting costs to skyrocket.
3. Prepare a Clear Task Description
Don't just say "help me optimize the project." A better description should include:
- Current problem: page loads slowly, a test fails, a button doesn't respond;
- Desired outcome: fix the bug, add tests, refactor a module, output a migration plan;
- Constraints: don't change the API, don't touch the database, don't rename public methods;
- Verification method: which command to run, which page to check, which output to examine.
Recommended Workflow
Step 1: Read-Only Analysis
First, let Claude Code read the project without making changes immediately:
Do a read-only analysis of this project first. Tell me the entry files, core modules, data flow, and potential risks. Do not modify any files.
The goal of this round is to establish shared context. You want to see whether it truly understands the project, not rush into accepting changes.
Step 2: Have It Output a Plan
Before taking any real action, ask it to provide a plan:
For this issue, please give me a 3-5 step modification plan. For each step, explain which files will be changed and how to verify.
A good plan should show clear boundaries: minimal changes, clear verification, and no impulse to refactor unrelated modules along the way.
Step 3: Limit the Write Scope
If you only want to modify the login page, explicitly constrain it:
Only allow modifications to
src/pages/loginand related test files. Do not change global config. Do not upgrade dependencies.
This step significantly reduces the probability of "fixing one bug and pulling in a bunch of unrelated changes."
Step 4: Review the Diff After Changes
After Claude Code makes changes, don't merge immediately. First review:
git diffKey things to check:
- Whether any unrelated files were changed;
- Whether any existing logic was deleted;
- Whether any keys, paths, or accounts were hardcoded;
- Whether any temporary logs were left in the code.
Step 5: Close the Loop with Tests or Builds
Finally, close the loop using the project's existing verification methods:
- Frontend projects: run builds, lint, manual testing of key pages;
- Backend projects: run unit tests, integration tests;
- Documentation projects: build the static site, spot-check key pages.
If there are no tests, have Claude Code produce a "manual verification checklist" and confirm each item.
Tasks Suitable for Claude Code
| Scenario | Suitability | Recommended Approach |
|---|---|---|
| Reading an unfamiliar project | Very suitable | Have it draw module diagrams and call chains first |
| Fixing a specific bug | Very suitable | Provide the error, reproduction steps, and desired outcome |
| Writing tests | Very suitable | Specify the testing framework and coverage targets |
| Large-scale refactoring | Use with caution | Have it plan in phases; only change a small piece at a time |
| Upgrading dependencies | Use with caution | Back up lock files first; handle dependencies one at a time |
| Building a large project from scratch | Not recommended | Break it into small tasks: pages, APIs, data models, etc. |
Common Mistakes
Mistake 1: Not Providing Context
Just saying "this project has a bug, help me fix it" leaves the AI guessing. At minimum, provide the error, trigger steps, and what you've already tried.
Mistake 2: Asking It to Change Too Much at Once
Asking it to "refactor the architecture, optimize performance, add tests, and redo the UI" all at once easily leads to cascading problems. The right approach is to complete one verifiable goal at a time.
Mistake 3: Not Reviewing the Diff
AI writes code fast, but not every change is correct. git diff is the lowest-cost quality gate.
Mistake 4: Handing Secrets and Private Files to the AI
Don't put .env files, private keys, production database backups, or user privacy data directly into the context. Sanitize them first if necessary.
Recommended Prompt Templates
Project Health Check
Please do a read-only analysis of this project first. Do not modify any files.
Please output:
1. Project entry point and core directories
2. Main business processes
3. Potential technical debt
4. If continuing development, which files should be read first as a priorityBug Fix
I'm encountering a bug: {describe the symptom}.
Reproduction steps: {steps}.
Expected result: {expected}.
Please first analyze possible causes and provide a modification plan. Do not change files immediately.Safe Changes
Please make changes according to your plan, but limit them to these files/directories: {scope}.
Do not upgrade dependencies, do not change public APIs, do not change unrelated styles.
After making changes, please explain what was changed and how I should verify.Related Reading
- Claude Tutorials: Learn about Claude's basic capabilities and account usage considerations first.
- How to Save Claude Chat History: Read this first if you need to preserve code discussion records long-term.
- Claude Pro Recharge Service: If you're stuck at the subscription payment step, check out the solution details.