40+ tips for getting the most out of Claude Code, from basics to advanced - includes a custom status line script, cutting the system prompt in half, using Gemini CLI as Claude Code's minion, and Claude Code running itself in a container. Also includes the dx plugin.
git clone https://github.com/ykdojo/claude-code-tips.githttps://github.com/ykdojo/claude-code-tips
[{"step":"Identify your specific bottleneck in Claude Code usage (e.g., slow responses, context limits, repetitive tasks).","action":"Run `claude --stats` to get baseline metrics on your current usage patterns.","tip":"Check the claude-code-tips collection for tips matching your bottleneck category (performance, automation, debugging)."},{"step":"Customize your status line for real-time monitoring.","action":"Edit `~/.claude_settings.json` and add the status line configuration from the tips. Restart Claude Code to see changes.","tip":"Focus on metrics that directly impact your workflow (e.g., memory usage for large projects, CPU for complex tasks)."},{"step":"Optimize your system prompt to reduce token waste.","action":"Create a custom system prompt file in `~/.claude/prompts/` and reference it with `--prompt` flag. Start with a minimal prompt and expand only as needed.","tip":"Test different prompt lengths by comparing token counts in the Claude Code UI (enable token display in settings)."},{"step":"Integrate complementary tools like Gemini CLI for parallel processing.","action":"Install gemini-cli via pip, then use it within Claude Code for tasks that can run concurrently (e.g., file analysis, testing).","tip":"Start with `--parallel 2` to avoid overwhelming your system, then increase gradually."},{"step":"Use containerized execution for consistent environments.","action":"Create a Dockerfile in your `.claude/` directory, then run Claude Code with the `--container` flag. Test with a simple command first.","tip":"Mount your project directory as a volume in the container to persist changes between sessions."}]
Customize your status line to display essential project information at a glance.
Utilize slash commands to streamline interactions and manage your Claude Code environment efficiently.
Implement a multi-Claude workflow to enhance productivity through voice input and task automation.
Use Git worktrees for parallel branch work, improving collaboration and version control.
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/ykdojo/claude-code-tipsCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
I need advanced Claude Code optimization tips for [SPECIFIC_TASK]. Give me the most relevant tips from your claude-code-tips collection that will help me [ACHIEVE_GOAL]. Focus on [PARTICULAR_AREA] like performance, debugging, or automation. Include code snippets where helpful.
Here are the most impactful Claude Code tips for automating a Python codebase refactor:
1. **Status Line Customization** (Saves 20% dev time):
```bash
# Add this to your ~/.claude_settings.json
{
"status_line": {
"left": "${project_name} | ${git_branch} | ${time}",
"right": "CPU:${cpu_usage}% | MEM:${memory_usage}MB"
}
}
```
This gives me real-time system metrics without leaving the terminal, helping me spot performance issues during long refactors.
2. **System Prompt Optimization** (Cuts token usage by 40%):
```bash
# Create ~/.claude/prompts/short_system.md
You are an expert Python developer. Focus on clean code and performance.
```
Then run: `claude --prompt short_system.md [YOUR_COMMAND]`
3. **Gemini CLI Integration** (Parallel processing):
```bash
# Install gemini-cli: pip install gemini-cli
# Then use in Claude Code:
claude> @gemini analyze /path/to/code --parallel 4
```
This lets me run 4 analysis tasks simultaneously while keeping the main context focused.
4. **Containerized Execution** (Isolated environments):
```bash
# Create .claude/Dockerfile
FROM claude:latest
COPY . /workspace
WORKDIR /workspace
# Then run:
claude --container .claude/Dockerfile -- "python /workspace/refactor.py"
```
This ensures my refactor runs in a clean environment matching production.
**Pro Tip**: Combine these with the dx plugin for instant project setup:
```bash
claude> @dx python-project --name refactor-2024
```
These optimizations reduced my refactor time from 8 hours to 3.5 hours while improving code quality.Google's multimodal AI model and assistant
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