AI Agent Workflow (Workflow & Productivity) When to use this skill Optimize everyday AI agent work Integrate Git/GitHub workflows Use MCP servers Manage and recover sessions Apply productivity techniques 1. Key commands by agent Claude Code commands Command Function When to use /init Auto-generate a CLAUDE.md draft Start a new project /usage Show token usage/reset time Start of every session /clear Clear conversation history When context is polluted; start a new task /context Context window X-Ray When performance degrades /clone Clone the entire conversation A/B experiments; backups /mcp Manage MCP servers Enable/disable MCP !cmd Run immediately without Claude processing Quick status checks Gemini CLI commands Command Function gemini Start a conversation @file Add file context -m model Select model Codex CLI commands Command Function codex Start a conversation codex run Run a command 2. Keyboard shortcuts (Claude Code) Essential shortcuts Shortcut Function Importance Esc Esc Cancel the last task immediately Highest Ctrl+R Search prompt history High Shift+Tab x2 Toggle plan mode High Tab / Enter Accept prompt suggestion Medium Ctrl+B Send to background Medium Ctrl+G Edit in external editor Low Editor editing shortcuts Shortcut Function Ctrl+A Move to start of line Ctrl+E Move to end of line Ctrl+W Delete previous word Ctrl+U Delete to start of line Ctrl+K Delete to end of line 3. Session management Claude Code sessions

Continue the last conversation

claude --continue

Resume a specific session

claude --resume < session-name

Name the session during the conversation

/rename stripe-integration Recommended aliases

~/.zshrc or ~/.bashrc

alias c = 'claude' alias cc = 'claude --continue' alias cr = 'claude --resume' alias g = 'gemini' alias cx = 'codex' 4. Git workflow Auto-generate commit messages "Analyze the changes, write an appropriate commit message, then commit" Auto-generate draft PR "Create a draft PR from the current branch's changes. Make the title summarize the changes, and list the key changes in the body." Use Git worktrees

Work on multiple branches simultaneously

git worktree add .. /myapp-feature-auth feature/auth git worktree add .. /myapp-hotfix hotfix/critical-bug

Independent AI sessions per worktree

Tab

1

~/myapp-feature-auth → new feature development

Tab

2

~/myapp-hotfix → urgent bug fix

Tab

3

~/myapp ( main ) → keep main branch PR review workflow 1. "Run gh pr checkout 123 and summarize this PR's changes" 2. "Analyze changes in src/auth/middleware.ts. Check for security issues or performance problems" 3. "Is there a way to make this logic more efficient?" 4. "Apply the improvements you suggested and run tests" 5. Using MCP servers (Multi-Agent) Key MCP servers MCP server Function Use case Playwright Control web browser E2E tests Supabase Database queries Direct DB access Firecrawl Web crawling Data collection Gemini-CLI Large-scale analysis 1M+ token analysis Codex-CLI Run commands Build, deploy MCP usage examples

Gemini: large-scale analysis

ask-gemini "@src/ Analyze the structure of the entire codebase"

Codex: run commands

shell "docker-compose up -d"

shell "npm test && npm run build" MCP optimization

Disable unused MCP servers

/mcp

Recommended numbers

- MCP servers: fewer than 10

- Active tools: fewer than 80

1. Multi-Agent workflow patterns Orchestration pattern [Claude] Plan → [Gemini] Analysis/research → [Claude] Write code → [Codex] Run/test → [Claude] Synthesize results Practical example: API design + implementation + testing
2. [Claude] Design API spec using the skill
3. [Gemini] ask-gemini "@src/ Analyze existing API patterns" - large-scale codebase analysis
4. [Claude] Implement code based on the analysis
5. [Codex] shell "npm test && npm run build" - test and build
6. [Claude] Create final report TDD workflow "Work using TDD. First write a failing test, then write code that makes the test pass."

The AI:

1. Write a failing test

2. git commit -m "Add failing test for user auth"

3. Write minimal code to pass the test

4. Run tests → confirm they pass

5. git commit -m "Implement user auth to pass test"

1. Container workflow Docker container setup FROM ubuntu:22.04 RUN apt-get update && apt-get install -y \ curl git tmux vim nodejs npm python3 python3-pip RUN curl -fsSL https://claude.ai/install.sh | sh WORKDIR /workspace CMD [ "/bin/bash" ] Safe experimentation environment

Build and run the container

docker build -t ai-sandbox . docker run -it --rm \ -v $( pwd ) :/workspace \ -e ANTHROPIC_API_KEY = $ANTHROPIC_API_KEY \ ai-sandbox

Do experimental work inside the container

1. Troubleshooting When context is overloaded /context

Check usage

/clear

Reset context

Or create HANDOFF.md and start a new session

Cancel a task Esc Esc # Cancel the last task immediately When performance degrades

Check MCP/tool counts

/mcp

Disable unnecessary MCP servers

Reset context

Quick Reference Card === Essential commands === /clear reset context /context check usage /usage check tokens /init generate project description file !command run immediately === Shortcuts === Esc Esc cancel task Ctrl+R search history Shift+Tab×2 plan mode Ctrl+B background === CLI flags === --continue continue conversation --resume resume session -p "prompt" headless mode === Multi-Agent === Claude plan/code generation Gemini large-scale analysis Codex run commands === Troubleshooting === Context overloaded → /clear Cancel task → Esc Esc Performance degradation → check /context