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

6. 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

1. [Claude] Design API spec using the skill
2. [Gemini] ask-gemini "@src/ Analyze existing API patterns" - large-scale codebase analysis
3. [Claude] Implement code based on the analysis
4. [Codex] shell "npm test && npm run build" - test and build
5. [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"

7. 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

8. 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