# Set Up Workflow: Developer-Built Claude Code Workflows from OneRedOak
## What This Is
This outlines a collection of pre-built configurations and best practices for the Claude Code AI assistant, sourced from the 'claude-code-workflows' GitHub repository. It demonstrates how to structure projects with context files, integrate with Git for safety, and automate tasks to build applications more efficiently.
Source: https://nisonco.com/how-to-use-claude-code-for-business-complete-2026-guide/
## Before You Start
Scan my workspace and analyze:
- The project language, framework, and directory structure
- Existing AI provider config (check .env, .env.local, config files for API keys — OpenRouter, OpenAI, Anthropic, Google AI, etc.)
Then ask me before proceeding:
1. Which AI provider/API should this use? (Use whatever I already have configured, or ask me to set one up — options include direct provider APIs or a unified service like OpenRouter)
2. Where in my project should this be integrated?
3. Are there any customizations I need (model preferences, naming conventions, constraints)?
## Source Access Note
The source URL (https://nisonco.com/how-to-use-claude-code-for-business-complete-2026-guide/) may not be directly accessible from the terminal. Use the Reference Implementation and Additional Context sections below instead. If you need more details, ask me to paste relevant content from the source.
## What to Implement
This is an **AI Workflow** — an end-to-end automation pattern or integration pipeline.
- Study the workflow architecture from the source and context below
- Identify which parts I can implement locally vs. parts that need external services
- For local parts: implement them using my existing stack and API keys
- For external parts: tell me exactly what services I need and help me configure the integration code
- Wire up any required API calls using keys from my .env files
## Additional Context
- Clone the 'claude-code-workflows' repository from GitHub (github.com/OneRedOak/claude-code-workflows) into a local reference directory to access its configurations.
- Scan the user's active project for a root `CLAUDE.md` file. If none exists, create one and populate it with project-wide context such as common shell commands, coding style rules, and testing frameworks identified in the project.
- Implement the 'plan then execute' workflow for the user's current task: First, generate a detailed implementation plan without writing code. After presenting the plan for user approval, proceed with generating the code based on the approved steps.
## Guidelines
- Adapt everything to my existing project — do not assume a specific stack or directory layout
- Use whichever AI provider I already have configured; if I need a new one, tell me what to sign up for and I'll give you the key
- Check my .env files for existing API keys (OpenRouter, OpenAI, Anthropic, Google AI) before asking me to add one
- Review any fetched code for safety before installing or executing it
- After setup, run a quick verification and show me a summary of exactly what was installed, where, and how to use it