Contributing to documentation
Good documentation helps developers succeed with Strands. We welcome contributions that make our docs clearer, more complete, or more helpful. Our documentation lives in the docs repository.
What we accept
We're looking for contributions that improve the developer experience. Documentation changes can range from small typo fixes to complete new guides.
| Type | Description |
|---|---|
| Typo fixes | Spelling, grammar, and formatting corrections |
| Clarifications | Rewording confusing sections |
| New examples | Code samples and tutorials |
| New guides | Complete tutorials or concept pages |
| Community extensions | Documentation for community-built packages |
Setup
!!! warning "Migration in progress" This section will be rewritten as we migrate to a new CMS.
Let's get the docs running locally so you can preview your changes as you work. The docs are built with MkDocs Material.
# Clone the docs repository
git clone https://github.com/strands-agents/docs.git
cd docs
# Create and activate virtual environment
python -m venv .venv
source .venv/bin/activate # On Windows use: .venv\Scripts\activate
# Install dependencies
pip install -e .
# Start the local development server
mkdocs serve
# Preview at http://localhost:8000
The development server automatically reloads when you save changes, so you can see your edits immediately.
Submission process
The submission process varies based on the size of your change. Small fixes can go straight to PR, while larger changes benefit from discussion first.
- Fork the docs repository on GitHub
- Create a branch with a descriptive name like
docs/clarify-tools-usageordocs/fix-typo-agent-loop - Make your changes in your favorite editor
- Preview locally with
mkdocs serveto verify formatting and links work correctly - Submit a pull request with a clear description of what you changed and why
For small changes (typos, grammar fixes, minor clarifications), you can skip local preview and go straight to PR. We'll catch any issues in review.
For larger changes (new guides, significant rewrites), we recommend opening a GitHub Discussion first to align on approach and scope.
Style guidelines
We aim for documentation that teaches, not just describes. A reader finishes understanding the "why" before the "how." This section covers our voice, writing style, and code example conventions.
Voice and tone
Our documentation uses a collaborative, developer-peer voice. We write as knowledgeable colleagues helping you succeed.
| Principle | Example | Why |
|---|---|---|
| Use "you" for the reader | "You create an agent by..." not "An agent is created by..." | Direct and personal |
| Use "we" collaboratively | "Let's install the SDK" not "Install the SDK" | Creates partnership |
| Active voice, present tense | "The agent returns a response" not "A response will be returned" | Clear and immediate |
| Explain why before how | Start with the problem, then the solution | Builds understanding |
Writing style
Keep prose tight and focused. Readers scan documentation looking for answers.
| Do | Don't |
|---|---|
| Keep sentences under 25 words | Write long, complex sentences with multiple clauses |
| Use "to create an agent, call..." | Use "in order to create an agent, you should call..." |
| Include code examples | Describe without showing |
| Use tables for comparisons | Use long bullet lists for structured data |
| Add lead-in sentences before lists | Jump directly into bulleted lists |
Code examples
Code examples are critical—they show developers exactly what to do. Always test your examples before submitting.
- Test all code — every example must actually work
- Include both languages — provide Python and TypeScript when both are supported
- Start simple — show the minimal example first, then add complexity
- Add comments — explain non-obvious parts
- Use realistic names — avoid foo/bar, use descriptive names
# Good: Start simple
from strands import Agent
agent = Agent()
agent("Hello, world!")
# Then show configuration
from strands import Agent
from strands.models import BedrockModel
agent = Agent(
model=BedrockModel(model_id="anthropic.claude-3-sonnet"),
system_prompt="You are a helpful assistant."
)
agent("What's the weather like?")