Ways to contribute
Report bugs
Report bugs
Found a bug? Please help us fix it by following these steps:If you are adding an issue, please try to keep it focused on a single topic. If two issues are related, or blocking, please link them rather than combining them. For example,
Search
Check if the issue already exists in our GitHub Issues for the respective repo:
Create issue
If no issue exists, create a new one. When writing, be sure to follow the template provided and to include a minimal, reproducible, example. Attach any relevant labels to the final issue once created. If a project maintainer is unable to reproduce the issue, it is unlikely to be addressed in a timely manner.
Suggest features
Suggest features
Have an idea for a new feature or enhancement?
Search
Search the issues for the respective repository for existing feature requests:
Discuss
If no requests exist, start a new discussion under the relevant category so that project maintainers and the community can provide feedback.
Improve documentation
Improve documentation
Documentation improvements are always welcome! We strive to keep our docs clear and comprehensive, and your perspective can make a big difference.
How to propose changes to the documentation
Guide
Contribute code
Contribute code
With a large userbase, it can be hard for our small team to keep up with all the feature requests and bug fixes. If you have the skills and time, we would love your help!If you start working on an issue, please assign it to yourself or ask a maintainer to do so. This helps avoid duplicate work.If you are looking for something to work on, check out the issues labeled “good first issue” or “help wanted” in our repos:
How to make your first Pull Request
Guide
Add a new integration
Add a new integration
Acceptable uses of LLMs
Generative AI can be a useful tool for contributors, but like any tool should be used with critical thinking and good judgement. We encourage contributors to use AI tools efficiently where they help. However, AI assistance must be paired with meaningful human intervention, judgement, and contextual understanding. If the human effort required to create a pull request is less than the effort required for maintainers to review it, that contribution should not be submitted. We struggle when contributors’ entire work (code changes, documentation updates, pull request descriptions) are LLM-generated. These drive-by contributions often mean well but miss the mark in terms of contextual relevance, accuracy, and quality. Mass automated contributions like these represent a denial-of-service attack on our human effort. We will close pull requests and issues that appear to be low-effort, AI-generated spam. With great tools comes great responsibility.Connect these docs to Claude, VSCode, and more via MCP for real-time answers.