No-Slop OSS, a checklist of contribution best practices when using AI (or not)

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NOSLOP.md

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A checklist of no-slop contribution best practices when using AI (or not) in open source projects.

These days there are so many AI-generated repos and PRs without clear ownership, often referred to as "AI slop". AI use is a reason for the slop, but some cases it's not the only reason. Many new, genuine (human) contributors are simply unfamiliar with open source workflows and project expectations, and AI tools can sometimes amplify those gaps. It results in their contributions getting lost among the noise and getting ignored by maintainers.

This checklist focuses on best practices that help contributors build trust and submit high-quality contributions, whether they use AI or not. It's a checklist for becoming the kind of contributor maintainers enjoy reviewing!

Index

Checklist

1. Contribute with purpose

1. Understand the project well

1. Engage with the project community

1. Set up your project environment thoroughly

1. Understand the project's AI policies

1. Use AI as your tool, not as your replacement

1. Test, validate and document

1. Choose the right issue

1. Starting to work on an issue

1. Communicate early and often

1. Submitting your contribution

1. Follow up

1. What NOT to Do

Note to project maintainers

Contributing

Recommended articles & guides

Closing thoughts

LICENSE

AI Disclosure

Checklist

Follow these guidelines to become a high quality, no-slop OSS contributor! 🌟

☐ 0. Contribute with purpose

Contribute with the goal of creating value for the project, whether you're learning, solving a problem, or giving back to the community.

Focus on making meaningful contributions rather than optimizing for visibility or metrics.

Compete with your own progress, not with others. Choose collaboration over competition.

☐ 1. Understand the project well

Read the project's readme, contributing, and code of conduct files.

Study the project's goals, architecture, and tech stack.

Explore existing issues, discussions, and pull requests to grasp community priorities.

Read recent pull requests to understand the project's coding style, review expectations, and current development priorities.

Check for project-specific guidelines (e.g., design docs, roadmaps, or architecture decisions).

☐ 2. Engage with the project community

If appropriate for the project's community, introduce yourself in its public communication channels (Slack, Discord, mailing lists, etc).

Example: Hi! I'm [Name], and I'd like to contribute to [Project]. I'm particularly interested in [specific area].

Ask relevant questions in public forums, and not privately to avoid duplicating discussions.

Before asking a question, spend a few minutes searching existing issues, discussions, and documentation.

Read first, contribute later i.e. observe community discussions before jumping in.

Follow the project's communication norms (e.g., response times, tone, meeting schedules).

☐ 3. Set up your project environment thoroughly

Fork the repository and clone it locally.

Set up the development environment exactly as documented in the project.

Install dependencies and verify the project runs locally.

Set up pre-commit hooks, linters, or formatters if recommended.

☐ 4. Understand the project's AI policies

Check if the project has AI contribution policies (e.g. AI disclosure requirements).

If the project doesn't mention AI usage, avoid assuming it's acceptable. Consider asking maintainers if disclosure or other expectations aren't clear.

Preferably disclose AI usage in your PR/issue irrespective of whether the project's AI policy demands it.

☐ 5. Use AI as your tool, not as your replacement

Use AI to:

Brainstorm ideas or generate draft code snippets.

Automate repetitive tasks (e.g., formatting, testing scaffolding).

Document complex processes (e.g., setup instructions, troubleshooting).

Never submit AI-generated code without:

Reviewing it line-by-line.

Testing it thoroughly.

Modifying it to fit the project's style.

Make sure you can explain every change you submit, whether it was written by you or assisted by AI.

☐ 6. Test, validate and document

Run the project's test suite and ensure no errors.

Write new tests for your changes.

Manually verify your changes work as intended.

If using AI-generated tests, review them carefully for edge cases.

Update documentation, examples, or changelog entries if your changes affect users.

☐ 7. Choose the right issue

Start small with:

Bug fixes.

Documentation improvements.

Test additions.

Small feature implementations (labeled "good first issue").

Avoid large or ambiguous changes until you're deeply familiar with the project.

Check for "help wanted" or "needs review" labels in the issue tracker.

☐ 8. Starting to work on an issue

Before raising a PR for an issue, check if there's one or more existing PRs for it. In case of existing PRs:

If any of those PRs are actively being updated, don't pick the issue as it could lead to duplicate effort. Find another issue to work on.

If all those PRs are inactive, then you could pick up the issue after confirming with maintainers.

Comment on the issue and confirm with the maintainers before starting work to avoid duplication.

Example: "I'd like to work on this. May I pick this up? I plan to implement it like this: [your brief plan]."

☐ 9. Communicate early and often

For larger changes, ask for feedback on your proposed approach before opening a PR.

Be prepared for your proposed solution to be declined. Not every good idea aligns with a project's roadmap.

Document your thought process in the issue/PR.

Be responsive to feedback and iterate.

☐ 10. Submitting your contribution

If the project has a pull request template, follow it thoroughly.

Keep your pull request focused on a single logical change whenever possible.

Create a new branch for your changes (e.g., fix/issue-123).

Write clear, descriptive commit messages.

Follow the project's conventions (e.g., Fix #123: [description]).

If you used AI tools and if project encourages commit-level AI disclosure, use the project's preferred format (e.g. Assisted-by or Co-authored-by).

If project recommends DCO sign-off, provide one in your commits using Signed-off-by.

Example DCO sign-off along with AI disclosure with Assisted-By in commit:

Improve error handling in user authentication module

• Added custom error classes for authentication failures
• Implemented retry logic for transient failures
• Updated tests to cover new error scenarios

Assisted-by: GitHub Copilot (for new error scenario tests) Signed-off-by: Your Name

Include references to relevant issues in your PR description.

In the PR description:

Disclose AI usage (e.g., "This PR includes AI-assisted code generation for [specific part]").

Explain your process and reasoning.

Link to any related discussions or issues.

☐ 11. Follow up

Monitor your PR for feedback and be ready to make changes.

Give the reviewers time to respond, avoid repeatedly asking for updates (e.g. every few hours).

Thank reviewers for their time and feedback.

If your PR is closed, ask for feedback on how to improve, so you can learn from your mistakes.

Celebrate your contribution, appreciate any help you received from other community members; open source is a community effort!

☐ 12. What NOT to do

Do not submit AI-generated code without reviewing, understanding, and testing it.

Do not ignore community guidelines or communication norms.

Do not submit large changes without prior discussion and approval.

Do not spam the issue tracker or PR queue with low-quality contributions.

Do not rely on AI in place of understanding the codebase or engaging with the community.

Note to project maintainers

Projects are welcome to adopt this checklist as NOSLOP.md, incorporate parts of it into CONTRIBUTING.md, or simply share this repository with contributors.

Contributing

Feel free to raise a PR in case you'd like to add something. Refer to the checklist above for contribution guidelines. All contributions should abide by this code of conduct.

Recommended articles & guides

GitHub's Open Source Guide

How to Responsibly and Effectively Contribute to Open Source Using AI

Maintaining open source in the age of generative AI: Recommendations for maintainers and contributors

The Open Source Way

Closing thoughts

Open source succeeds through people as much as code. Building trust, communicating clearly, and collaborating well are just as important as writing software.

License

AI Disclosure

This checklist has been reviewed with assistance from ChatGPT to improve tone and grammar consistency. All suggestions were manually reviewed before being incorporated.

About

A checklist of no-slop contribution best practices when using AI (or not) in open source projects.

Topics

checklist

awareness

newcomers

ai-ethics

newcontributors

responsible-ai

ethical-development

no-slop

ai-disclosure

oss-contributions

Resources

Readme

License

CC0-1.0 license

Code of conduct

Code of conduct

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