Short version: be decent, assume good faith, and remember there's one person maintaining this in their spare time.
- Be civil. Disagree with the code, the maths, or the decision — not the person. Sharp technical criticism is welcome and useful; contempt isn't.
- Assume good faith. If a metric looks wrong or a decision looks strange, there's usually a reason written down somewhere. Ask before concluding it's carelessness.
- Be patient. Issues get read and answered, but not always quickly, and not in the order they arrived. "Any update on this?" a day later doesn't speed anything up.
- Respect the honesty rules. A recurring theme here is that numbers admit what they don't know, and that the docs don't overclaim. Arguing for a change is fine; pressuring for output that looks more confident than the data supports isn't.
Harassment, personal attacks, discriminatory language, sexualised content, deliberate intimidation, sustained disruption, publishing others' private information, or posting someone else's health data.
Issues and discussions are public and stay public. Please redact health values, dates, names, and device or account identifiers from screenshots and logs before posting. If someone forgets, don't quote or amplify it — flag it and it'll be edited.
Don't ask anyone to share their raw health data publicly to debug something. There's almost always a way to reproduce with a redacted screenshot or a description.
This project produces approximations from published research. It isn't a medical device and nothing it outputs is a diagnosis. Please don't give other users medical advice in issues or discussions, and don't present OpenStrap's numbers to anyone as clinical measurements. If someone posts something that reads as a health scare, point them at an actual clinician.
Applies in all OpenStrap repos — issues, pull requests, discussions, commit messages, and code review.
Email the maintainer at the address on the organisation profile, or report the content to GitHub directly. Reports are handled privately.
Consequences scale with severity and intent: usually a warning and an edit; for repeated or deliberate behaviour, blocking from the org.