OpenRubric vs Pawtograder

OpenRubric is a managed judging service for hackathons, handling submission imports, scoring coordination, timeline review, and rankings. Organizers can import projects from a public Devpost URL, upload a CSV, or enter them manually. They set weighted criteria and tracks; judges score each criterion, may add comments, and keep independent records. OpenRubric calculates winners by track and overall, and event data can be exported to CSV at any time. When configured with a GitHub token, it scans repository dates, commits, and contributors as timeline signals for organizers to review. It is not a cheating detector or AI judge: people make scores and award decisions, and the product does not automatically deduct points. AI can draft short summaries for judges, and organizers can switch that off without affecting ranking calculations. The hosted service says it retains event data while an account or event is active and does not sell data or use it for advertising. A partner event is listed at free for one event in kind; managed events are billed at $50 to $100 per event, with larger events quoted before agreement.

Pawtograder combines autograding, manual grading, office hours, discussion, a gradebook, and analytics for computer science courses. Each commit can trigger tests through GitHub Actions, with results shown by test in the grading interface. Rubrics support additive, deductive, and multi-level criteria, line-level annotations, and separate scoring for group members. The gradebook includes MathJS expression columns, drop-lowest calculations, CSV import, and a student what-if mode. Office hours queues support text, video, and screen sharing, and can show linked submissions and failing tests. Discussions can surface relevant threads for known errors and allow public or staff-only posts. Calendar feeds and Discord channel mirroring cover course events; LTI 1.3 integrations with Canvas, Blackboard, Brightspace, and Moodle are listed as roadmap items. Optional AI-generated test hints and an MCP server for compatible AI clients are also listed. Instructors can use the project-hosted community instance or self-host on Kubernetes with Helm charts. The project is GPLv3 open source. The free community instance is for evaluation; ongoing use at scale requires contacting the project.