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Raptor is presented by its builders as an open-source, self-hostable platform for hackathon submissions and judging. Its central idea is to make important decisions—whether a submission meets event rules, how judges score it, and who can change or publish results—more visible and reviewable. The feature descriptions below come from the project authors; they are not an independent software or security audit.
What Raptor is designed to do
Raptor brings submission intake, eligibility review, judging, and event administration into one platform. Its repository describes it as “self-hostable” and “built backend-first,” while the project article presents local operation as a way to avoid requiring a cloud account, external API calls, or participant signup just to run the software. Those are project descriptions, not an independent confirmation of the current release or deployment behavior.
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The underlying principle is straightforward: if software helps determine who receives recognition or money, organizers and participants should be able to inspect the path from submission to result. Raptor’s authors describe workflows intended to support that goal, including review of edge cases, rubric-based scoring, role separation, and audit records.
How Raptor handles submission eligibility
The described workflow checks each project against its GitHub commit history and the hackathon’s event window. A repository that is private, is not hosted on GitHub, or has commits outside the event dates is flagged for organizer review rather than automatically treated as eligible. The project article also says a disqualification should include a permanent written reason.
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This distinction matters: an automated flag is not the same as a final ruling. Organizers still need a documented process for examining unusual cases and recording why a submission was accepted or disqualified. The available description does not independently establish how accurately the checks detect every possible eligibility issue.
How judging scores are calculated
Judges are assigned projects and score them against a rubric, with possible bonus tracks and written feedback. The article says judges can revise their reviews until judging closes. It describes the score flow in this order:
- Apply the rubric’s weights to the judge’s criterion scores.
- Add any applicable bonus points after calculating the weighted component.
- Average the reviews from judges who completed their evaluations for that project.
- Scale the result to the event’s display scale.
This is an explanation of the scoring model, not a reported performance test. The article does not provide enough detail here to establish a universal formula for every event or a specific treatment for all missing-score cases, so organizers should check the configuration and published rules for their own event.
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What judge normalization is meant to address
Judges may use a rubric differently even when they assess the same work: one judge may score generously across the board, while another may be consistently strict. Raptor’s authors describe optional judge-level normalization intended to account for differences in scoring profiles before results are compared.
The authors report simulating 30 judges and 40 projects and say normalization had more impact when judges assessed many projects, with a smaller effect when judges saw fewer. The article excerpt does not publish sufficient underlying data or methods to reproduce the result, and it gives no measured improvement percentage. Normalization is therefore best understood as an available scoring option, not proof that a particular event’s results will become more accurate or fair.
Roles, permissions, and audit records
The project article describes separate capabilities for visitors, participants, judges, organizers, and administrators. Judges are meant to see assigned work; organizers manage event operations and publication; and admin-level access is described as logged. This separation can help limit casual access to other teams’ work or judging decisions, but the feature description is not a security audit and does not establish that every permission boundary is enforced correctly.
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For an organizer evaluating the platform, useful questions include whether role checks happen on the server, which administrative actions are recorded, who can read those records, and how records can be retained or exported. The Dogfood 2026 event brief also identifies role isolation, audit trails, and protection against voting abuse as platform concerns; those priorities belong to the event brief, not a certification of Raptor.
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The builders report a stack consisting of a Next.js web application, a NestJS API, a BullMQ worker, PostgreSQL, and Redis. They describe five Docker Compose services split across an application network and a data network, with the database and Redis not exposed directly and the browser communicating with the API rather than the database.
The authors say that docker compose up is sufficient to start the platform and that operation does not require a cloud account or external API calls. This is a project claim, not a guarantee about every deployment environment or current version. The description gives no hardware minimum, backup procedure, upgrade policy, or production-hardening checklist, so those operational details should be verified against the repository and deployment documentation before using it for a live event.
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Why pinning the evaluated submission matters
Checking commit history only establishes eligibility if the submitted work is tied to the same source that judges later inspect. A repository branch can move after a submission is approved; without a pinned commit, the code presented for evaluation could differ from the evidence that passed the initial check.
In an October 1, 2026 comment, Raptor’s author acknowledged that clean submissions at that point did not store a commit SHA and were not re-checked after review. The author said a fix had been tested locally so judges would resolve a pinned GitHub commit, while GitLab and Bitbucket would use an organizer-confirmed binding; the same comment said the change had not yet been pushed. Accordingly, that fix should not be treated as released based on the comment alone. Before relying on pinning, organizers should verify that the deployed version actually records and evaluates an immutable revision.
What the Dogfood 2026 connection does—and does not—show
Hackathon Raptors described Dogfood 2026 as a challenge to build a submission and judging platform for real self-hosted use. Its event brief lists backend-enforced role isolation, weighted rubrics, normalization, audit trails, voting-abuse protections, documentation, and local operation as areas of concern. The brief’s judging weights—40% tier completion and correctness, 25% judging integrity, 20% adoptability and operability, and 15% code quality and innovation—are Dogfood event criteria, not Raptor’s own judging formula.
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The brief scheduled a 72-hour event for September 25–28, 2026, judging through October 8, and winners for October 9. It also stated a $2,500 prize pool and claimed that Hackathon Raptors had run 35 hackathons across more than 85 countries since 2023. Those are organizer-published event details and claims, not independent measurements of Raptor or its adoption. The brief directs readers to the official event website and Discord for changes; no separate URL for either is included here.
How to assess Raptor for an event
Raptor’s described feature set is relevant to organizers who want a self-hosted workflow with visible eligibility decisions and structured scoring. Before using it for a consequential competition, evaluate the deployed version against the event’s actual needs:
- Eligibility evidence: Confirm which repository hosts are supported, how event windows are configured, and how flagged submissions are reviewed and documented.
- Immutable evaluation: Verify that each approved submission is bound to a specific commit or other immutable revision, and that judges evaluate that same revision.
- Scoring rules: Check rubric weights, bonus handling, judge completion requirements, normalization settings, and how final scores are displayed.
- Permissions and records: Test what each role can access and change, and confirm which actions are logged and how organizers can review records.
- Operations: Validate installation, backups, upgrades, and recovery in the environment where the event will run rather than assuming a local Compose setup answers production needs.
The project article is useful as a description of design goals and reported implementation, but it does not establish independent correctness, security, or current release status. The repository is the appropriate place to check the code and current deployment instructions: Raptor on GitHub. The project-build account and its October 1 comment thread are available at the authors’ Raptor article; the event context appears in the Dogfood 2026 brief.
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