AI-Powered Repository Evaluation Assistant

Grade student repositories in minutes, not hours.

RubricLM connects to student GitHub repositories, drafts weighted rubrics grounded in real code evidence, and delivers publication-ready Excel workbooks — with every score cited, flagged, and fully overrideable.

CS-301 · Project 2 — REST API

42 of 44 graded · rubric v2 · run #7

● Live
Ana Petrova
8979
33/40
Marcus Lee
7!88
29/40
Priya Nair
99✎8
35/40

Amber = flagged for review · Purple = instructor override · every cell links to cited code

15 min → 90 sec

Per-student grading time

80%+

AI scores accepted unchanged

300 × 8

Gradebook cells at full frame rate

5 sheets

In every exported workbook

Workflow

From assignment brief to final workbook

Five steps from repo links to registrar-ready grades — and you approve everything along the way.

  1. 01

    Connect & import

    Sign in with read-only GitHub access, create a course, then upload a CSV or paste repo URLs. Every link is validated and branch-resolved first.

  2. 02

    Draft the rubric

    RubricLM proposes weighted criteria with performance anchors from your assignment brief. Tune weights until they sum to exactly 100%.

  3. 03

    Run the evaluation

    Repos are cloned and analyzed statically, then scored criterion by criterion while a live board streams progress end to end.

  4. 04

    Review with evidence

    Open any score for cited files, highlighted line ranges, and AI commentary. Override in one click — original scores are preserved.

  5. 05

    Export the workbook

    Download a formatted XLSX with Summary, Rubric Reference, per-student Detail sheets, Evidence Log, and Raw Metrics.

Features

Built for rigor, designed for speed

Automation where it saves time, human judgment where it matters.

🧾

Evidence-grounded scoring

Every score carries at least one citation: file path, line range, and a verbatim quote verified against the repository snapshot.

⚖️

Rubrics in minutes

Four to eight weighted criteria with scoring anchors, drafted from your brief, then editable, reorderable, and fully versioned.

🔬

Static analysis only

LOC, language breakdown, test detection, commit stats, README quality, CI presence — computed without ever executing student code.

🚩

Confidence flags & overrides

Low-confidence scores arrive pre-flagged. Overrides keep the original AI score, author, and timestamp for later calibration.

📡

Live run monitoring

Watch every submission move through clone, extract, grade, and aggregate stages on a streaming status board with smart retries.

📗

Registrar-ready exports

Multi-sheet Excel with frozen headers, color scales, and clickable GitHub permalinks — verified across Excel, Sheets, and LibreOffice.

Trust

Defensible by design

Automated grading only works if you can defend it to a department chair. RubricLM pairs tenant isolation and encryption in transit and at rest with transparent evidence, effortless overrides, and a complete audit history of every action taken in your workspace.

✓

Read-only by design

We request minimum viable GitHub scopes — never write or admin.

✓

FERPA-minded posture

Workspace-scoped records with a documented retention window and automated purge.

✓

Secret scrubbing

Keys, tokens, and connection strings are stripped before any excerpt is stored.

✓

Immutable audit trail

Every override, finalize, and export is logged with actor and timestamp.

Reclaim your weekends this term.

RubricLM is onboarding a limited cohort of pilot instructors for the upcoming semester. Bring one course — we will take it from there.

Free during beta · No credit card · Works with any GitHub-hosted course