unilabsim/unilab
Grade a repo

98

/ 100

GradeA

Exemplary work. Strong across project hygiene, engineering, and documentation.

Top 3% of 5,156 graded repos

UniLab: Contract-driven infrastructure for robot learning across physics backends and hardware

Documentation96
Engineering98
Health100
Python983Apache-2.05d ago

Outstanding. A score of 98/100 puts this repo in a very small tier of truly well-engineered projects.

Top fixes

Highest-impact changes first, ranked by point weight

5 to address
  1. 1
    Install and run instructions9pt

    Add a .env.example listing all required environment variables so contributors know what to set up.

  2. 2
    Reproducibility6pt

    Add .github/dependabot.yml with at least one package-ecosystem entry, or a renovate.json, so dependencies are updated automatically.

  3. 3
    Reproducibility6pt

    Use a multi-stage Dockerfile.

  4. 4
    Contributing guide5pt

    Show contributors how to run the test suite (e.g. npm test, pytest, cargo test).

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Scorecard

Every check, grouped by category and sorted worst-first

Documentation

96

Install and run instructions9pt90

README documents how to install the project.

Contributing guide5pt92

Contributing guide is detailed and thorough.

README12pt100

README is present.

License6pt100

Licensed under Apache-2.0.

Engineering

98

Reproducibility6pt80

Lockfile present (uv.lock). Installs are reproducible.

Tests18pt100

Test files detected (scripts/benchmark/smoke_test.py).

CI/CD14pt100

CI is configured (.github/workflows/ci.yml).

Linting and formatting5pt100

Linter or formatter configured ([tool.ruff] / [tool.black] in pyproject.toml).

Issue and PR templates6pt100

Issue or PR templates present.

Project health

100

Dependency manifest6pt100

Dependency manifest found (pyproject.toml).

Repository metadata5pt100

Repository has a description.

Activity5pt100

Actively maintained (pushed within the last month).

Housekeeping3pt100

.gitignore present.

Repository health signals

Activity, community, and responsiveness at scan time

Activity

  • 501 / 1122
    Commits (30d / 90d)
  • 118
    Forks
  • 21
    Releaseslatest 1mo ago

Community

  • 62% - Fair
    Community health
  • 1 bus factorlow
    author own >50% of commits
  • 983
    Watchers

Responsiveness

  • 6d 19h
    Median issue response
  • <1h
    Median PR merge time
  • 27
    Open issues
Repository files20 root entries
  • .github
    Good: CI is configured (.github/workflows/ci.yml).
    Good: Issue or PR templates present.
  • docs
  • scripts
    Good: Test files detected (scripts/benchmark/smoke_test.py).
  • src
  • tests
  • .dockerignore
  • .gitignore
    Good: .gitignore present.
  • .pre-commit-config.yaml
  • AGENTS.md
  • CLAUDE.md
  • CONTRIBUTING.md
    Good: Contributing guide is detailed and thorough.
    Good: Contributing guide includes setup/install instructions.
    Good: Contributing guide describes code style expectations.
    Issue: Contributing guide lacks a testing section (−8 pts).Fix: Show contributors how to run the test suite (e.g. npm test, pytest, cargo test).
    Good: Contributing guide describes the PR/review workflow.
    Good: Contributing guide includes code examples.
  • Dockerfile
    Good: Environment pinned via Dockerfile.
  • LICENSE
    Good: Licensed under Apache-2.0.
  • Makefile
  • pyproject.rocm.toml
  • pyproject.toml
    Good: Dependency manifest found (pyproject.toml).
  • README_zh.md
    Good: README is present.
    Good: README is well structured with multiple sections.
    Good: README includes screenshots or visuals. Great for first impressions.
    Good: README has code examples.
    Good: README links to a live demo or deployed app.
    Good: README includes status badges.
    Good: README documents how to install the project.
    Good: README documents how to run the project.
  • README.md
  • uv.lock
    Good: Lockfile present (uv.lock). Installs are reproducible.
  • uv.rocm.lock
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