88
/ 100
Well engineered. The main gaps are a reproducible setup and the README.
The Unity Machine Learning Agents Toolkit (ML-Agents) is an open-source project that enables games and simulations to serve as environments for training intelligent agents using deep reinforcement learning and imitation learning.
Top fixes
Highest-impact changes first, ranked by point weight
- 1README12pt
Add a GIF, screenshot, or logo image. It is the fastest way to show what your project does.
- 2README12pt
Show a quick-start snippet so contributors can see what using your project looks like.
- 3Install and run instructions9pt
Add a .env.example listing all required environment variables so contributors know what to set up.
- 4Reproducibility6pt
Commit poetry.lock, uv.lock, pdm.lock, Pipfile.lock, conda-lock.yml, or another lockfile for your Python dependency manager.
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Scorecard
Every check, grouped by category and sorted worst-first
Documentation
80
README is present.
CONTRIBUTING guide found.
README documents how to install the project.
Licensed under Other.
Engineering
89
No dependency lockfile found (−70 pts).
→ Commit poetry.lock, uv.lock, pdm.lock, Pipfile.lock, conda-lock.yml, or another lockfile for your Python dependency manager.
Test files detected (DevProject/Assets/ML-Agents/Scripts/Tests).
CI is configured (.github/workflows/pre-commit.yml).
.NET formatting configured (.editorconfig).
Issue or PR templates present.
Project health
100
Dependency manifest found (setup.cfg).
Repository has a description.
Actively maintained (pushed within the last month).
.gitignore present.
Repository health signals
Activity, community, and responsiveness at scan time
Activity
- 9 / 11Commits (30d / 90d)
- 4,512Forks
- 63Releaseslatest 8y ago
Community
- 75% - GoodCommunity health
- 3 bus factorauthors own >50% of commits
- 19,809Watchers
Responsiveness
- 2hMedian issue response
- 14hMedian PR merge time
- 19Open issues
Repository files42 root entries
- .githubGood: CONTRIBUTING guide found.Issue: CONTRIBUTING guide contents could not be read (−28 pts vs a readable file).Fix: Move the file to the repo root or docs/CONTRIBUTING.md so its setup, style, test, and PR sections can be graded.Good: CI is configured (.github/workflows/pre-commit.yml).Good: Issue or PR templates present.
- .yamato
- colab
- com.unity.ml-agents
- com.unity.ml-agents.tests
- config
- DevProjectGood: Test files detected (DevProject/Assets/ML-Agents/Scripts/Tests).
- docs
- localized_docs
- ml-agents
- ml-agents-envs
- ml-agents-plugin-examples
- ml-agents-trainer-plugin
- PerformanceProject
- Project
- protobuf-definitions
- Tools
- unity-volume
- utils
- .editorconfigGood: .NET formatting configured (.editorconfig).
- .gitattributes
- .gitignoreGood: .gitignore present.
- .gitmodules
- .pre-commit-config.yaml
- .pre-commit-search-and-replace.yaml
- catalog-info.yaml
- CODE_OF_CONDUCT.mdGood: Code of conduct present.
- CODEOWNERS
- colab_requirements.txt
- conftest.py
- DockerfileGood: Environment pinned via Dockerfile.
- LICENSE.mdGood: Licensed under Other.
- markdown-link-check.fast.json
- markdown-link-check.full.json
- mkdocs.yml
- pytest.ini
- Readme.mdGood: README is present.Good: README is well structured with multiple sections.Issue: No screenshots or images in the README (−20 pts).Fix: Add a GIF, screenshot, or logo image. It is the fastest way to show what your project does.Issue: README has no code examples (−15 pts).Fix: Show a quick-start snippet so contributors can see what using your project looks like.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.
- setup.cfgGood: Dependency manifest found (setup.cfg).
- SURVEY.md
- test_constraints_version.txt
- test_requirements.txt
- Third Party Notices.md
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