cognizant-ai-lab/neuro-san-studio
Grade a repo

99

/ 100

GradeA

Polished and well engineered. Punching above its star count.

Top 2% of 5,156 graded repos

A playground for neuro-san

Documentation100
Engineering98
Health100
Python584Apache-2.01mo ago

Outstanding. A score of 99/100 puts this repo in a very small tier of truly well-engineered projects.

Top fixes

Highest-impact changes first, ranked by point weight

1 to address
  1. 1
    Reproducibility6pt

    Add .github/dependabot.yml with at least one package-ecosystem entry so dependencies are updated automatically.

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Scorecard

Every check, grouped by category and sorted worst-first

Documentation

100

README12pt100

README is present.

Install and run instructions9pt100

README documents how to install the project.

License6pt100

Licensed under Apache-2.0.

Contributing guide5pt100

Contributing guide is detailed and thorough.

Engineering

98

Reproducibility6pt80

Lockfile present (requirements.txt). Installs are reproducible.

Tests18pt100

Test files detected (apps/wwaw/test_build_wwaw.py).

CI/CD14pt100

CI is configured (.github/workflows/checkmarx.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

  • -
    Commits (30d / 90d)
  • 191
    Forks
  • 34
    Releaseslatest 1y ago

Community

  • 87% - Good
    Community health
  • -
    authors own >50% of commits
  • 584
    Watchers

Responsiveness

  • 5d 8h
    Median issue response
  • <1h
    Median PR merge time
  • 99
    Open issues
Repository files31 root entries
  • .github
    Good: CI is configured (.github/workflows/checkmarx.yml).
    Good: Issue or PR templates present.
  • apps
    Good: Test files detected (apps/wwaw/test_build_wwaw.py).
  • build_scripts
  • coded_tools
  • config
  • deploy
    Good: Environment pinned via deploy/Dockerfile.
  • docs
  • middleware
  • neuro_san_studio
  • registries
  • servers
  • skills
  • tests
  • .env.example
  • .gitattributes
  • .gitignore
    Good: .gitignore present.
  • .lycheeignore
  • .pymarkdownlint.yaml
  • CODE_OF_CONDUCT.md
    Good: Code of conduct present.
  • CONTRIBUTING.md
    Good: Contributing guide is detailed and thorough.
    Good: Contributing guide includes setup/install instructions.
    Good: Contributing guide describes code style expectations.
    Good: Contributing guide explains how to run tests.
    Good: Contributing guide describes the PR/review workflow.
    Good: Contributing guide includes code examples.
  • LICENSE.txt
    Good: Licensed under Apache-2.0.
  • logging.hocon
  • Makefile
  • pyproject.toml
    Good: Dependency manifest found (pyproject.toml).
  • pytest.ini
  • README.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.
  • requirements-build.txt
  • requirements.txt
    Good: Lockfile present (requirements.txt). Installs are reproducible.
  • SECURITY.md
    Good: Security policy present.
  • setup.py
  • SUPPORT.md
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