kpole95/llm-code-review-agent
Grade a repo

100

/ 100

GradeA

Exemplary work. Strong across documentation, engineering, and project hygiene. It just hasn't found an audience yet.

Top 1% of 5,156 graded repos

AI agent that reviews code for bugs and security vulnerabilities across 5 languages, with RAG-grounded findings, suggested fixes, and plain-English explanations. LangGraph + Claude, deployed on AWS.

Documentation100
Engineering100
Health100
Python2MIT3d ago

Perfect 100/100. An exceptionally rare score. This repo is a model of open source craftsmanship.

Working through the fixes? Let every push regrade itself.

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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 MIT.

Contributing guide5pt100

Contributing guide is detailed and thorough.

Engineering

100

Tests18pt100

Test files detected (tests).

CI/CD14pt100

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

Linting and formatting5pt100

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

Reproducibility6pt100

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

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)
  • 0
    Forks
  • 0
    Releases

Community

  • 71% - Fair
    Community health
  • 1 bus factorlow
    author own >50% of commits
  • 2
    Watchers

Responsiveness

  • -
    Median issue response
  • -
    Median PR merge time
  • 4
    Open issues
Repository files17 root entries
  • .github
    Good: CI is configured (.github/workflows/ci.yml).
    Good: Dependabot covers 2 ecosystems (pip, github-actions). Dependencies stay current.
    Good: Issue or PR templates present.
  • .streamlit
  • docker
  • docs
  • knowledge_base
  • src
  • streamlit_app
  • tests
    Good: Test files detected (tests).
  • .dockerignore
  • .env.example
  • .gitignore
    Good: .gitignore 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.
  • docker-compose.yml
    Good: Environment pinned via docker-compose.yml.
  • LICENSE
    Good: Licensed under MIT.
  • pyproject.toml
    Good: Dependency manifest found (pyproject.toml).
  • 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.
  • uv.lock
    Good: Lockfile present (uv.lock). Installs are reproducible.
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