codeabra/iai-personal-memory-engine

0

/ 100

Documentation100
Engineering86
Health96
Python295MIT1d ago
Grade a repo

Impressive early momentum. Already polished and picking up traction fast.

The best-benchmarked open-source memory system for AI coding assistants

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

86

Linting and formatting5pt0

No linter or formatter configured.

→ Add [tool.ruff] to pyproject.toml. Ruff handles linting and formatting in one tool and replaces flake8, isort, and black.

Reproducibility6pt70

Lockfile present (mcp-wrapper/package-lock.json). Installs are reproducible.

Tests18pt100

Test files detected (mcp-wrapper/test).

CI/CD14pt100

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

Issue and PR templates6pt100

Issue or PR templates present.

Project health

96

Dependency manifest6pt86

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)
  • 41
    Forks
  • 20
    Releaseslatest 18d ago

Community

  • —
    Community health
  • —
    authors own >50% of commits
  • 295
    Watchers

Responsiveness

  • 1d 18h
    Median issue response
  • 16h
    Median PR merge time
  • 2
    Open issues
Repository files24 root entries
  • .github
    Good: CI is configured (.github/workflows/ci.yml).
    Good: Issue or PR templates present.
  • bench
  • docs
  • mcp-wrapper
    Good: Test files detected (mcp-wrapper/test).
    Good: Lockfile present (mcp-wrapper/package-lock.json). Installs are reproducible.
  • rust
  • scripts
  • src
  • tests
  • .env.example
  • .gitignore
    Good: .gitignore present.
  • BENCHMARKS.md
  • CHANGELOG.md
  • 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.
  • glama.json
  • LICENSE
    Good: Licensed under MIT.
  • logo.png
  • MANIFEST.in
  • NOTICE.md
  • pyproject.toml
    Good: Dependency manifest found (pyproject.toml).
  • README_zh-CN.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
  • SECURITY.md
    Good: Security policy present.
  • setup.py