brycewang-stanford/statspai
Grade a repo

99

/ 100

GradeA

Polished and well engineered. Punching above its star count.

Top 2% of 5,156 graded repos

StatsPAI is the first Agent-native Python library for causal inference and applied econometrics — unified API, broad cross-method coverage, structured result objects, machine-readable schemas, Skills, an MCP server, and R/Stata parity validation.

Documentation97
Engineering99
Health100
Python258MIT1mo 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

2 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 a Dockerfile, .nvmrc, or .python-version to pin the runtime version and make the environment reproducible.

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Scorecard

Every check, grouped by category and sorted worst-first

Documentation

97

Install and run instructions9pt90

README documents how to install the project.

README12pt100

README is present.

License6pt100

Licensed under MIT.

Contributing guide5pt100

Contributing guide is detailed and thorough.

Engineering

99

Reproducibility6pt90

Lockfile present (rust/statspai_hdfe/Cargo.lock). Installs are reproducible.

Tests18pt100

Test files detected (src/statspai/diagnostics/late_test.py).

CI/CD14pt100

CI is configured (.github/workflows/build-wheels.yml).

Linting and formatting5pt100

Linter or formatter configured (.flake8).

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)
  • 48
    Forks
  • 26
    Releaseslatest 3mo ago

Community

  • 100% - Good
    Community health
  • 1 bus factorlow
    author own >50% of commits
  • 258
    Watchers

Responsiveness

  • 6h
    Median issue response
  • 2h
    Median PR merge time
  • 4
    Open issues
Repository files43 root entries
  • .cov_decomp
  • .coverage_campaign
  • .examples_campaign
  • .github
    Good: CI is configured (.github/workflows/build-wheels.yml).
    Good: Dependabot covers 3 ecosystems (pip, github-actions, cargo). Dependencies stay current.
    Good: Issue or PR templates present.
  • .tier_eg_campaign
  • .tierd_campaign
  • benchmarks
  • docs
  • examples
  • papers
  • plans
  • rust
    Good: Lockfile present (rust/statspai_hdfe/Cargo.lock). Installs are reproducible.
  • schemas
  • scripts
  • specs
  • src
    Good: Test files detected (src/statspai/diagnostics/late_test.py).
  • StatsPAI_full_data_analysis_skill
  • test-notebooks
  • tests
  • tools
  • .codespellrc
  • .flake8
    Good: Linter or formatter configured (.flake8).
  • .gitignore
    Good: .gitignore present.
  • .pre-commit-config.yaml
  • .zenodo.json
  • CHANGELOG_GITHUB.md
  • CHANGELOG.md
  • CITATION.cff
  • 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.
  • CONTRIBUTORS.md
  • LICENSE
    Good: Licensed under MIT.
  • MANIFEST.in
  • MIGRATION.md
  • mkdocs.yml
  • paper.bib
  • paper.md
  • pyproject.toml
    Good: Dependency manifest found (pyproject.toml).
  • README_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.
  • SUPPORT.md
  • test_results_full_suite.md
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