GitHub Repository Stats

Understanding the health and trajectory of open source projects is critical for making informed technology and investment decisions. GitHub Repository Stats extracts comprehensive analytics from any public GitHub repository, providing detailed insights into commit history, contributor patterns, issue trends, and project activity. This actor transforms raw GitHub data into actionable metrics that help engineering teams, investors, and project managers evaluate repository quality and maintenance status.

What It Does

GitHub Repository Stats scrapes and analyzes public repositories, extracting key metrics that reveal the true state of a project. The actor tracks the complete commit history including authorship, dates, and message content to identify development velocity and activity patterns. It analyzes contributor statistics, showing who contributes most frequently and how contributor diversity has evolved over time. Issue tracking data reveals problem-solving patterns and maintenance quality, while branch information and release history provide context about project stability and release cadence. All data is processed and returned in structured JSON format, making it simple to integrate into dashboards, databases, or analysis workflows.

Who Uses This

Engineering leaders use GitHub Repository Stats to evaluate open source dependencies before adoption, checking that projects maintain active development and responsive maintenance. Venture capital firms and private equity investors analyzing technology companies rely on repository metrics to assess development quality and team productivity. DevTool companies building development platforms integrate this actor to provide clients with competitive intelligence and market insights. Enterprise security teams leverage the data to audit supply chain dependencies and identify dormant or poorly maintained projects. Technical recruiters use repository metrics to evaluate candidate expertise and project contributions.

What You Get Back

The actor returns a comprehensive JSON dataset for each repository containing complete commit history with timestamps, author names, and message content. Contributor statistics include individual contribution counts, commit frequencies, and contribution patterns over time. Issue data captures open issues, closed issues, issue creation dates, and discussion volume. The response includes repository metadata such as star count, fork count, primary language, and last update timestamp. Release information documents version history and deployment patterns. Branch analytics show main branch activity and development branch patterns. All data points come with timestamps enabling trend analysis and comparative evaluation.

Comparison to Alternatives

While GitHub's REST API provides raw data, it lacks the aggregation and analysis capabilities of GitHub Repository Stats. Using the raw API requires extensive post-processing and multiple API calls to construct meaningful metrics. GitOctoverse provides industry-level statistics but lacks the granular repository-specific analysis needed for detailed evaluation. Libraries like PyGithub require substantial custom coding and data manipulation. GitHub Repository Stats delivers pre-processed, aggregated metrics ready for immediate analysis, saving weeks of development and API quota consumption. The actor handles pagination automatically, captures historical data patterns, and calculates derived metrics like contributor trends and activity velocity without additional effort.

Sample JSON Output

{
  "repository": "expressjs/express",
  "owner": "expressjs",
  "name": "express",
  "url": "https://github.com/expressjs/express",
  "description": "Fast, unopinionated, minimalist web framework for node.",
  "stars": 64000,
  "forks": 16500,
  "watchers": 3200,
  "language": "JavaScript",
  "lastUpdate": "2026-03-28T14:22:15Z",
  "commits": [
    {
      "sha": "abc123def456",
      "author": "Author Name",
      "date": "2026-03-28T10:30:00Z",
      "message": "Fix security vulnerability in middleware layer"
    }
  ],
  "contributors": [
    {
      "username": "tjholowaychuk",
      "commits": 523,
      "lastContribution": "2025-10-15T08:22:00Z"
    }
  ],
  "issues": {
    "open": 124,
    "closed": 3450,
    "averageResolutionTime": "4.2 days"
  },
  "releases": {
    "total": 45,
    "latest": "4.18.2",
    "latestDate": "2025-09-10T12:00:00Z"
  }
}

Use Cases

Venture capital firms evaluating technology startups perform due diligence on codebases by analyzing repository health, commit frequency, and contributor diversity. This reveals whether teams have solid engineering practices and maintain code quality. Engineering leaders assessing open source dependencies check that critical libraries receive active maintenance and regular updates, reducing supply chain risk. Development tool companies building integrations, IDE extensions, or API clients analyze competitor repositories to understand their technology choices, architecture patterns, and development velocity. Security teams audit the software supply chain by identifying unmaintained projects with stale codebases and few recent commits, which often signal higher vulnerability risk. Academic researchers studying open source development patterns use the comprehensive metrics to analyze trends in collaboration, contribution models, and project lifecycle.

Pricing

GitHub Repository Stats costs three dollars per one thousand repositories analyzed, with a minimum charge of one dollar per actor run. Analyzing fifty repositories costs approximately fifteen cents, making it affordable for one-off evaluations. Analyzing five hundred repositories costs approximately one dollar and fifty cents. Large-scale market analysis of one thousand repositories costs approximately three dollars. Most users analyze between one hundred and five hundred repositories per run, with average costs between thirty cents and one dollar and fifty cents. Enterprise customers analyzing thousands of repositories monthly often negotiate volume discounts. The flexible pricing model means you pay only for repositories you analyze, with no recurring charges or minimum commitments.

FAQ

Can you analyze private repositories? The actor only accesses public repositories on GitHub. To analyze private repositories, you would need to provide your GitHub authentication credentials, which GitHub Repository Stats does not support for security reasons. Does the actor retrieve all historical data? Yes, GitHub Repository Stats downloads all available commit history, contributor data, and issue records for the repository. For very large repositories with millions of commits, the process takes longer but still completes successfully. Are results cached? Each run retrieves fresh data from GitHub, ensuring complete accuracy. Results are not cached between runs. Can I analyze GitHub Enterprise repositories? The current version only supports GitHub.com public repositories. GitHub Enterprise support is available through a custom integration. What's the typical latency for analyzing repositories? Analyzing one hundred repositories typically takes two to five minutes depending on repository size and GitHub API rate limits. How far back does commit history go? The actor retrieves all available commit history from the repository's creation date forward.