ExamplesSample Analysis

Sample Analysis

This example shows how the analyzer interprets a mixed portfolio of well-known repositories.

Example Set

RepositoryStarsForksActivityComplexityDifficulty
facebook/react~232k~47k~55~63Advanced
tensorflow/tensorflow~187k~74k~48~72Advanced
torvalds/linux~185k~55k~65~68Advanced
fastapi/fastapi~80k~6k~42~52Intermediate
firstcontributions/first-contributions~45k~75k~60~28Intermediate

What The Results Suggest

  • Linux trends highest on activity because of exceptional contributor count and recent commit volume.
  • TensorFlow trends highest on complexity because of file volume and language diversity.
  • FastAPI stays in the middle because it is active but comparatively focused.
  • first-contributions is active and visible, but structurally simple enough to avoid the Advanced band.

Example JSON Fragment

{
  "generatedAt": "2026-03-15T10:30:00.000Z",
  "summary": {
    "totalAnalyzed": 5,
    "successCount": 5,
    "errorCount": 0,
    "averageActivity": 48.2,
    "averageComplexity": 55.6,
    "difficultyDistribution": {
      "beginner": 0,
      "intermediate": 2,
      "advanced": 3
    }
  },
  "repositories": [
    {
      "url": "https://github.com/facebook/react",
      "name": "facebook/react",
      "metrics": {
        "stars": 232000,
        "forks": 47000,
        "contributors": 1700,
        "commitsLast30d": 95,
        "fileCount": 8500,
        "languageCount": 7,
        "hasDependencyFile": true,
        "dependencyCountEstimate": 68
      },
      "activityScore": { "total": 55.3 },
      "complexityScore": { "total": 62.8 },
      "difficulty": {
        "level": "Advanced",
        "combined": 59.1,
        "description": "Significant experience required"
      }
    }
  ]
}

Reading The Portfolio Summary

The summary object is useful when the goal is not one repository but a ranked set. You can use average activity, average complexity, and difficulty distribution to compare cohorts of repositories rather than individuals.

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