Repository Analysis

microsoft/generative-ai-for-beginners

21 Lessons, Get Started Building with Generative AI

8.3 Low AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of microsoft/generative-ai-for-beginners, a Jupyter Notebook project with 112,965 GitHub stars. SynthScan v2.0 examined 529,491 lines of code across 2445 source files, recording 1169 pattern matches distributed across 14 syntactic categories. The overall adjusted score of 8.3 places this repository in the Low AI signal band.

The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).

8.3
Adjusted Score
8.3
Raw Score
100%
Time Factor
2026-07-14
Last Push
113.0K
Stars
Jupyter Notebook
Language
529.5K
Lines of Code
2.4K
Files
1.2K
Pattern Hits
2026-07-14
Scan Date
0.26
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 0HIGH 628MEDIUM 358LOW 183

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 1169 distinct pattern matches across 14 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Cross-File Repetition615 hits · 3075 pts
SeverityFileLineSnippetContext
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HIGHtranslations/ja/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
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HIGHtranslations/cs/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/te/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/ru/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/tl/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/ro/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/zh-CN/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/uk/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/sr/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
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HIGHtranslations/pt-PT/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/ml/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/kn/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/zh-TW/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
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HIGHtranslations/ar/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/hr/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
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HIGHtranslations/hu/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/nl/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
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HIGHtranslations/de/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/ko/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/fi/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/id/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/fr/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/es/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/et/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/fa/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/lt/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/zh-HK/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
HIGHtranslations/ta/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
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HIGHtranslations/th/05-advanced-prompts/README.md0<h1>books api</h1> <p>a prototype api for retrieving books.</p>STRING
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HIGH20-mistral/README.md0context information is below. --------------------- {retrieved_chunks} --------------------- given the context informatiSTRING
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555 more matches not shown…
Modern AI Meta-Vocabulary354 hits · 1061 pts
SeverityFileLineSnippetContext
MEDIUM10-building-low-code-ai-applications/README.md75[Microsoft Copilot Studio](https://learn.microsoft.com/microsoft-copilot-studio/fundamentals-what-is-copilot-studio?WT.mCODE
MEDIUM20-mistral/README.md33### RAG Example using Mistral Large 2COMMENT
MEDIUM02-exploring-and-comparing-different-llms/README.md163### Retrieval Augmented Generation (RAG)COMMENT
MEDIUM15-rag-and-vector-databases/README.md1# Retrieval Augmented Generation (RAG) and Vector DatabasesCOMMENT
MEDIUM15-rag-and-vector-databases/README.md41## Retrieval Augmented Generation (RAG)COMMENT
MEDIUM15-rag-and-vector-databases/README.md238## Use Cases for using RAG (Retrieval Augmented Generation) and vector databasesCOMMENT
MEDIUMtranslations/sl/20-mistral/README.md31### Primer RAG z uporabo Mistral Large 2COMMENT
MEDIUM…sl/02-exploring-and-comparing-different-llms/README.md162### Generacija z obogatenim pridobivanjem podatkov (RAG)COMMENT
MEDIUMtranslations/sl/15-rag-and-vector-databases/README.md1# Retrieval Augmented Generation (RAG) in vektorske baze podatkovCOMMENT
MEDIUMtranslations/sl/15-rag-and-vector-databases/README.md41## Retrieval Augmented Generation (RAG)COMMENT
MEDIUMtranslations/sl/15-rag-and-vector-databases/README.md45### Kako delujejo RAG (Retrieval Augmented Generation)COMMENT
MEDIUMtranslations/sl/15-rag-and-vector-databases/README.md69### Zakaj uporabiti RAG?COMMENT
MEDIUMtranslations/sl/15-rag-and-vector-databases/README.md237## Primeri uporabe RAG in vektorskih baz podatkovCOMMENT
MEDIUMtranslations/sk/20-mistral/README.md30### Príklad RAG použitia s Mistral Large 2COMMENT
MEDIUM…sk/02-exploring-and-comparing-different-llms/README.md162### Retrieval Augmented Generation (RAG)COMMENT
MEDIUMtranslations/sk/15-rag-and-vector-databases/README.md1# Retrieval Augmented Generation (RAG) a vektorové databázyCOMMENT
MEDIUMtranslations/sk/15-rag-and-vector-databases/README.md41## Retrieval Augmented Generation (RAG)COMMENT
MEDIUMtranslations/sk/15-rag-and-vector-databases/README.md45### Ako fungujú RAG (Retrieval Augmented Generation)COMMENT
MEDIUMtranslations/sk/15-rag-and-vector-databases/README.md69### Prečo používať RAG?COMMENT
MEDIUMtranslations/sk/15-rag-and-vector-databases/README.md237## Príklady použitia RAG (Retrieval Augmented Generation) a vektorových databázCOMMENT
MEDIUMtranslations/ur/20-mistral/README.md31### Mistral Large 2 کا استعمال کرتے ہوئے RAG کی مثالCOMMENT
MEDIUM…ur/02-exploring-and-comparing-different-llms/README.md162### ریٹریول آگمنٹڈ جنریشن (RAG)COMMENT
MEDIUMtranslations/ur/15-rag-and-vector-databases/README.md1# بازیافت میں اضافہ شدہ تخلیق (RAG) اور ویکٹر ڈیٹا بیسزCOMMENT
MEDIUMtranslations/ur/15-rag-and-vector-databases/README.md41## بازیافت میں اضافہ شدہ تخلیق (RAG)COMMENT
MEDIUMtranslations/ur/15-rag-and-vector-databases/README.md45### RAG کیسے کام کرتے ہیں (بازیافت میں اضافہ شدہ تخلیق)COMMENT
MEDIUMtranslations/ur/15-rag-and-vector-databases/README.md69### آپ RAG کیوں استعمال کریں؟COMMENT
MEDIUMtranslations/ur/15-rag-and-vector-databases/README.md237## RAG (بازیافت میں اضافہ شدہ تخلیق) اور ویکٹر ڈیٹا بیسز کے استعمال کے کیسزCOMMENT
MEDIUMtranslations/sw/20-mistral/README.md31### Mfano wa RAG ukitumia Mistral Large 2COMMENT
MEDIUM…sw/02-exploring-and-comparing-different-llms/README.md163### Uzalishaji Ulioimarishwa na Urejeshaji (RAG)COMMENT
MEDIUMtranslations/sw/15-rag-and-vector-databases/README.md1# Kuzalishwa kwa Uboreshaji wa Upataji (RAG) na Hifadhidata za VectorCOMMENT
MEDIUMtranslations/sw/15-rag-and-vector-databases/README.md41## Kuzalishwa kwa Uboreshaji wa Upataji (RAG)COMMENT
MEDIUMtranslations/sw/15-rag-and-vector-databases/README.md45### Jinsi RAG (Kuzalishwa kwa Uboreshaji wa Upataji) hufanya kaziCOMMENT
MEDIUMtranslations/sw/15-rag-and-vector-databases/README.md69### Kwa nini utumie RAG?COMMENT
MEDIUMtranslations/sw/15-rag-and-vector-databases/README.md237## Matumizi ya kutumia RAG (Kuzalishwa kwa Uboreshaji wa Upataji) na hifadhidata za vectorCOMMENT
MEDIUMtranslations/pl/20-mistral/README.md31### Przykład RAG z użyciem Mistral Large 2COMMENT
MEDIUM…pl/02-exploring-and-comparing-different-llms/README.md162### Retrieval Augmented Generation (RAG)COMMENT
MEDIUMtranslations/pl/15-rag-and-vector-databases/README.md1# Retrieval Augmented Generation (RAG) i bazy danych wektorowychCOMMENT
MEDIUMtranslations/pl/15-rag-and-vector-databases/README.md41## Retrieval Augmented Generation (RAG)COMMENT
MEDIUMtranslations/pl/15-rag-and-vector-databases/README.md45### Jak działają RAG (Retrieval Augmented Generation)COMMENT
MEDIUMtranslations/pl/15-rag-and-vector-databases/README.md69### Dlaczego warto używać RAG?COMMENT
MEDIUMtranslations/pl/15-rag-and-vector-databases/README.md238## Przykłady użycia RAG i baz danych wektorowychCOMMENT
MEDIUMtranslations/vi/20-mistral/README.md30### Ví dụ RAG sử dụng Mistral Large 2COMMENT
MEDIUM…vi/02-exploring-and-comparing-different-llms/README.md162### Tạo nội dung tăng cường truy xuất (RAG)COMMENT
MEDIUMtranslations/vi/15-rag-and-vector-databases/README.md1# Retrieval Augmented Generation (RAG) và Cơ sở Dữ liệu VectorCOMMENT
MEDIUMtranslations/vi/15-rag-and-vector-databases/README.md41## Retrieval Augmented Generation (RAG)COMMENT
MEDIUMtranslations/vi/15-rag-and-vector-databases/README.md45### Cách RAG (Retrieval Augmented Generation) hoạt độngCOMMENT
MEDIUMtranslations/vi/15-rag-and-vector-databases/README.md69### Tại sao bạn nên dùng RAG?COMMENT
MEDIUMtranslations/vi/15-rag-and-vector-databases/README.md237## Các trường hợp sử dụng RAG (Retrieval Augmented Generation) và cơ sở dữ liệu vectorCOMMENT
MEDIUMtranslations/sv/20-mistral/README.md31### RAG-exempel med Mistral Large 2COMMENT
MEDIUM…sv/02-exploring-and-comparing-different-llms/README.md162### Retrieval Augmented Generation (RAG)COMMENT
MEDIUMtranslations/sv/15-rag-and-vector-databases/README.md1# Retrieval Augmented Generation (RAG) och vektordatabaserCOMMENT
MEDIUMtranslations/sv/15-rag-and-vector-databases/README.md41## Retrieval Augmented Generation (RAG)COMMENT
MEDIUMtranslations/sv/15-rag-and-vector-databases/README.md237## Användningsområden för RAG (Retrieval Augmented Generation) och vektordatabaserCOMMENT
MEDIUMtranslations/he/20-mistral/README.md30### דוגמה ל-RAG עם Mistral Large 2COMMENT
MEDIUM…he/02-exploring-and-comparing-different-llms/README.md162### יצירת מידע מוגברת על ידי אחזור (RAG)COMMENT
MEDIUMtranslations/he/15-rag-and-vector-databases/README.md1# יצירה מוגברת של שליפה (RAG) ומסדי נתונים וקטורייםCOMMENT
MEDIUMtranslations/he/15-rag-and-vector-databases/README.md41## יצירה מוגברת של שליפה (RAG)COMMENT
MEDIUMtranslations/he/15-rag-and-vector-databases/README.md237## שימושים עבור RAG (יצירה מוגברת של שליפה) ומסדי נתונים וקטורייםCOMMENT
MEDIUMtranslations/ms/20-mistral/README.md30### Contoh RAG menggunakan Mistral Large 2COMMENT
MEDIUM…ms/02-exploring-and-comparing-different-llms/README.md162### Retrieval Augmented Generation (RAG)COMMENT
294 more matches not shown…
Excessive Try-Catch Wrapping114 hits · 114 pts
SeverityFileLineSnippetContext
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Docstring Block Structure11 hits · 55 pts
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Hyper-Verbose Identifiers28 hits · 38 pts
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Unused Imports17 hits · 17 pts
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Self-Referential Comments4 hits · 10 pts
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MEDIUM…ing-search-applications/scripts/transcript_download.py135# Create a request object with the playlist ID and the max resultsCOMMENT
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Synthetic Comment Markers2 hits · 10 pts
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HIGH12-designing-ux-for-ai-applications/README.md64When AI helps inform decisions such as imparting knowledge to future generations, it is critical for teachers and parentCODE
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Structural Annotation Overuse12 hits · 9 pts
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Modern Structural Boilerplate7 hits · 7 pts
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Over-Commented Block2 hits · 2 pts
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LOW.devcontainer/post-create.sh1#!/bin/bashCOMMENT
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Redundant / Tautological Comments1 hit · 2 pts
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Fake / Example Data1 hit · 2 pts
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LOWtests/test_input_validation.py92 assert validate_email("User@Example.COM") == "user@example.com"CODE
Deep Nesting1 hit · 1 pts
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