Repository Analysis

joeseesun/qiaomu-anything-to-notebooklm

Claude Skill: Multi-source content processor for NotebookLM. Supports WeChat articles, web pages, YouTube, PDF, Markdown, search queries → Podcast/PPT/MindMap/Quiz etc.

35.4 Strong AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of joeseesun/qiaomu-anything-to-notebooklm, a Python project with 5,553 GitHub stars. SynthScan v2.0 examined 4,624 lines of code across 18 source files, recording 85 pattern matches distributed across 12 syntactic categories. The overall adjusted score of 35.4 places this repository in the Strong 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).

35.4
Adjusted Score
35.4
Raw Score
100%
Time Factor
2026-04-28
Last Push
5.6K
Stars
Python
Language
4.6K
Lines of Code
18
Files
85
Pattern Hits
2026-07-14
Scan Date
0.61
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 11MEDIUM 8LOW 66

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 85 distinct pattern matches across 12 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-Language Confusion10 hits · 65 pts
SeverityFileLineSnippetContext
HIGHfeishu-read-mcp/src/scraper.py188 paragraphs.push(currentPara);CODE
HIGHfeishu-read-mcp/src/scraper.py196 paragraphs.push(currentPara);CODE
HIGHfeishu-read-mcp/src/scraper.py199 paragraphs.push(part);CODE
HIGHfeishu-read-mcp/src/scraper.py393 const text = element.innerText || element.getAttribute('title');CODE
HIGHfeishu-read-mcp/src/scraper.py394 if (text && text.trim()) {CODE
HIGHfeishu-read-mcp/src/scraper.py400 return null;CODE
HIGHfeishu-read-mcp/src/scraper.py236 if (text.length > maxText && text.length > 100) {CODE
HIGHfeishu-read-mcp/src/scraper.py243 return result || document.body.innerHTML;CODE
HIGHfeishu-read-mcp/src/scraper.py364 if (element && element.innerText.trim()) {CODE
HIGHfeishu-read-mcp/src/scraper.py430 urls.push(src);CODE
Decorative Section Separators8 hits · 24 pts
SeverityFileLineSnippetContext
MEDIUMscripts/fetch_url.sh21# ── Paywall domain lists (from BPC source) ──────────────────────────COMMENT
MEDIUMscripts/fetch_url.sh38# ── Helper functions ─────────────────────────────────────────────────COMMENT
MEDIUMscripts/fetch_url.sh126# ── Level 1: Proxy services ─────────────────────────────────────────COMMENT
MEDIUMscripts/fetch_url.sh136# ── Level 2: Site-specific bot UA bypass (BPC core strategy) ─────────COMMENT
MEDIUMscripts/fetch_url.sh190# ── Level 3: Generic paywall bypass (for all paywall domains) ────────COMMENT
MEDIUMscripts/fetch_url.sh327# ── Level 4: archive.today with CAPTCHA handling ────────────────────COMMENT
MEDIUMscripts/fetch_url.sh353# ── Level 5: Google cache ───────────────────────────────────────────COMMENT
MEDIUMscripts/fetch_url.sh368# ── Level 6: agent-fetch (last resort local tool) ───────────────────COMMENT
Unused Imports22 hits · 22 pts
SeverityFileLineSnippetContext
LOWcheck_env.py7CODE
LOWcheck_env.py156CODE
LOWfeishu-read-mcp/src/scraper.py3CODE
LOWfeishu-read-mcp/src/scraper.py4CODE
LOWfeishu-read-mcp/src/scraper.py5CODE
LOWfeishu-read-mcp/src/scraper.py6CODE
LOWfeishu-read-mcp/src/scraper.py6CODE
LOWfeishu-read-mcp/src/scraper.py8CODE
LOWfeishu-read-mcp/src/scraper.py8CODE
LOWfeishu-read-mcp/src/scraper.py12CODE
LOWfeishu-read-mcp/src/scraper.py12CODE
LOWfeishu-read-mcp/src/__init__.py6CODE
LOWfeishu-read-mcp/src/__init__.py7CODE
LOWfeishu-read-mcp/src/__init__.py8CODE
LOWfeishu-read-mcp/src/__init__.py9CODE
LOWfeishu-read-mcp/src/parser.py5CODE
LOWfeishu-read-mcp/src/parser.py6CODE
LOWfeishu-read-mcp/src/parser.py6CODE
LOWfeishu-read-mcp/src/parser.py7CODE
LOWfeishu-read-mcp/src/parser.py7CODE
LOWfeishu-read-mcp/src/image_handler.py8CODE
LOWfeishu-read-mcp/src/image_handler.py13CODE
Structural Annotation Overuse9 hits · 14 pts
SeverityFileLineSnippetContext
LOWSKILL.md179### Step 1: 识别内容源类型COMMENT
LOWSKILL.md202### Step 2: 获取内容COMMENT
LOWSKILL.md269### Step 3: 上传到 NotebookLMCOMMENT
LOWSKILL.md280### Step 4: 深度分析模式(可选)COMMENT
LOWSKILL.md319### Step 5: 根据意图生成内容(可选)COMMENT
LOWscripts/get_podcast_transcript.py93 # Step 1: Create link note via OpenAPICOMMENT
LOWscripts/get_podcast_transcript.py112 # Step 2: Wait for transcriptionCOMMENT
LOWscripts/get_podcast_transcript.py132 # Step 3: Get full transcript via Web APICOMMENT
LOWscripts/get_podcast_transcript.py143 # Step 4: Save as TXTCOMMENT
Excessive Try-Catch Wrapping16 hits · 13 pts
SeverityFileLineSnippetContext
LOWcheck_env.py93 except Exception as e:CODE
LOWcheck_env.py128 except Exception as e:CODE
LOWcheck_env.py159 except Exception as e:CODE
LOWfeishu-read-mcp/test.py44 except Exception as e:CODE
LOWfeishu-read-mcp/test.py80 except Exception as e:STRING
LOWfeishu-read-mcp/test.py100 except Exception as e:CODE
LOWfeishu-read-mcp/test.py127 except Exception as e:CODE
LOWfeishu-read-mcp/src/scraper.py282 except Exception as e:STRING
LOWfeishu-read-mcp/src/scraper.py333 except Exception as e:STRING
LOWfeishu-read-mcp/src/scraper.py442 except Exception as e:STRING
LOWfeishu-read-mcp/src/server.py83 except Exception as e:CODE
LOWfeishu-read-mcp/src/server.py112 except Exception as e:CODE
LOWfeishu-read-mcp/src/image_handler.py147 except Exception as e:CODE
LOWfeishu-read-mcp/src/image_handler.py239 except Exception as e:CODE
LOWfeishu-read-mcp/src/image_handler.py281 except Exception as e:CODE
LOWfeishu-read-mcp/src/image_handler.py299 except Exception as e:CODE
Verbosity Indicators4 hits · 6 pts
SeverityFileLineSnippetContext
LOWscripts/get_podcast_transcript.py93 # Step 1: Create link note via OpenAPICOMMENT
LOWscripts/get_podcast_transcript.py112 # Step 2: Wait for transcriptionCOMMENT
LOWscripts/get_podcast_transcript.py132 # Step 3: Get full transcript via Web APICOMMENT
LOWscripts/get_podcast_transcript.py143 # Step 4: Save as TXTCOMMENT
Deep Nesting6 hits · 6 pts
SeverityFileLineSnippetContext
LOWmain.py16CODE
LOWmain.py315CODE
LOWfeishu-read-mcp/src/scraper.py55CODE
LOWfeishu-read-mcp/src/parser.py340CODE
LOWfeishu-read-mcp/src/image_handler.py203CODE
LOWfeishu-read-mcp/src/image_handler.py285CODE
Magic Placeholder Names1 hit · 5 pts
SeverityFileLineSnippetContext
HIGHREADME.md181export GETNOTE_API_KEY="your_api_key"CODE
Modern Structural Boilerplate5 hits · 5 pts
SeverityFileLineSnippetContext
LOWfeishu-read-mcp/src/scraper.py24logger = logging.getLogger(__name__)CODE
LOWfeishu-read-mcp/src/server.py23logger = logging.getLogger(__name__)CODE
LOWfeishu-read-mcp/src/__init__.py11__all__ = [CODE
LOWfeishu-read-mcp/src/parser.py9logger = logging.getLogger(__name__)CODE
LOWfeishu-read-mcp/src/image_handler.py15logger = logging.getLogger(__name__)CODE
Hyper-Verbose Identifiers2 hits · 2 pts
SeverityFileLineSnippetContext
LOWmain.py113def generate_questions_progressive(content_type):CODE
LOWfeishu-read-mcp/README.md186async def download_with_custom_handler(urls):CODE
Redundant / Tautological Comments1 hit · 2 pts
SeverityFileLineSnippetContext
LOWscripts/fetch_url.sh71 # Check if URL matches any domain in a pipe-separated listCOMMENT
Over-Commented Block1 hit · 1 pts
SeverityFileLineSnippetContext
LOWscripts/fetch_url.sh1#!/usr/bin/env bashCOMMENT