Repository Analysis

blackboxo/CleanMyWechat

自动删除 Windows 和 Mac 电脑端微信缓存数据,包括从所有聊天中自动下载的大量文件、视频、图片等数据内容,解放你的空间。

14.5 Low AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of blackboxo/CleanMyWechat, a Python project with 5,444 GitHub stars. SynthScan v2.0 examined 5,986 lines of code across 12 source files, recording 96 pattern matches distributed across 4 syntactic categories. The overall adjusted score of 14.5 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).

14.5
Adjusted Score
14.5
Raw Score
100%
Time Factor
2026-07-13
Last Push
5.4K
Stars
Python
Language
6.0K
Lines of Code
12
Files
96
Pattern Hits
2026-07-14
Scan Date
0.00
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

Longitudinal tracking requires multiple scan runs. Once this repository is re-scanned after new commits land, this chart will visualise how the synthetic code signal evolves over time — enabling you to detect whether AI authorship is growing, stabilising, or being actively corrected by human engineers.

No multi-scan history yet — run the scanner again to build trend data.

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 0MEDIUM 14LOW 82

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 96 distinct pattern matches across 4 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.

Excessive Try-Catch Wrapping53 hits · 56 pts
SeverityFileLineSnippetContext
MEDIUMmain.py198def load_json(path, default_value):CODE
MEDIUMmain.py213def format_size(size):CODE
MEDIUMmain.py325def merge_detected_accounts(config):CODE
MEDIUMmain.py382def safe_file_size(path):CODE
MEDIUMmain.py390def is_sub_path(path, root):CODE
MEDIUMmain.py467def mouseMoveEvent(self, QMouseEvent):CODE
MEDIUMmain.py515def center_on_screen(self):CODE
MEDIUMmain.py1131def add_file_if_match(self, file_path, now, day, category, file_list, file_set, CODE
MEDIUMmain.py1887def finish_smart_detect_wechat_path(self, show_config_on_fail=False):CODE
MEDIUMmain.py1913def check_auto_clean_after_start(self):CODE
LOWmain.py30 except Exception:CODE
LOWmain.py40 except Exception:CODE
LOWmain.py49 except Exception:CODE
LOWmain.py203 except Exception as e:CODE
LOWmain.py216 except Exception:CODE
LOWmain.py272 except Exception:CODE
LOWmain.py320 except Exception:CODE
LOWmain.py344 except Exception:CODE
LOWmain.py385 except Exception:CODE
LOWmain.py395 except Exception:CODE
LOWmain.py444 except Exception:CODE
LOWmain.py472 except Exception:CODE
LOWmain.py496 except Exception:CODE
LOWmain.py519 except Exception:CODE
LOWmain.py817 except Exception as e:STRING
LOWmain.py828 except Exception as e:STRING
LOWmain.py834 except Exception as e:STRING
LOWmain.py1165 except Exception:STRING
LOWmain.py1183 except Exception:STRING
LOWmain.py1222 except Exception:STRING
LOWmain.py1272 except Exception:STRING
LOWmain.py1274 except Exception:STRING
LOWmain.py1301 except Exception:STRING
LOWmain.py1583 except Exception:STRING
LOWmain.py1782 except Exception:STRING
LOWmain.py1789 except Exception:STRING
LOWmain.py1890 except Exception:STRING
LOWmain.py1907 except Exception:STRING
LOWmain.py1924 except Exception:STRING
LOWutils/deleteThread.py47 except Exception:CODE
LOWutils/deleteThread.py57 except Exception:CODE
LOWutils/deleteThread.py64 except Exception as e:CODE
LOWutils/selectVersion.py30 except Exception:CODE
LOWutils/selectVersion.py75 except Exception:CODE
LOWutils/selectVersion.py87 except Exception:CODE
LOWutils/selectVersion.py114 except Exception as e:CODE
MEDIUMutils/selectVersion.py115 print("Error occurred:", str(e))CODE
MEDIUMutils/selectVersion.py80def check_dir(file_path):CODE
LOWutils/scanThread.py103 except Exception as e:CODE
MEDIUMutils/scanThread.py104 print(f"Error processing file {file_path}: {e}")CODE
LOWutils/scanThread.py184 except Exception as e:CODE
MEDIUMutils/scanThread.py31def get_file_size(self, path):CODE
LOWutils/multiDeleteThread.py46 except Exception:CODE
Unused Imports19 hits · 12 pts
SeverityFileLineSnippetContext
LOWmain.py55CODE
LOWmain.py55CODE
LOWmain.py55CODE
LOWmain.py55CODE
LOWmain.py58CODE
LOWmain.py58CODE
LOWmain.py58CODE
LOWmain.py59CODE
LOWmain.py62CODE
LOWmain.py63CODE
LOWmain.py64CODE
LOWmain.py64CODE
LOWmain.py64CODE
LOWmain.py66CODE
LOWmain.py68CODE
LOWutils/deleteThread.py1CODE
LOWutils/deleteThread.py1CODE
LOWutils/deleteThread.py1CODE
LOWutils/deleteThread.py2CODE
Deep Nesting14 hits · 10 pts
SeverityFileLineSnippetContext
LOWmain.py258CODE
LOWmain.py277CODE
LOWmain.py325CODE
LOWmain.py583CODE
LOWmain.py808CODE
LOWmain.py1226CODE
LOWmain.py1469CODE
LOWmain.py1552CODE
LOWutils/selectVersion.py47CODE
LOWutils/selectVersion.py156CODE
LOWutils/selectVersion.py180CODE
LOWutils/scanThread.py31CODE
LOWutils/scanThread.py77CODE
LOWutils/scanThread.py107CODE
Hyper-Verbose Identifiers10 hits · 9 pts
SeverityFileLineSnippetContext
LOWmain.py21def install_early_crash_logging():CODE
LOWmain.py675 def apply_global_config_to_ui(self, global_config):STRING
LOWmain.py1531 def parse_preview_detail_line(self, line):STRING
LOWmain.py1887 def finish_smart_detect_wechat_path(self, show_config_on_fail=False):STRING
LOWmain.py1913 def check_auto_clean_after_start(self):STRING
LOWtests/test_select_version_macos.py22 def test_detects_macos_xwechat_account_root(self):CODE
LOWtests/test_select_version_macos.py32 def test_detects_macos_wxwork_users_root(self):CODE
LOWtests/test_select_version_macos.py42 def test_find_all_wechat_paths_includes_macos_candidates(self):CODE
LOWutils/selectVersion.py21def is_wechat_like_account_dir(file_path):CODE
LOWutils/selectVersion.py156def request_macos_private_data_access():CODE