Repository Analysis

xming521/WeClone

🚀 One-stop solution for creating your AI twin from chat history 💡 Fine-tune LLMs with your chat logs to capture your unique style, then bind to a chatbot to bring your digital self to life.

11.5 Low AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of xming521/WeClone, a Python project with 18,081 GitHub stars. SynthScan v2.0 examined 6,410 lines of code across 52 source files, recording 72 pattern matches distributed across 8 syntactic categories. The overall adjusted score of 11.5 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).

11.5
Adjusted Score
11.5
Raw Score
100%
Time Factor
2026-07-06
Last Push
18.1K
Stars
Python
Language
6.4K
Lines of Code
52
Files
72
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

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 0MEDIUM 0LOW 72

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 72 distinct pattern matches across 8 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 Wrapping21 hits · 21 pts
SeverityFileLineSnippetContext
LOWtests/test_full_pipe.py256 except Exception as e:CODE
LOWtests/test_full_pipe.py317 except Exception as e:CODE
LOWweclone/cli.py227 except Exception as e:CODE
LOWweclone/cli.py252 except Exception as e:CODE
LOWweclone/cli.py269 except Exception as e:CODE
LOWweclone/core/PII/pii_detector.py235 except Exception as e:CODE
LOWweclone/core/inference/online_infer.py123 except Exception as e:CODE
LOWweclone/core/inference/online_infer.py144 except Exception as e:CODE
LOWweclone/core/inference/offline_infer.py74 except Exception as e:CODE
LOWweclone/utils/config.py31 except Exception as e:CODE
LOWweclone/utils/config.py44 except Exception as e:CODE
LOWweclone/utils/log.py122 except Exception as e:CODE
LOWweclone/utils/retry.py65 except Exception as e:CODE
LOWweclone/utils/retry.py112 except Exception as e:CODE
LOWweclone/eval/cli_demo.py26 except Exception:CODE
LOWweclone/data/utils.py32 except Exception as e:CODE
LOWweclone/data/utils.py107 except Exception as e:CODE
LOWweclone/data/qa_generator.py204 except Exception as e:CODE
LOWweclone/data/clean/strategies.py67 except Exception as e:CODE
LOWweclone/data/clean/strategies.py202 except Exception as e:CODE
LOWweclone/data/chat_parsers/telegram_parser.py129 except Exception as e:CODE
Deep Nesting16 hits · 16 pts
SeverityFileLineSnippetContext
LOWtests/test_PII.py31CODE
LOWweclone/core/inference/online_infer.py84CODE
LOWweclone/core/inference/offline_infer.py48CODE
LOWweclone/utils/config.py62CODE
LOWweclone/utils/retry.py9CODE
LOWweclone/utils/retry.py36CODE
LOWweclone/utils/retry.py38CODE
LOWweclone/data/utils.py53CODE
LOWweclone/data/qa_generator.py32CODE
LOWweclone/data/qa_generator.py228CODE
LOWweclone/data/qa_generator.py437CODE
LOWweclone/data/qa_generator.py586CODE
LOWweclone/data/clean/strategies.py78CODE
LOWweclone/data/clean/strategies.py158CODE
LOWweclone/data/chat_parsers/telegram_parser.py38CODE
LOWweclone/data/chat_parsers/telegram_parser.py96CODE
Unused Imports13 hits · 13 pts
SeverityFileLineSnippetContext
LOWtests/test_PII.py2CODE
LOWtests/test_PII.py3CODE
LOWtests/test_PII.py10CODE
LOWtests/test_PII.py20CODE
LOWtests/test_PII.py21CODE
LOWtests/test_full_pipe.py1CODE
LOWtests/test_full_pipe.py7CODE
LOWtests/test_full_pipe.py7CODE
LOWtests/test_full_pipe.py8CODE
LOWweclone/core/PII/__init__.py1CODE
LOWweclone/core/PII/__init__.py1CODE
LOWweclone/core/PII/__init__.py1CODE
LOWweclone/eval/cli_demo.py10CODE
Hyper-Verbose Identifiers12 hits · 12 pts
SeverityFileLineSnippetContext
LOWtests/test_full_pipe.py300def test_full_pipeline_for_config(config_file):CODE
LOWweclone/core/inference/offline_infer.py24def _make_guided_decoding_params(json_schema: dict, disable_any_whitespace: bool = True):CODE
LOWweclone/core/inference/offline_infer.py48def parse_guided_decoding_results(CODE
LOWweclone/utils/config.py51def _flatten_quantization_args(train_sft_args) -> dict:CODE
LOWweclone/utils/config.py62def create_config_by_arg_type(arg_type: str, wc_config: WcConfig) -> BaseModel:CODE
LOWweclone/utils/config.py124def process_config_dict_and_argv(arg_type: str, config_pydantic: BaseModel) -> None:CODE
LOWweclone/utils/log.py110def configure_log_level_from_config():CODE
LOWweclone/data/utils.py53 def _process_images_in_parallel(self, qa_list):CODE
LOWweclone/data/qa_generator.py31class DataProcessor:CODE
LOWweclone/data/qa_generator.py160 def _execute_length_cdf_script(self):CODE
LOWweclone/data/qa_generator.py437 def group_consecutive_messages(self, messages: List[ChatMessage]) -> List[ChatMessage]:CODE
LOWweclone/data/chat_parsers/telegram_parser.py38 def get_message_type_and_content(self, message: Dict) -> tuple[str, str, str, bool]:CODE
Redundant / Tautological Comments3 hits · 4 pts
SeverityFileLineSnippetContext
LOWtests/test_full_pipe.py230 # Check if blocked_words filtering is working correctlyCOMMENT
LOWtests/test_full_pipe.py238 # Check if <image> tags count is correct for Qwen2.5-VL.jsonc configCOMMENT
LOWweclone/utils/i18n.py23 # Check if all lists have the same lengthCOMMENT
Over-Commented Block4 hits · 4 pts
SeverityFileLineSnippetContext
LOW.pre-commit-config.yaml41COMMENT
LOWweclone/utils/length_cdf.py1# Copyright 2025 the LlamaFactory team.COMMENT
LOWweclone/prompts/clean_data.py41# **重要考量:**COMMENT
LOWweclone/prompts/clean_data.py61COMMENT
AI Structural Patterns2 hits · 2 pts
SeverityFileLineSnippetContext
LOWweclone/core/inference/online_infer.py71CODE
LOWweclone/core/inference/offline_infer.py90CODE
Modern Structural Boilerplate1 hit · 1 pts
SeverityFileLineSnippetContext
LOWweclone/core/PII/__init__.py3__all__ = ["PIIResult", "PIIDetector", "ChinesePIIDetector"]CODE