Repository Analysis

subframe7536/maple-font

Maple Mono: Open source monospace font with round corner, ligatures and Nerd-Font icons for IDE and terminal, fine-grained customization options. 带连字和控制台图标的圆角等宽字体,中英文宽度完美2:1,细粒度的自定义选项

6.8 Low AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of subframe7536/maple-font, a Python project with 27,273 GitHub stars. SynthScan v2.0 examined 14,109 lines of code across 111 source files, recording 65 pattern matches distributed across 9 syntactic categories. The overall adjusted score of 6.8 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).

6.8
Adjusted Score
6.8
Raw Score
100%
Time Factor
2026-07-13
Last Push
27.3K
Stars
Python
Language
14.1K
Lines of Code
111
Files
65
Pattern Hits
2026-07-14
Scan Date
0.02
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 2MEDIUM 9LOW 54

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 65 distinct pattern matches across 9 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.

Decorative Section Separators8 hits · 32 pts
SeverityFileLineSnippetContext
MEDIUMbuild.py49# =========================================================================================COMMENT
MEDIUMbuild.py79# =========================================================================================COMMENT
MEDIUMbuild.py310# =========================================================================================COMMENT
MEDIUMsource/py/feature/calt/tag.py269 # =========================================================COMMENT
MEDIUMsource/py/feature/calt/tag.py271 # ---------------------------------------------------------COMMENT
MEDIUMsource/py/feature/calt/tag.py280 # =========================================================COMMENT
MEDIUMsource/py/feature/calt/tag.py284 # ---------------------------------------------------------COMMENT
MEDIUMsource/py/feature/calt/tag.py291 # =========================================================COMMENT
Deep Nesting18 hits · 18 pts
SeverityFileLineSnippetContext
LOWbuild.py1479CODE
LOWbuild.py1710CODE
LOWbuild.py436CODE
LOWtask.py7CODE
LOWsource/py/in_browser.py19CODE
LOWsource/py/in_browser.py90CODE
LOWsource/py/utils.py263CODE
LOWsource/py/utils.py291CODE
LOWsource/py/freeze.py20CODE
LOWsource/py/task/merge_font/__init__.py192CODE
LOWsource/py/task/merge_font/utils.py298CODE
LOWsource/py/task/merge_font/merger.py15CODE
LOWsource/py/feature/__init__.py48CODE
LOWsource/py/feature/__init__.py143CODE
LOWsource/py/feature/__init__.py231CODE
LOWsource/py/feature/ast.py544CODE
LOWsource/py/feature/ast.py60CODE
LOWsource/py/feature/calt/tag.py133CODE
Over-Commented Block15 hits · 15 pts
SeverityFileLineSnippetContext
LOWbuild.py381 # if not, will use font-patcher to generate fontsCOMMENT
LOWbuild.py841 # self.__instantiate_cn_base(COMMENT
LOWbuild.py881COMMENT
LOWbuild.py921COMMENT
LOWbuild.py941# if feature_record.FeatureTag in config:COMMENT
LOWrequirements.txt1# This file was autogenerated by uv via the following command:COMMENT
LOWrequirements.txt21 # xattrCOMMENT
LOWrequirements.txt41 # via foundrytoolsCOMMENT
LOWrequirements.txt61 # dehinterCOMMENT
LOWrequirements.txt81lxml==6.0.2COMMENT
LOWrequirements.txt101 # via richCOMMENT
LOWrequirements.txt121 # via foundrytoolsCOMMENT
LOWsource/py/utils.py541 # - NameID1 should be the family nameCOMMENT
LOWsource/py/feature/calt/tag.py281 # Mark annotation in XcodeCOMMENT
LOWsource/py/feature/ss/ss03.py1from source.py.feature import astCOMMENT
Excessive Try-Catch Wrapping12 hits · 13 pts
SeverityFileLineSnippetContext
LOWbuild.py74 except Exception as e:CODE
LOWbuild.py474 except Exception as e:CODE
LOWbuild.py700 except Exception as e:CODE
LOWbuild.py1504 except Exception as e:CODE
LOWsource/py/utils.py119 except Exception as e:CODE
LOWsource/py/utils.py130 except Exception as e:CODE
LOWsource/py/utils.py370 except Exception as e:CODE
MEDIUMsource/py/utils.py371 print(f"Error merging fonts: {str(e)}")CODE
LOWsource/py/task/merge_font/__init__.py299 except Exception as e:CODE
LOWsource/py/task/merge_font/__init__.py312 except Exception as e:CODE
LOWsource/py/task/merge_font/utils.py197 except Exception as e:CODE
LOWsource/py/task/merge_font/merger.py84 except Exception:CODE
Hyper-Verbose Identifiers8 hits · 8 pts
SeverityFileLineSnippetContext
LOWbuild.py628 def get_valid_glyph_width_list(self, cn=False):CODE
LOWbuild.py1193def build_nf_by_prebuild_nerd_font(CODE
LOWsource/py/transform.py260def change_glyph_width_or_scale(CODE
LOWsource/py/task/release.py52def update_build_script_version(script_path: str, tag: str):CODE
LOWsource/py/task/nerdfont.py89def get_nerd_font_patcher_args(mono: bool, propo: bool = False):CODE
LOWsource/py/task/merge_font/__init__.py40def copy_to_tmp_with_ascii_name(src_path: str, tmp_dir: str) -> str:CODE
LOWsource/py/feature/__init__.py134def generate_fea_string_cn_only():CODE
LOWsource/py/feature/__init__.py217def get_cv_italic_version_info() -> dict[str, dict[str, str]]:CODE
Docstring Block Structure1 hit · 5 pts
SeverityFileLineSnippetContext
HIGHsource/py/feature/ast.py426 Generate substitution lines for target ligature. Default ``target`` is ``gly(source)`` Default ``lookup_nSTRING
Cross-Language Confusion1 hit · 2 pts
SeverityFileLineSnippetContext
HIGHsource/py/task/merge_font/merger.py31 {"path": "/path/to/override2.ttf", "width_scale": null}STRING
Redundant / Tautological Comments1 hit · 2 pts
SeverityFileLineSnippetContext
LOWbuild.py1257 # Check if the glyph 'nonmarkingreturn' exists in the fontCOMMENT
Modern Structural Boilerplate1 hit · 1 pts
SeverityFileLineSnippetContext
LOWsource/py/task/fea.py36def update_schema(file_path: str, features: dict[str, str]) -> None:CODE