Repository Analysis

yetone/avante.nvim

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3.4 Likely human-written View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of yetone/avante.nvim, a Lua project with 18,035 GitHub stars. SynthScan v2.0 examined 50,075 lines of code across 186 source files, recording 61 pattern matches distributed across 12 syntactic categories. The overall adjusted score of 3.4 places this repository in the Likely human-written 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).

3.4
Adjusted Score
3.4
Raw Score
100%
Time Factor
2026-07-08
Last Push
18.0K
Stars
Lua
Language
50.1K
Lines of Code
186
Files
61
Pattern Hits
2026-07-14
Scan Date
0.09
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 17MEDIUM 10LOW 34

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 61 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.

Magic Placeholder Names15 hits · 105 pts
SeverityFileLineSnippetContext
HIGHREADME.md925> export ANTHROPIC_API_KEY=your-api-keyCODE
HIGHREADME.md931> export OPENAI_API_KEY=your-api-keyCODE
HIGHREADME.md937> export AZURE_OPENAI_API_KEY=your-api-keyCODE
HIGHREADME.md1154 export MORPH_API_KEY="your-api-key"CODE
HIGHREADME_zh.md631> export ANTHROPIC_API_KEY=your-api-keyCODE
HIGHREADME_zh.md637> export OPENAI_API_KEY=your-api-keyCODE
HIGHREADME_zh.md643> export AZURE_OPENAI_API_KEY=your-api-keyCODE
HIGHlua/avante/init.lua52--- export ANTHROPIC_API_KEY=your-api-keyCODE
HIGHlua/avante/init.lua53--- export OPENAI_API_KEY=your-api-keyCODE
HIGHlua/avante/init.lua54--- export AZURE_OPENAI_API_KEY=your-api-keyCODE
HIGHlua/avante/config.lua144--- export MORPH_API_KEY="your-api-key"CODE
HIGHdoc/avante.txt52 export ANTHROPIC_API_KEY=your-api-keyCODE
HIGHdoc/avante.txt53 export OPENAI_API_KEY=your-api-keyCODE
HIGHdoc/avante.txt54 export AZURE_OPENAI_API_KEY=your-api-keyCODE
HIGHdoc/avante.txt344 export MORPH_API_KEY="your-api-key"CODE
Modern AI Meta-Vocabulary6 hits · 17 pts
SeverityFileLineSnippetContext
MEDIUMREADME.md1329## RAG ServiceCOMMENT
MEDIUMREADME.md1653### How to disable agentic mode?COMMENT
MEDIUMREADME_zh.md804## RAG 服务COMMENT
MEDIUMpy/rag-service/README.md1# RAG Service ConfigurationCOMMENT
MEDIUMpy/rag-service/src/main.py489# Initialize embedding model and LLM based on provider using the factoryCOMMENT
MEDIUMlua/avante/providers/claude.lua617 if prompt_opts.tools and #prompt_opts.tools > 0 and Config.mode == "agentic" thenCODE
Docstring Block Structure2 hits · 10 pts
SeverityFileLineSnippetContext
HIGHpy/rag-service/src/providers/factory.py20 Initialize embedding model based on specified provider and configuration. Dynamically loads the provider modulSTRING
HIGHpy/rag-service/src/providers/factory.py104 Create LLM model with the specified configuration. Dynamically loads the provider module based on the llm_provSTRING
Redundant / Tautological Comments8 hits · 9 pts
SeverityFileLineSnippetContext
LOWpy/rag-service/src/main.py418# # Check if provider or model has changedCOMMENT
LOWpy/rag-service/src/main.py594 # Check if the file was recently processedCOMMENT
LOWpy/rag-service/src/main.py608 # Check if the text mainly contains printable charactersCOMMENT
LOWpy/rag-service/src/main.py632 # Check if document with same hash has already been successfully processedCOMMENT
LOWpy/rag-service/src/main.py1333 # Check if the file path starts with the specified directorySTRING
LOWpy/rag-service/src/main.py1336 # Check if directory is a parent of file_pathSTRING
LOWpy/rag-service/src/main.py1193 # Check if resource already existsSTRING
LOWpy/rag-service/src/services/indexing_history.py64 # Check if record existsCOMMENT
Deep Nesting6 hits · 6 pts
SeverityFileLineSnippetContext
LOWpy/rag-service/src/main.py182CODE
LOWpy/rag-service/src/main.py623CODE
LOWpy/rag-service/src/main.py734CODE
LOWpy/rag-service/src/main.py1311CODE
LOWpy/rag-service/src/main.py1327CODE
LOWpy/rag-service/src/services/indexing_history.py106CODE
Excessive Try-Catch Wrapping5 hits · 6 pts
SeverityFileLineSnippetContext
LOWpy/rag-service/src/providers/factory.py61 except Exception as err:CODE
LOWpy/rag-service/src/providers/factory.py88 except Exception as err:CODE
LOWpy/rag-service/src/providers/factory.py149 except Exception as e:CODE
LOWpy/rag-service/src/providers/factory.py171 except Exception as e:CODE
MEDIUMlua/avante/repo_map.lua154 print("Error watching directory " .. project_root .. ":", err)CODE
Hyper-Verbose Identifiers7 hits · 6 pts
SeverityFileLineSnippetContext
LOWpy/rag-service/src/main.py980 def append_embedding_sized_documents(doc: Document, base_metadata: dict[str, object] | None = None) -> None:CODE
LOWpy/rag-service/src/main.py1059async def index_remote_resource_async(resource: Resource) -> None:CODE
LOWpy/rag-service/src/main.py1124async def index_local_resource_async(resource: Resource) -> None:CODE
LOWpy/rag-service/src/main.py362def is_remote_resource_exists(url: str) -> bool:STRING
LOWpy/rag-service/src/main.py1487async def get_indexing_status_for_resource(request: IndexingStatusRequest): # noqa: D103, ANN201STRING
LOWpy/rag-service/src/services/resource.py29 def update_resource_indexing_status(self, uri: str, indexing_status: str, indexing_status_message: str) -> None:CODE
LOWpy/rag-service/src/services/indexing_history.py26 def delete_indexing_status_by_document_id(self, document_id: str) -> None:CODE
Modern Structural Boilerplate4 hits · 4 pts
SeverityFileLineSnippetContext
LOWpy/rag-service/src/main.py933def update_index_for_file(directory: Path, abs_file_path: Path) -> None:CODE
LOWpy/rag-service/src/libs/logger.py16logger = logging.getLogger(__name__)CODE
LOWpy/rag-service/src/services/resource.py29 def update_resource_indexing_status(self, uri: str, indexing_status: str, indexing_status_message: str) -> None:CODE
LOWpy/rag-service/src/services/resource.py52 def update_resource_status(self, uri: str, status: str, error: str | None = None) -> None:CODE
Unused Imports3 hits · 3 pts
SeverityFileLineSnippetContext
LOWpy/rag-service/src/main.py3CODE
LOWpy/rag-service/src/providers/factory.py8CODE
LOWpy/rag-service/src/libs/utils.py1CODE
AI Slop Vocabulary2 hits · 3 pts
SeverityFileLineSnippetContext
LOWlua/avante/suggestion.lua188L4: # just passCODE
MEDIUMlua/avante/libs/acp_client.lua5---Avante.nvim now supports the Agent Client Protocol (ACP) (https://agentclientprotocol.com/overview/introduction), enaCODE
Self-Referential Comments2 hits · 2 pts
SeverityFileLineSnippetContext
MEDIUMpy/rag-service/src/main.py1326 # Create a filter function to only include documents from the specified directorySTRING
MEDIUMpy/rag-service/src/main.py1360 # Create a custom post processorSTRING
Over-Commented Block1 hit · 1 pts
SeverityFileLineSnippetContext
LOW.github/workflows/tests.yaml61 # docker_platform: linux/amd64COMMENT