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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).
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.
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.
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.
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.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH⚡ | README.md | 925 | > export ANTHROPIC_API_KEY=your-api-key | CODE |
| HIGH⚡ | README.md | 931 | > export OPENAI_API_KEY=your-api-key | CODE |
| HIGH⚡ | README.md | 937 | > export AZURE_OPENAI_API_KEY=your-api-key | CODE |
| HIGH | README.md | 1154 | export MORPH_API_KEY="your-api-key" | CODE |
| HIGH⚡ | README_zh.md | 631 | > export ANTHROPIC_API_KEY=your-api-key | CODE |
| HIGH⚡ | README_zh.md | 637 | > export OPENAI_API_KEY=your-api-key | CODE |
| HIGH⚡ | README_zh.md | 643 | > export AZURE_OPENAI_API_KEY=your-api-key | CODE |
| HIGH⚡ | lua/avante/init.lua | 52 | --- export ANTHROPIC_API_KEY=your-api-key | CODE |
| HIGH⚡ | lua/avante/init.lua | 53 | --- export OPENAI_API_KEY=your-api-key | CODE |
| HIGH⚡ | lua/avante/init.lua | 54 | --- export AZURE_OPENAI_API_KEY=your-api-key | CODE |
| HIGH | lua/avante/config.lua | 144 | --- export MORPH_API_KEY="your-api-key" | CODE |
| HIGH⚡ | doc/avante.txt | 52 | export ANTHROPIC_API_KEY=your-api-key | CODE |
| HIGH⚡ | doc/avante.txt | 53 | export OPENAI_API_KEY=your-api-key | CODE |
| HIGH⚡ | doc/avante.txt | 54 | export AZURE_OPENAI_API_KEY=your-api-key | CODE |
| HIGH | doc/avante.txt | 344 | export MORPH_API_KEY="your-api-key" | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | README.md | 1329 | ## RAG Service | COMMENT |
| MEDIUM | README.md | 1653 | ### How to disable agentic mode? | COMMENT |
| MEDIUM | README_zh.md | 804 | ## RAG 服务 | COMMENT |
| MEDIUM | py/rag-service/README.md | 1 | # RAG Service Configuration | COMMENT |
| MEDIUM | py/rag-service/src/main.py | 489 | # Initialize embedding model and LLM based on provider using the factory | COMMENT |
| MEDIUM | lua/avante/providers/claude.lua | 617 | if prompt_opts.tools and #prompt_opts.tools > 0 and Config.mode == "agentic" then | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | py/rag-service/src/providers/factory.py | 20 | Initialize embedding model based on specified provider and configuration. Dynamically loads the provider modul | STRING |
| HIGH | py/rag-service/src/providers/factory.py | 104 | Create LLM model with the specified configuration. Dynamically loads the provider module based on the llm_prov | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | py/rag-service/src/main.py | 418 | # # Check if provider or model has changed | COMMENT |
| LOW | py/rag-service/src/main.py | 594 | # Check if the file was recently processed | COMMENT |
| LOW | py/rag-service/src/main.py | 608 | # Check if the text mainly contains printable characters | COMMENT |
| LOW | py/rag-service/src/main.py | 632 | # Check if document with same hash has already been successfully processed | COMMENT |
| LOW⚡ | py/rag-service/src/main.py | 1333 | # Check if the file path starts with the specified directory | STRING |
| LOW⚡ | py/rag-service/src/main.py | 1336 | # Check if directory is a parent of file_path | STRING |
| LOW | py/rag-service/src/main.py | 1193 | # Check if resource already exists | STRING |
| LOW | py/rag-service/src/services/indexing_history.py | 64 | # Check if record exists | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | py/rag-service/src/main.py | 182 | CODE | |
| LOW | py/rag-service/src/main.py | 623 | CODE | |
| LOW | py/rag-service/src/main.py | 734 | CODE | |
| LOW | py/rag-service/src/main.py | 1311 | CODE | |
| LOW | py/rag-service/src/main.py | 1327 | CODE | |
| LOW | py/rag-service/src/services/indexing_history.py | 106 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | py/rag-service/src/providers/factory.py | 61 | except Exception as err: | CODE |
| LOW | py/rag-service/src/providers/factory.py | 88 | except Exception as err: | CODE |
| LOW | py/rag-service/src/providers/factory.py | 149 | except Exception as e: | CODE |
| LOW | py/rag-service/src/providers/factory.py | 171 | except Exception as e: | CODE |
| MEDIUM | lua/avante/repo_map.lua | 154 | print("Error watching directory " .. project_root .. ":", err) | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | py/rag-service/src/main.py | 980 | def append_embedding_sized_documents(doc: Document, base_metadata: dict[str, object] | None = None) -> None: | CODE |
| LOW | py/rag-service/src/main.py | 1059 | async def index_remote_resource_async(resource: Resource) -> None: | CODE |
| LOW | py/rag-service/src/main.py | 1124 | async def index_local_resource_async(resource: Resource) -> None: | CODE |
| LOW | py/rag-service/src/main.py | 362 | def is_remote_resource_exists(url: str) -> bool: | STRING |
| LOW | py/rag-service/src/main.py | 1487 | async def get_indexing_status_for_resource(request: IndexingStatusRequest): # noqa: D103, ANN201 | STRING |
| LOW | py/rag-service/src/services/resource.py | 29 | def update_resource_indexing_status(self, uri: str, indexing_status: str, indexing_status_message: str) -> None: | CODE |
| LOW | py/rag-service/src/services/indexing_history.py | 26 | def delete_indexing_status_by_document_id(self, document_id: str) -> None: | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | py/rag-service/src/main.py | 933 | def update_index_for_file(directory: Path, abs_file_path: Path) -> None: | CODE |
| LOW | py/rag-service/src/libs/logger.py | 16 | logger = logging.getLogger(__name__) | CODE |
| LOW | py/rag-service/src/services/resource.py | 29 | def update_resource_indexing_status(self, uri: str, indexing_status: str, indexing_status_message: str) -> None: | CODE |
| LOW | py/rag-service/src/services/resource.py | 52 | def update_resource_status(self, uri: str, status: str, error: str | None = None) -> None: | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | py/rag-service/src/main.py | 3 | CODE | |
| LOW | py/rag-service/src/providers/factory.py | 8 | CODE | |
| LOW | py/rag-service/src/libs/utils.py | 1 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | lua/avante/suggestion.lua | 188 | L4: # just pass | CODE |
| MEDIUM | lua/avante/libs/acp_client.lua | 5 | ---Avante.nvim now supports the Agent Client Protocol (ACP) (https://agentclientprotocol.com/overview/introduction), ena | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM⚡ | py/rag-service/src/main.py | 1326 | # Create a filter function to only include documents from the specified directory | STRING |
| MEDIUM | py/rag-service/src/main.py | 1360 | # Create a custom post processor | STRING |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | .github/workflows/tests.yaml | 61 | # docker_platform: linux/amd64 | COMMENT |