https://adongwanai.github.io/AgentGuide | AI Agent开发指南 | LangGraph实战 | 高级RAG | 转行大模型 | 大模型面试 | 算法工程师 | 面试题库 | 强化学习|数据合成
This report presents the forensic synthetic code analysis of adongwanai/AgentGuide, a HTML project with 6,977 GitHub stars. SynthScan v2.0 examined 117,151 lines of code across 215 source files, recording 198 pattern matches distributed across 9 syntactic categories. The overall adjusted score of 4.6 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).
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.
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 198 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.
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM | README.md | 52 | - [📖 技术教程](#-第五步系统学习-agent-技术技术准备) - LangGraph、RAG、上下文工程、监督微调、强化学习 | CODE |
| MEDIUM | README.md | 409 | | **零基础** | 从 [6步学习路径](#-从零到offer的完整路径快速导航) 开始,先建立 Agent / Workflow / RAG / Multi-Agent 的坐标系 | | CODE |
| MEDIUM | README.md | 1977 | # 第四步:搭建第一个 RAG Agent | COMMENT |
| MEDIUM | research/docs/code/03-agents/index.html | 54 | <span class="line"><span style="color:#E1E4E8"> A --> C{需要知识库/RAG?}</span></span> | CODE |
| MEDIUM | projects/04-end-to-end-projects/README.md | 208 | ### [RAG-Anything](https://github.com/HKUDS/RAG-Anything) | COMMENT |
| MEDIUM | resources/tools.md | 115 | ### RAG 技术栈 | COMMENT |
| MEDIUM | resources/tools.md | 262 | ### 场景1:开发 RAG Agent | COMMENT |
| MEDIUM | resources/agent/frameworks.md | 283 | **链接**:https://github.com/ginobefun/agentic-design-patterns-cn | CODE |
| MEDIUM | resources/agent/official-guides.md | 172 | **链接**:https://github.com/ginobefun/agentic-design-patterns-cn | CODE |
| MEDIUM | resources/agent/official-guides.md | 246 | - 阅读 [Agentic Design Patterns](#1-agentic-design-patterns中英对照),理解主流的 Agent 架构思想。 | CODE |
| MEDIUM | resources/agent/official-guides.md | 255 | - 学习 [Multi-Agent 设计模式](#1-agentic-design-patterns中英对照),并尝试在协作场景中进行应用。 | CODE |
| MEDIUM | resources/agent/evaluation-harness.md | 53 | ## 📄 RAG 评估框架 | COMMENT |
| MEDIUM | resources/agent/README.md | 335 | - **链接**:https://github.com/ginobefun/agentic-design-patterns-cn | CODE |
| MEDIUM | resources/agent/README.md | 341 | #### 1. RAG from Scratch ⭐⭐⭐⭐ | COMMENT |
| MEDIUM | resources/rag/projects.md | 208 | ## ⚙️ RAG 引擎与服务 | COMMENT |
| MEDIUM | resources/rag/papers/README.md | 1 | # RAG Papers | COMMENT |
| MEDIUM | resources/rag/papers/agentic_rag/agentic_rag.md | 19 | ## 什么是Agentic RAG? | COMMENT |
| MEDIUM⚡ | resources/rag/papers/agentic_rag/agentic_rag.md | 36 | #### Athina AI RAG Cookbooks ⭐⭐⭐⭐⭐ | COMMENT |
| MEDIUM⚡ | resources/rag/papers/agentic_rag/agentic_rag.md | 42 | #### IBM Granite Agentic RAG | COMMENT |
| MEDIUM⚡ | resources/rag/papers/agentic_rag/agentic_rag.md | 47 | #### NVIDIA Agentic RAG | COMMENT |
| MEDIUM⚡ | resources/rag/papers/agentic_rag/agentic_rag.md | 48 | - **GitHub**: https://github.com/NVIDIA/workbench-example-agentic-rag | CODE |
| MEDIUM⚡ | resources/rag/papers/agentic_rag/agentic_rag.md | 56 | #### Azure GPT-RAG Agentic Orchestrator | COMMENT |
| MEDIUM⚡ | resources/rag/papers/agentic_rag/agentic_rag.md | 57 | - **GitHub**: https://github.com/Azure/gpt-rag-agentic | CODE |
| MEDIUM⚡ | resources/rag/papers/agentic_rag/agentic_rag.md | 61 | #### Hierarchical Multi-Agent RAG | COMMENT |
| MEDIUM⚡ | resources/rag/papers/agentic_rag/agentic_rag.md | 62 | - **GitHub**: https://github.com/lorenzejay/agentic-rag-practical-example | CODE |
| MEDIUM⚡ | resources/rag/papers/agentic_rag/agentic_rag.md | 70 | #### Hugging Face Agentic RAG | COMMENT |
| MEDIUM⚡ | resources/rag/papers/agentic_rag/agentic_rag.md | 71 | - **GitHub**: https://github.com/aymericroucher/agentic-rag-query-reformulation | CODE |
| MEDIUM | resources/rag/papers/agentic_rag/agentic_rag.md | 92 | #### Redis Agentic RAG | COMMENT |
| MEDIUM | resources/rag/papers/agentic_rag/agentic_rag.md | 93 | - **GitHub**: https://github.com/redis-developer/agentic-rag | CODE |
| MEDIUM | resources/rag/papers/agentic_rag/agentic_rag.md | 125 | #### Agentic RAG Survey (2025.01) ⭐⭐⭐⭐⭐ | COMMENT |
| MEDIUM | resources/rag/papers/agentic_rag/agentic_rag.md | 147 | #### Self-RAG (ICLR 2024 Oral) ⭐⭐⭐⭐⭐ | COMMENT |
| MEDIUM | resources/rag/papers/agentic_rag/agentic_rag.md | 558 | - Building Agentic RAG with LlamaIndex: https://www.deeplearning.ai/short-courses/building-agentic-rag-with-llamaindex/ | CODE |
| MEDIUM | resources/rag/papers/agentic_rag/agentic_rag.md | 559 | - AI Agentic Design Patterns with AutoGen: https://www.deeplearning.ai/short-courses/ai-agentic-design-patterns-with-aut | CODE |
| MEDIUM | resources/rag/papers/agentic_rag/agentic_rag.md | 572 | - LlamaIndex Agentic RAG: https://www.llamaindex.ai/blog/agentic-rag-with-llamaindex-2721b8a49ff6 | CODE |
| MEDIUM | resources/rag/papers/agentic_rag/agentic_rag.md | 579 | ### Agentic RAG Survey | COMMENT |
| MEDIUM | resources/rag/papers/agentic_rag/agentic_rag.md | 591 | ### Self-RAG | COMMENT |
| MEDIUM | resources/rag/papers/agentic_rag/README.md | 1 | # Agentic RAG 论文汇总 | COMMENT |
| MEDIUM | resources/rag/papers/agentic_rag/README.md | 15 | ## RAG 与推理(RAG-Reasoning) | COMMENT |
| MEDIUM | resources/rag/papers/agentic_rag/README.md | 72 | ## RAG 系统性思考 | COMMENT |
| MEDIUM | resources/rag/papers/agentic_rag/README.md | 112 | ##### 4. RAG 如何工作?(How RAG Works) | COMMENT |
| MEDIUM | resources/rag/papers/agentic_rag/README.md | 152 | ##### RAG 风险 | COMMENT |
| MEDIUM | resources/rag/papers/multimodal_rag/README.md | 1 | # Multimodal RAG Papers | COMMENT |
| MEDIUM | resources/multimodal/tools-and-projects.md | 1 | # 多模态 RAG 工具与项目清单 | COMMENT |
| MEDIUM | resources/multimodal/tools-and-projects.md | 36 | ## 一体化多模态 RAG | COMMENT |
| MEDIUM | resources/multimodal/tools-and-projects.md | 38 | ### RAG-Anything | COMMENT |
| MEDIUM | resources/multimodal/evaluation-checklist.md | 1 | # 多模态 RAG 评测清单 | COMMENT |
| MEDIUM | resources/multimodal/multimodal-rag-pipeline.md | 1 | # 多模态 RAG 管线 | COMMENT |
| MEDIUM | resources/multimodal/README.md | 1 | # Multimodal RAG 与文档智能资源 | COMMENT |
| MEDIUM | resources/multimodal/README.md | 25 | ### 项目 2:财报多模态 RAG | COMMENT |
| MEDIUM | docs/03-practice/02-high-availability-rag.md | 1 | # 高可用 RAG 系统实战 | COMMENT |
| MEDIUM | docs/03-practice/03-agent-security.md | 109 | ## RAG / 文档 Agent 安全 | COMMENT |
| MEDIUM | docs/archive/2.md | 87 | ### 5. RAG | COMMENT |
| MEDIUM | docs/04-interview/06-development-specialized.md | 32 | ### 高并发 RAG 系统设计 | COMMENT |
| MEDIUM | docs/04-interview/06-development-specialized.md | 37 | - 标签:#系统设计 #高并发 #RAG | CODE |
| MEDIUM | docs/04-interview/06-development-specialized.md | 65 | - 标签:#RAG #流式输出 #系统设计 | CODE |
| MEDIUM | docs/04-interview/06-development-specialized.md | 147 | - 标签:#SaaS #多租户 #RAG | CODE |
| MEDIUM | docs/04-interview/06-development-specialized.md | 183 | - 标签:#知识库 #增量更新 #RAG | CODE |
| MEDIUM | docs/04-interview/06-development-specialized.md | 207 | - 标签:#混合检索 #RAG #系统设计 | CODE |
| MEDIUM | docs/04-interview/06-development-specialized.md | 224 | - 标签:#性能优化 #延迟 #RAG | CODE |
| MEDIUM | docs/04-interview/06-development-specialized.md | 248 | - 标签:#向量检索 #优化 #RAG | CODE |
| 84 more matches not shown… | ||||
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| MEDIUM⚡ | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 2000 | # ============================================================ | COMMENT |
| MEDIUM⚡ | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 2002 | # ============================================================ | COMMENT |
| MEDIUM⚡ | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 2094 | # ============================================================ | COMMENT |
| MEDIUM⚡ | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 2096 | # ============================================================ | COMMENT |
| MEDIUM⚡ | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 2105 | # ============================================================ | COMMENT |
| MEDIUM⚡ | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 2107 | # ============================================================ | COMMENT |
| MEDIUM⚡ | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 2116 | # ============================================================ | COMMENT |
| MEDIUM⚡ | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 2118 | # ============================================================ | COMMENT |
| MEDIUM⚡ | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 2196 | # ============================================================ | COMMENT |
| MEDIUM⚡ | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 2198 | # ============================================================ | COMMENT |
| MEDIUM⚡ | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 2235 | # ============================================================ | COMMENT |
| MEDIUM⚡ | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 2237 | # ============================================================ | COMMENT |
| MEDIUM | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1396 | # ============================================================ | COMMENT |
| MEDIUM | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1398 | # ============================================================ | COMMENT |
| MEDIUM | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1458 | # ============================================================ | COMMENT |
| MEDIUM | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1460 | # ============================================================ | COMMENT |
| MEDIUM | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1476 | # ============================================================ | COMMENT |
| MEDIUM | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1478 | # ============================================================ | COMMENT |
| MEDIUM | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1569 | # ============================================================ | COMMENT |
| MEDIUM | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1571 | # ============================================================ | COMMENT |
| MEDIUM | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1764 | # ============================================================ | COMMENT |
| MEDIUM | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1766 | # ============================================================ | COMMENT |
| MEDIUM | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1874 | # ============================================================ | COMMENT |
| MEDIUM | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1876 | # ============================================================ | COMMENT |
| MEDIUM | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1927 | # ============================================================ | COMMENT |
| MEDIUM | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1929 | # ============================================================ | COMMENT |
| MEDIUM | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1965 | # ============================================================ | COMMENT |
| MEDIUM | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1967 | # ============================================================ | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | CONTRIBUTING.md | 72 | ### Step 1: Fork 项目 | COMMENT |
| LOW⚡ | CONTRIBUTING.md | 76 | ### Step 2: 克隆到本地 | COMMENT |
| LOW⚡ | CONTRIBUTING.md | 83 | ### Step 3: 创建分支 | COMMENT |
| LOW | CONTRIBUTING.md | 96 | ### Step 4: 进行修改 | COMMENT |
| LOW | CONTRIBUTING.md | 102 | ### Step 5: 提交修改 | COMMENT |
| LOW | CONTRIBUTING.md | 120 | ### Step 6: 推送到 GitHub | COMMENT |
| LOW | CONTRIBUTING.md | 126 | ### Step 7: 提交 Pull Request | COMMENT |
| LOW⚡ | …02-tech-stack/22-parlant-agent-compliance-deep-dive.md | 246 | #### Step 1: 引导ARQ阶段 | COMMENT |
| LOW⚡ | …02-tech-stack/22-parlant-agent-compliance-deep-dive.md | 254 | #### Step 2: 响应生成 | COMMENT |
| LOW⚡ | …02-tech-stack/22-parlant-agent-compliance-deep-dive.md | 258 | #### Step 3: 响应验证(可选) | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1994 | except Exception as e: | CODE |
| LOW | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1650 | except Exception as e: | CODE |
| LOW | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 1548 | except Exception as e: | STRING |
| LOW | examples/minimal-agent-loop.md | 40 | except Exception as exc: | CODE |
| LOW | scripts/generate_resources.py | 19 | except Exception: | CODE |
| LOW | scripts/generate_resources.py | 89 | except Exception: | CODE |
| MEDIUM | scripts/generate_resources.py | 15 | def read_text(path): | CODE |
| MEDIUM | scripts/generate_resources.py | 85 | def mtime_date(path): | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| HIGH | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 856 | api_key: "your-api-key" | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW⚡ | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 2200 | def generate_test_cases_from_production_logs(logs, sample_size=100): | CODE |
| LOW⚡ | docs/02-tech-stack/26-agent-evaluation-harness-guide.md | 2239 | def generate_test_cases_with_llm(task_description, num_cases=50): | CODE |
| LOW | external/InterviewGuide/src/lib/path.ts | 54 | function normalizeCompanyRouteName(name: string): string { | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | docs/04-interview/examples/requirements.txt | 1 | # This example uses only the Python standard library. | COMMENT |
| LOW | docs/02-tech-stack/17-claude-code-best-practices.md | 441 | # 适用场景: | COMMENT |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | docs/04-interview/examples/resume_storytelling_check.py | 15 | CODE |
| Severity | File | Line | Snippet | Context |
|---|---|---|---|---|
| LOW | scripts/generate_resources.py | 95 | CODE |