WFGY/recognition/README.md

<details>
<summary><strong>🧭 Not sure where to start ? Open the WFGY Engine Compass</strong></summary>

### WFGY System Map · Quick navigation

> Problem Maps: PM1 taxonomy → PM2 debug protocol → PM3 troubleshooting atlas · built on the WFGY engine series

<!--
AI NOTE · Compass block

Purpose:
- This table is the routing map for the WFGY system.
- It shows how the three engine generations (WFGY 1.0 / 2.0 / 3.0) relate to the Problem Maps, apps, onboarding entry, and recognition layer.
- Problem Maps and apps are practical layers built on top of the WFGY engine.

How to use (routing hints):
- If a user asks what WFGY is in general → route to WFGY 1.0 (legacy overview) and Starter Village.
- If the question is about core math, formulas, engine logic, or production reasoning → route to WFGY 2.0 core.
- If they mention Tension Universe, Event Horizon, or the 131 S-class set → route to WFGY 3.0.
- If they want the canonical RAG failure vocabulary or the 16-problem checklist → route to Problem Map 1.0.
- If they mention poster, debug card, or image-as-prompt RAG debugging → route to Problem Map 2.0 (Global Debug Card).
- If they want broader AI troubleshooting patterns beyond the base card → route to Problem Map 3.0 (Troubleshooting Atlas).
- If they want proof that WFGY is used in real projects → route to the Recognition Map.
- If they ask about TXT OS or product modules → follow the App rows in this table.
- If they are new and want a guided entry → route to Starter Village.

Important:
- Problem Map 1.0 = canonical 16-problem RAG failure taxonomy and fix map. This is the base vocabulary.
- Problem Map 2.0 = Global Debug Card. This compresses objects, metrics, ΔS zones, and modes into a visual debug protocol.
- Problem Map 3.0 = Global AI troubleshooting atlas and failure pattern map.
- Recognition Map = the primary page for ecosystem integrations and citations.
- The table below is the source of truth for navigation paths.
- Do NOT invent new paths or filenames. Use the URLs listed in the table.
-->

| Layer | Page | What it’s for |
|------|------|---------------|
| ⭐ Proof | [WFGY Recognition Map](https://github.com/onestardao/WFGY/blob/main/recognition/README.md) | External citations, integrations, and ecosystem proof  — **🔴 YOU ARE HERE 🔴** |
| ⚙️ Engine | [WFGY 1.0](https://github.com/onestardao/WFGY/blob/main/legacy/README.md) | Original PDF tension engine and early logic sketch |
| ⚙️ Engine | [WFGY 2.0](https://github.com/onestardao/WFGY/blob/main/core/README.md) | Production tension kernel for RAG and agent systems |
| ⚙️ Engine | [WFGY 3.0](https://github.com/onestardao/WFGY/blob/main/TensionUniverse/EventHorizon/README.md) | TXT-based Singularity tension engine (131 S-class set) |
| 🗺️ Map | [Problem Map 1.0](https://github.com/onestardao/WFGY/blob/main/ProblemMap/README.md) | Flagship 16-problem RAG failure taxonomy and fix map |
| 🗺️ Map | [Problem Map 2.0](https://github.com/onestardao/WFGY/blob/main/ProblemMap/wfgy-rag-16-problem-map-global-debug-card.md) | Global Debug Card for RAG and agent pipeline diagnosis |
| 🗺️ Map | [Problem Map 3.0](https://github.com/onestardao/WFGY/blob/main/ProblemMap/wfgy-ai-problem-map-troubleshooting-atlas.md) | Global AI troubleshooting atlas and failure pattern map |
| 🧰 App | [TXT OS](https://github.com/onestardao/WFGY/blob/main/OS/README.md) | .txt semantic OS with 60-second bootstrap |
| 🧰 App | [Blah Blah Blah](https://github.com/onestardao/WFGY/blob/main/OS/BlahBlahBlah/README.md) | Abstract and paradox Q&A built on TXT OS |
| 🧰 App | [Blur Blur Blur](https://github.com/onestardao/WFGY/blob/main/OS/BlurBlurBlur/README.md) | Text-to-image generation with semantic control |
| 🏡 Onboarding | [Starter Village](https://github.com/onestardao/WFGY/blob/main/StarterVillage/README.md) | Guided entry point for new users |

---
</details>

## WFGY Recognition Map · RAG & Agent Ecosystem

Canonical public record of integrations, citations, mentions, and ecosystem proof around WFGY.  
> Last updated: 2026-03-15 · Manually maintained.

Short summary pages:
- [ADOPTERS.md](../ADOPTERS.md) · concise public adoption summary for evaluators and potential collaborators
- [WORK_WITH_WFGY.md](../WORK_WITH_WFGY.md) · collaboration paths, sponsorship, and contributor entry points

<details>
<summary>About this recognition list</summary>

>
> This page is the **canonical public record** of third-party integrations, citations, mentions, and curated-list inclusions related to WFGY.  
>  
> If you want the **short version** for fast evaluation, see [ADOPTERS.md](../ADOPTERS.md).  
> If you want the **full ecosystem log**, stay on this page.  
>  
> At the current stage, most external recognition is tied to the **WFGY ProblemMap line**, especially the **RAG 16 Problem Map / 16-problem failure checklist**. That is the part most commonly adopted, cited, or adapted by other repositories, docs, and discussions.  
>  
> This does **not** mean that every external project on this page is using the full WFGY ecosystem, or every WFGY module equally. In most cases, the recognized entry point is the **ProblemMap-style diagnostic framework** for RAG, LLM robustness, and reliability workflows.  
>  
> A smaller portion of entries also references **WFGY 3.0 / Singularity Demo** and related stress-test material. Since this is still a transition period, they are kept together in one list for simplicity.  
>  
> This page exists to keep ecosystem recognition in one place, reduce duplication across other docs, and make future updates easier to maintain.  
>  
> If your repository, article, benchmark, documentation page, or discussion has included WFGY, you are welcome to:
> - open a PR
> - open an issue
> - fork and reference this list
> - suggest missing entries or proof links
>  
> Contributions are welcome. If you have cited, integrated, adapted, or discussed WFGY in a public resource, feel free to add it here.  
>  
> ### Scope note
> For accuracy and transparency:
> - the majority of entries below are about the **WFGY ProblemMap / RAG 16 Problem Map** line
> - some entries mention broader **WFGY 3.0** materials
> - this list should be read as a **recognition log and ecosystem proof record**, not as a claim that all listed projects adopted the full WFGY ecosystem
> - this page is the **source-of-truth ledger**, while [ADOPTERS.md](../ADOPTERS.md) is the shorter summary layer

</details>

### 1. Core integrations & research

| Project | Stars | Segment | How it uses WFGY ProblemMap | Proof (PR / doc) |
| --- | --- | --- | --- | --- |
| [LlamaIndex](https://github.com/run-llama/llama_index) | [![GitHub Repo stars](https://img.shields.io/github/stars/run-llama/llama_index?style=social)](https://github.com/run-llama/llama_index) | Mainstream RAG infra | Integrates the WFGY 16-problem RAG failure checklist into its official RAG troubleshooting docs as a structured failure mode reference. | [PR #20760](https://github.com/run-llama/llama_index/pull/20760) |
| [RAGFlow](https://github.com/infiniflow/ragflow) | [![GitHub Repo stars](https://img.shields.io/github/stars/infiniflow/ragflow?style=social)](https://github.com/infiniflow/ragflow) | Mainstream RAG engine | Introduced a RAG failure modes checklist guide to the RAGFlow documentation via PR, adapted from the WFGY 16-problem failure map for step-by-step RAG pipeline diagnostics. | [PR #13204](https://github.com/infiniflow/ragflow/pull/13204) |
| [FlashRAG (RUC NLPIR Lab)](https://github.com/RUC-NLPIR/FlashRAG) | [![GitHub Repo stars](https://img.shields.io/github/stars/RUC-NLPIR/FlashRAG?style=social)](https://github.com/RUC-NLPIR/FlashRAG) | Academic lab / RAG research toolkit | Adapts the **WFGY ProblemMap** as a structured RAG failure checklist in its documentation. The 16-mode taxonomy is cited to support reproducible debugging and systematic failure-mode reasoning for RAG experiments. | [PR #224](https://github.com/RUC-NLPIR/FlashRAG/pull/224) |
| [DeepAgent (RUC NLPIR Lab)](https://github.com/RUC-NLPIR/DeepAgent) | [![GitHub Repo stars](https://img.shields.io/github/stars/RUC-NLPIR/DeepAgent?style=social)](https://github.com/RUC-NLPIR/DeepAgent) | Academic lab / agent research | Adds a **multi-tool agent failure modes troubleshooting note** inspired by WFGY-style debugging concepts for diagnosing tool selection loops, tool misuse, and multi-tool workflow failures in agent pipelines. | [PR #15](https://github.com/RUC-NLPIR/DeepAgent/pull/15#issuecomment-4020600680) |
| [ToolUniverse (Harvard MIMS Lab)](https://github.com/mims-harvard/ToolUniverse) | [![GitHub Repo stars](https://img.shields.io/github/stars/mims-harvard/ToolUniverse?style=social)](https://github.com/mims-harvard/ToolUniverse) | Academic lab / tools | Provides a `WFGY_triage_llm_rag_failure` tool that wraps the 16 mode map for incident triage. | [PR #75](https://github.com/mims-harvard/ToolUniverse/pull/75) |
| [Rankify (University of Innsbruck)](https://github.com/DataScienceUIBK/Rankify) | [![GitHub Repo stars](https://img.shields.io/github/stars/DataScienceUIBK/Rankify?style=social)](https://github.com/DataScienceUIBK/Rankify) | Academic lab / system | Uses the 16 failure patterns in RAG and re-ranking troubleshooting docs. | [PR #76](https://github.com/DataScienceUIBK/Rankify/pull/76) |
| [Multimodal RAG Survey (QCRI LLM Lab)](https://github.com/llm-lab-org/Multimodal-RAG-Survey) | [![GitHub Repo stars](https://img.shields.io/github/stars/llm-lab-org/Multimodal-RAG-Survey?style=social)](https://github.com/llm-lab-org/Multimodal-RAG-Survey) | Academic lab / survey | Cites WFGY as a practical diagnostic resource for multimodal RAG. | [PR #4](https://github.com/llm-lab-org/Multimodal-RAG-Survey/pull/4) |
| [LightAgent](https://github.com/wanxingai/LightAgent) | [![GitHub Repo stars](https://img.shields.io/github/stars/wanxingai/LightAgent?style=social)](https://github.com/wanxingai/LightAgent) | Agent framework | Incorporates WFGY ProblemMap concepts into its documentation via a **Multi-agent troubleshooting (failure map)** section, providing a structured symptom → failure-mode → debugging checklist for diagnosing role drift, cross-agent memory issues, and coordination failures in multi-agent systems. | [PR #24](https://github.com/wanxingai/LightAgent/pull/24#event-23265428525) |
| [OmniRoute](https://github.com/diegosouzapw/OmniRoute) | ![GitHub Repo stars](https://img.shields.io/github/stars/diegosouzapw/OmniRoute?style=social) | Gateway / routing infra | Adds an optional WFGY 16-problem RAG / LLM failure taxonomy to its official troubleshooting documentation, allowing teams to classify downstream RAG and agent failures with `No.1` to `No.16` alongside OmniRoute logs when the gateway itself appears healthy. | [PR #164](https://github.com/diegosouzapw/OmniRoute/pull/164) |




### 2. High-impact curated lists, benchmarks, and ecosystem discussions

| Project | Stars | How it uses WFGY ProblemMap | Proof |
| --- | --- | --- | --- |
| [Awesome LLM Apps](https://github.com/Shubhamsaboo/awesome-llm-apps/) | [![GitHub Repo stars](https://img.shields.io/github/stars/Shubhamsaboo/awesome-llm-apps?style=social)](https://github.com/Shubhamsaboo/awesome-llm-apps) | Includes the **RAG Failure Diagnostics Clinic** tutorial, designed by the WFGY author as a small, framework-agnostic clinic built around the WFGY 16-problem failure map for hands-on RAG debugging. | [PR #520](https://github.com/Shubhamsaboo/awesome-llm-apps/pull/520) |
| [everything-claude-code](https://github.com/affaan-m/everything-claude-code) | [![GitHub Repo stars](https://img.shields.io/github/stars/affaan-m/everything-claude-code?style=social)](https://github.com/affaan-m/everything-claude-code) | Adds a structured troubleshooting concept for memory, context, and agent workflow failures inspired by WFGY-style debugging ideas. The merged documentation update also **closes issue #326**, where the original troubleshooting proposal referencing these ideas was introduced. | [PR #373](https://github.com/affaan-m/everything-claude-code/pull/373) |
| [Awesome Data Science – academic](https://github.com/academic/awesome-datascience) | [![GitHub Repo stars](https://img.shields.io/github/stars/academic/awesome-datascience?style=social)](https://github.com/academic/awesome-datascience) | Lists WFGY as a reference for LLM and RAG diagnostic workflows in data science infrastructure. | [PR #543](https://github.com/academic/awesome-datascience/pull/543) |
| [Awesome AI Apps](https://github.com/Arindam200/awesome-ai-apps/) | [![GitHub Repo stars](https://img.shields.io/github/stars/Arindam200/awesome-ai-apps?style=social)](https://github.com/Arindam200/awesome-ai-apps) | Lists **WFGY 16 Problem Map LLM Debugger** under the *RAG Applications* section as a 16-mode map-based debugger for LLM and RAG bugs, alongside major RAG starter templates and production-ready pipelines. | [PR #144](https://github.com/Arindam200/awesome-ai-apps/pull/144) |
| [Awesome-AITools](https://github.com/ikaijua/Awesome-AITools) | [![GitHub Repo stars](https://img.shields.io/github/stars/ikaijua/Awesome-AITools?style=social)](https://github.com/ikaijua/Awesome-AITools) | Lists WFGY ProblemMap as an open-source RAG failure-mode checklist and diagnostics toolkit for LLM pipelines (data, embeddings, retrievers, tools, evaluation). | [PR #298](https://github.com/ikaijua/Awesome-AITools/pull/298) |
| [Awesome AI in Finance](https://github.com/georgezouq/awesome-ai-in-finance) | [![GitHub Repo stars](https://img.shields.io/github/stars/georgezouq/awesome-ai-in-finance?style=social)](https://github.com/georgezouq/awesome-ai-in-finance) | Lists WFGY as a tool for stress testing and validating RAG-based financial systems. | [PR #45](https://github.com/georgezouq/awesome-ai-in-finance/pull/45) |
| [ruoyi-ai](https://github.com/ageerle/ruoyi-ai) | [![GitHub Repo stars](https://img.shields.io/github/stars/ageerle/ruoyi-ai?style=social)](https://github.com/ageerle/ruoyi-ai) | Includes WFGY in its RAG troubleshooting / FAQ guidance as a reference checklist for diagnosing RAG answer inconsistencies and retrieval-related failures in knowledge base workflows. | [PR #268](https://github.com/ageerle/ruoyi-ai/pull/268#issuecomment-3988269145) |
| [Awesome GPT Super Prompting](https://github.com/CyberAlbSecOP/Awesome_GPT_Super_Prompting) | [![GitHub Repo stars](https://img.shields.io/github/stars/CyberAlbSecOP/Awesome_GPT_Super_Prompting?style=social)](https://github.com/CyberAlbSecOP/Awesome_GPT_Super_Prompting) | Includes **onestardao/WFGY** under Secure Prompting as a structured 16 failure-mode map for RAG and agent pipelines, including prompt injection patterns with practical mitigation checklists. | [Issue #10](https://github.com/CyberAlbSecOP/Awesome_GPT_Super_Prompting/issues/10) |
| [awesome-agentic-patterns](https://github.com/nibzard/awesome-agentic-patterns) | [![GitHub Repo stars](https://img.shields.io/github/stars/nibzard/awesome-agentic-patterns?style=social)](https://github.com/nibzard/awesome-agentic-patterns) | Adds the **Reliability Problem Map Checklist for RAG and Agents** pattern in the Reliability and Eval category, based on the WFGY ProblemMap and linking back to WFGY as a reliability checklist for RAG-heavy agents. | [PR #24](https://github.com/nibzard/awesome-agentic-patterns/pull/24) |
| [Awesome-GraphRAG](https://github.com/DEEP-PolyU/Awesome-GraphRAG) | [![GitHub Repo stars](https://img.shields.io/github/stars/DEEP-PolyU/Awesome-GraphRAG?style=social)](https://github.com/DEEP-PolyU/Awesome-GraphRAG) | Includes **WFGY Problem Map** in its curated GraphRAG resource list as a diagnostic toolkit that defines recurring failure modes in RAG and LLM pipelines, supporting systematic triage and remediation. | [Issue #17 (event)](https://github.com/DEEP-PolyU/Awesome-GraphRAG/issues/17#event-23247141290) |
| [Awesome AI Books](https://github.com/zslucky/awesome-ai-books) | [![GitHub Repo stars](https://img.shields.io/github/stars/zslucky/awesome-ai-books?style=social)](https://github.com/zslucky/awesome-ai-books) | Mentions the WFGY TXT and PDF packs in the LLM reading list. | [PR #14](https://github.com/zslucky/awesome-AI-books/pull/14) |
| [Awesome Explainable AI](https://github.com/wangyongjie-ntu/Awesome-explainable-AI) | [![GitHub Repo stars](https://img.shields.io/github/stars/wangyongjie-ntu/Awesome-explainable-AI?style=social)](https://github.com/wangyongjie-ntu/Awesome-explainable-AI) | Lists **WFGY** among explainable AI tools and resources, referencing it as an open-source framework for analyzing reasoning failures and debugging LLM/RAG systems through structured problem mapping. | [Issue #39](https://github.com/wangyongjie-ntu/Awesome-explainable-AI/issues/39#issuecomment-4016288198) |
| [awesome-ai-ml-dl](https://github.com/neomatrix369/awesome-ai-ml-dl) | [![GitHub Repo stars](https://img.shields.io/github/stars/neomatrix369/awesome-ai-ml-dl?style=social)](https://github.com/neomatrix369/awesome-ai-ml-dl) | Lists **WFGY Problem Map** as a structured 16-problem checklist for diagnosing common RAG and LLM failure modes within its curated AI and machine learning resource collection. | [PR #163](https://github.com/neomatrix369/awesome-ai-ml-dl/pull/163) |
| [Awesome-LLM-RAG-Application](https://github.com/lizhe2004/Awesome-LLM-RAG-Application) | [![GitHub Repo stars](https://img.shields.io/github/stars/lizhe2004/Awesome-LLM-RAG-Application?style=social)](https://github.com/lizhe2004/Awesome-LLM-RAG-Application) | Includes **WFGY 16 Problem Map** as a structured guide for diagnosing retrieval and pipeline failures in RAG applications within its curated list of LLM RAG frameworks and tools. | [PR #9](https://github.com/lizhe2004/Awesome-LLM-RAG-Application/pull/9) ||
| [Awesome AI Web Search (discussion 15)](https://github.com/felladrin/awesome-ai-web-search/discussions/15) | [![GitHub Repo stars](https://img.shields.io/github/stars/felladrin/awesome-ai-web-search?style=social)](https://github.com/felladrin/awesome-ai-web-search) | Discusses the 16 mode map as a candidate taxonomy for RAG failure modes in web search agents. | [Issue #49](https://github.com/felladrin/awesome-ai-web-search/issues/49) |
| [Awesome-AI-Agents](https://github.com/Jenqyang/Awesome-AI-Agents) | [![GitHub Repo stars](https://img.shields.io/github/stars/Jenqyang/Awesome-AI-Agents?style=social)](https://github.com/Jenqyang/Awesome-AI-Agents) | Lists **WFGY 16 Problem Map** as a framework-agnostic debugging and evaluation checklist for LLM agents and RAG systems, covering common failure modes across retrieval, vector stores, prompts, tools, and deployment workflows. | [PR #68](https://github.com/Jenqyang/Awesome-AI-Agents/pull/68#event-23251915496) 

### 3. Other public mentions

| Project | Stars | How it uses WFGY ProblemMap |
| --- | --- | --- |
| [awesome-data-analysis](https://github.com/PavelGrigoryevDS/awesome-data-analysis) | [![GitHub Repo stars](https://img.shields.io/github/stars/PavelGrigoryevDS/awesome-data-analysis?style=social)](https://github.com/PavelGrigoryevDS/awesome-data-analysis) | Includes **WFGY Problem Map** in its curated data science repository list as a MIT-licensed checklist for diagnosing RAG / LLM pipeline failures and improving reliability in AI-driven data workflows. |
| [awesome-gpt-security](https://github.com/cckuailong/awesome-gpt-security) | [![GitHub Repo stars](https://img.shields.io/github/stars/cckuailong/awesome-gpt-security?style=social)](https://github.com/cckuailong/awesome-gpt-security) | Includes **WFGY Problem Map** in its GPT security resource list as a structured diagnostic handbook that catalogs common failure modes in RAG/agent systems, helping practitioners go from symptom identification to concrete remediation. |
| [machine-learning-repos](https://github.com/recodehive/machine-learning-repos) | [![GitHub Repo stars](https://img.shields.io/github/stars/recodehive/machine-learning-repos?style=social)](https://github.com/recodehive/machine-learning-repos) | Lists **WFGY** under GitHub resources as an open-source framework for debugging LLM agents and RAG pipelines, highlighting the 16-mode ProblemMap and practical triage checklists. |
| [Awesome AI System](https://github.com/lambda7xx/awesome-AI-system) | [![GitHub Repo stars](https://img.shields.io/github/stars/lambda7xx/awesome-AI-system?style=social)](https://github.com/lambda7xx/awesome-AI-system) | Lists WFGY under LLM robustness and debugging infrastructure. |
| [free-ai-agents-resources](https://github.com/avinash201199/free-ai-agents-resources) | [![GitHub Repo stars](https://img.shields.io/github/stars/avinash201199/free-ai-agents-resources?style=social)](https://github.com/avinash201199/free-ai-agents-resources) | Lists **onestardao/WFGY** as an open-source framework for debugging and stress testing LLM agents and RAG pipelines, highlighting the 16-problem failure map and reproducible prompt-driven triage workflow. |
| [Awesome-AI](https://github.com/cssmagic/Awesome-AI) | [![GitHub Repo stars](https://img.shields.io/github/stars/cssmagic/Awesome-AI?style=social)](https://github.com/cssmagic/Awesome-AI) | Includes **WFGY 16 Problem Map** in its RAG resources section, describing it as an open-source diagnostic framework that helps developers debug common failure patterns in LLM and RAG pipelines. |
| [Awesome AI Tools](https://github.com/eudk/awesome-ai-tools) | [![GitHub Repo stars](https://img.shields.io/github/stars/eudk/awesome-ai-tools?style=social)](https://github.com/eudk/awesome-ai-tools) | Includes WFGY as an open-source framework for debugging LLM agents and RAG pipelines. |
| [LLM-Agent-Benchmark-List](https://github.com/zhangxjohn/LLM-Agent-Benchmark-List) | [![GitHub Repo stars](https://img.shields.io/github/stars/zhangxjohn/LLM-Agent-Benchmark-List?style=social)](https://github.com/zhangxjohn/LLM-Agent-Benchmark-List) | Lists **WFGY 3.0 · Singularity Demo (BlackHole-131)** as a long-horizon, text-only stress test for LLM agents, covering 131 S-class problems for tension-based reasoning and robustness evaluation. |
| [Awesome-Data-Science](https://github.com/natnew/Awesome-Data-Science/blob/main/docs/generative-ai.md) | [![GitHub Repo stars](https://img.shields.io/github/stars/natnew/Awesome-Data-Science?style=social)](https://github.com/natnew/Awesome-Data-Science) | Adds **WFGY ProblemMap** under “Practical Guides & Debugging” as a reference for diagnosing and fixing RAG/LLM pipeline failures. |
| [Awesome-Prompt-Engineering-ZH-CN](https://github.com/yunwei37/Awesome-Prompt-Engineering-ZH-CN) | [![GitHub Repo stars](https://img.shields.io/github/stars/yunwei37/Awesome-Prompt-Engineering-ZH-CN?style=social)](https://github.com/yunwei37/Awesome-Prompt-Engineering-ZH-CN) | Includes **WFGY 16 Problem Map** in the Tools & Code section as a vendor-neutral failure map for LLM/RAG pipelines, describing the 16 failure modes and minimal recovery strategies in Chinese. |
| [AI Agents for Cybersecurity](https://github.com/santosomar/AI-agents-for-cybersecurity) | [![GitHub Repo stars](https://img.shields.io/github/stars/santosomar/AI-agents-for-cybersecurity?style=social)](https://github.com/santosomar/AI-agents-for-cybersecurity) | References the 16 mode map as a debugging guide for RAG-heavy security agents. |
| [Awesome Artificial Intelligence Research](https://github.com/ThyrixYang/awesome-artificial-intelligence-research) | [![GitHub Repo stars](https://img.shields.io/github/stars/ThyrixYang/awesome-artificial-intelligence-research?style=social)](https://github.com/ThyrixYang/awesome-artificial-intelligence-research) | Links to WFGY in the NLP section as a project on LLM robustness, debugging, and reliability. |
| [Awesome-Prompt-Engineering](https://github.com/natnew/Awesome-Prompt-Engineering) | [![GitHub Repo stars](https://img.shields.io/github/stars/natnew/Awesome-Prompt-Engineering?style=social)](https://github.com/natnew/Awesome-Prompt-Engineering) | Lists **“WFGY 16 Problem Map”** in the Key Reading section as a troubleshooting guide for RAG and LLM pipelines. |
| [Awesome-LLM-based-Evaluators](https://github.com/dependentsign/Awesome-LLM-based-Evaluators) | [![GitHub Repo stars](https://img.shields.io/github/stars/dependentsign/Awesome-LLM-based-Evaluators?style=social)](https://github.com/dependentsign/Awesome-LLM-based-Evaluators) | Lists **WFGY 3.0 · Singularity Demo** and the **WFGY ProblemMap** in its “Robustness and stress-test resources” section as a TXT-based long-horizon tension reasoning benchmark and failure map for RAG and LLM robustness evaluation. |



---

### ⭐ Star-powered Proof

The WFGY project has been starred by a diverse group of developers, maintainers, and ecosystem contributors.  
Stars are not the same as technical integrations or formal citations, but they show who cared enough to follow WFGY and keep an eye on its work.

This section highlights some early and notable “Star Gators” who starred the project in its first growth waves.

Explore the full list of notable supporters:

👉 [Star Gators · notable stargazers](https://github.com/onestardao/WFGY/blob/main/stargazers/README.md)


---

## 4. Community Works (open PRs)

This is a community showcase for projects, demos, websites, tutorials, translations, and integrations built with WFGY ideas.
Small projects are welcome. There is no star requirement.

Submission requirements:
1) Public link
2) One sentence explaining which WFGY part you used
3) A proof link or a verifiable reference
4) Language tag (EN / ZH / Bilingual / others)

Disclaimer:
Entries here are community submissions and do not imply endorsement.

| Project | Type | Language | Link | What it does with WFGY | Proof | Credit |
| --- | --- | --- | --- | --- | --- | --- |
| WFGY 3.0 UI (S131 Problem Browser) | website | ZH | [scyprodigy.github.io/wfgy-scy](https://scyprodigy.github.io/wfgy-scy/) | A Traditional Chinese UI prototype that visualizes and lets users browse the WFGY 3.0 "131 S-Class Problems" set (work in progress). | [live demo](https://scyprodigy.github.io/wfgy-scy/) | scyprodigy |
| Dungeon Master OS | project | EN | [github.com/djnightmare9909/Dungeon-master-OS-](https://github.com/djnightmare9909/Dungeon-master-OS-WFGY) | An experimental system exploring WFGY-style structured reasoning for worldbuilding, scenario design, and interactive narrative workflows. | [repo](https://github.com/djnightmare9909/Dungeon-master-OS-WFGY) | djnightmare9909 |


### 🤝 Contributing

If you find a public repository, benchmark, article, doc page, course page, or discussion that includes WFGY, you are welcome to help keep this list accurate.

You can contribute by:

- adding a missing entry  
- updating an outdated description  
- attaching a better proof link  
- correcting categorization  
- submitting a PR with a new citation or integration  

Forks and PRs are welcome. If your project includes WFGY in any public form, feel free to add it to this recognition list with a short description and a verifiable link.