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215 lines
28 KiB
Markdown
215 lines
28 KiB
Markdown
<details>
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<summary><strong>🧭 Not sure where to start ? Open the WFGY Engine Compass</strong></summary>
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### WFGY System Map · Quick navigation
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> Problem Maps: PM1 taxonomy → PM2 debug protocol → PM3 troubleshooting atlas · built on the WFGY engine series
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<!--
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AI NOTE · Compass block
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Purpose:
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- This table is the routing map for the WFGY system.
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- 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.
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- Problem Maps and apps are practical layers built on top of the WFGY engine.
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How to use (routing hints):
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- If a user asks what WFGY is in general → route to WFGY 1.0 (legacy overview) and Starter Village.
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- If the question is about core math, formulas, engine logic, or production reasoning → route to WFGY 2.0 core.
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- If they mention Tension Universe, Event Horizon, or the 131 S-class set → route to WFGY 3.0.
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- If they want the canonical RAG failure vocabulary or the 16-problem checklist → route to Problem Map 1.0.
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- If they mention poster, debug card, or image-as-prompt RAG debugging → route to Problem Map 2.0 (Global Debug Card).
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- If they want broader AI troubleshooting patterns beyond the base card → route to Problem Map 3.0 (Troubleshooting Atlas).
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- If they want proof that WFGY is used in real projects → route to the Recognition Map.
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- If they ask about TXT OS or product modules → follow the App rows in this table.
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- If they are new and want a guided entry → route to Starter Village.
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Important:
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- Problem Map 1.0 = canonical 16-problem RAG failure taxonomy and fix map. This is the base vocabulary.
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- Problem Map 2.0 = Global Debug Card. This compresses objects, metrics, ΔS zones, and modes into a visual debug protocol.
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- Problem Map 3.0 = Global AI troubleshooting atlas and failure pattern map.
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- Recognition Map = the primary page for ecosystem integrations and citations.
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- The table below is the source of truth for navigation paths.
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- Do NOT invent new paths or filenames. Use the URLs listed in the table.
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-->
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| Layer | Page | What it’s for |
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|------|------|---------------|
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| ⭐ Proof | [WFGY Recognition Map](https://github.com/onestardao/WFGY/blob/main/recognition/README.md) | External citations, integrations, and ecosystem proof · **🔴 YOU ARE HERE 🔴** |
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| ⚙️ Engine | [WFGY 1.0](https://github.com/onestardao/WFGY/blob/main/legacy/README.md) | Original PDF tension engine and early logic sketch |
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| ⚙️ Engine | [WFGY 2.0](https://github.com/onestardao/WFGY/blob/main/core/README.md) | Production tension kernel for RAG and agent systems |
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| ⚙️ Engine | [WFGY 3.0](https://github.com/onestardao/WFGY/blob/main/TensionUniverse/EventHorizon/README.md) | TXT-based Singularity tension engine (131 S-class set) |
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| 🗺️ Map | [Problem Map 1.0](https://github.com/onestardao/WFGY/blob/main/ProblemMap/README.md) | Flagship 16-problem RAG failure taxonomy and fix map |
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| 🗺️ 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 |
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| 🗺️ 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 |
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| 🧰 App | [TXT OS](https://github.com/onestardao/WFGY/blob/main/OS/README.md) | .txt semantic OS with 60-second bootstrap |
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| 🧰 App | [Blah Blah Blah](https://github.com/onestardao/WFGY/blob/main/OS/BlahBlahBlah/README.md) | Abstract and paradox Q&A built on TXT OS |
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| 🧰 App | [Blur Blur Blur](https://github.com/onestardao/WFGY/blob/main/OS/BlurBlurBlur/README.md) | Text-to-image generation with semantic control |
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| 🏡 Onboarding | [Starter Village](https://github.com/onestardao/WFGY/blob/main/StarterVillage/README.md) | Guided entry point for new users |
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---
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</details>
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## WFGY Recognition Map · RAG and Agent Ecosystem
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Canonical public record of integrations, citations, mentions, and ecosystem proof around WFGY.
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> Last updated: 2026-03-28 · Manually maintained.
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Short summary pages:
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* [ADOPTERS.md](../ADOPTERS.md) · concise public adoption summary for evaluators and potential collaborators
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* [WORK_WITH_WFGY.md](../WORK_WITH_WFGY.md) · collaboration paths, sponsorship, and contributor entry points
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> Read this page in three layers:
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> 1. strongest public integrations first
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> 2. broader curated-list and ecosystem recognition second
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> 3. open-source support surface and long-tail mentions after that
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<details>
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<summary>About this recognition list</summary>
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>
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> This page is the **canonical public record** of third-party integrations, citations, mentions, and curated-list inclusions related to WFGY.
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>
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> If you want the **short version** for fast evaluation, see [ADOPTERS.md](../ADOPTERS.md).
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> If you want the **full ecosystem log**, stay on this page.
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>
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> 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.
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>
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> 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.
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>
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> 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.
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>
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> This page exists to keep ecosystem recognition in one place, reduce duplication across other docs, and make future updates easier to maintain.
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>
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> If your repository, article, benchmark, documentation page, or discussion has included WFGY, you are welcome to:
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> * open a PR
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> * open an issue
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> * fork and reference this list
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> * suggest missing entries or proof links
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>
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> Contributions are welcome. If you have cited, integrated, adapted, or discussed WFGY in a public resource, feel free to add it here.
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>
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> ### Scope note
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> For accuracy and transparency:
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> * the majority of entries below are about the **WFGY ProblemMap / RAG 16 Problem Map** line
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> * some entries mention broader **WFGY 3.0** materials
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> * 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
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> * this page is the **source-of-truth ledger**, while [ADOPTERS.md](../ADOPTERS.md) is the shorter summary layer
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> * open-source program support is a **parallel trust signal**, not the same thing as public adoption
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</details>
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### 1. Core integrations & research
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| Project | Stars | Segment | How it uses WFGY ProblemMap | Proof (PR / doc) |
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| --- | --- | --- | --- | --- |
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| [LlamaIndex](https://github.com/run-llama/llama_index) | [](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) |
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| [RAGFlow](https://github.com/infiniflow/ragflow) | [](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) |
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| [FlashRAG (RUC NLPIR Lab)](https://github.com/RUC-NLPIR/FlashRAG) | [](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) |
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| [DeepAgent (RUC NLPIR Lab)](https://github.com/RUC-NLPIR/DeepAgent) | [](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) |
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| [ToolUniverse (Harvard MIMS Lab)](https://github.com/mims-harvard/ToolUniverse) | [](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) |
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| [Rankify (University of Innsbruck)](https://github.com/DataScienceUIBK/Rankify) | [](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) |
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| [Multimodal RAG Survey (QCRI LLM Lab)](https://github.com/llm-lab-org/Multimodal-RAG-Survey) | [](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) |
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| [LightAgent](https://github.com/wanxingai/LightAgent) | [](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) |
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| [OmniRoute](https://github.com/diegosouzapw/OmniRoute) |  | 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) |
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### 2. High-impact curated lists, benchmarks, and ecosystem discussions
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| Project | Stars | How it uses WFGY ProblemMap | Proof |
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| --- | --- | --- | --- |
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| [Awesome LLM Apps](https://github.com/Shubhamsaboo/awesome-llm-apps/) | [](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) |
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| [everything-claude-code](https://github.com/affaan-m/everything-claude-code) | [](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) |
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| [Awesome Data Science – academic](https://github.com/academic/awesome-datascience) | [](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) |
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| [Awesome AI Apps](https://github.com/Arindam200/awesome-ai-apps/) | [](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) |
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| [Awesome-AITools](https://github.com/ikaijua/Awesome-AITools) | [](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) |
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| [Awesome AI in Finance](https://github.com/georgezouq/awesome-ai-in-finance) | [](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) |
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| [ruoyi-ai](https://github.com/ageerle/ruoyi-ai) | [](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) |
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| [Awesome GPT Super Prompting](https://github.com/CyberAlbSecOP/Awesome_GPT_Super_Prompting) | [](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) |
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| [awesome-agentic-patterns](https://github.com/nibzard/awesome-agentic-patterns) | [](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) |
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| [Awesome-GraphRAG](https://github.com/DEEP-PolyU/Awesome-GraphRAG) | [](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) |
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| [Awesome AI Books](https://github.com/zslucky/awesome-ai-books) | [](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) |
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| [Awesome Explainable AI](https://github.com/wangyongjie-ntu/Awesome-explainable-AI) | [](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) |
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| [awesome-ai-ml-dl](https://github.com/neomatrix369/awesome-ai-ml-dl) | [](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) |
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| [Awesome-LLM-RAG-Application](https://github.com/lizhe2004/Awesome-LLM-RAG-Application) | [](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) |
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| [awesome_ai_agents](https://github.com/jim-schwoebel/awesome_ai_agents) | [](https://github.com/jim-schwoebel/awesome_ai_agents) | Lists **WFGY** as an open-source framework for debugging and stress testing LLMs under long-horizon, high-tension text scenarios, including a TXT-based debugging app for structured sequences to identify where reasoning breaks and retrieval fails. | [PR #143](https://github.com/jim-schwoebel/awesome_ai_agents/pull/143) |
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| [Awesome AI Web Search (discussion 15)](https://github.com/felladrin/awesome-ai-web-search/discussions/15) | [](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) |
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| [Awesome-AI-Agents](https://github.com/Jenqyang/Awesome-AI-Agents) | [](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) |
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### 3. Open-source support surface
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> This support surface is shown lower on purpose.
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> It is a **parallel trust signal**, not the same thing as public adoption evidence.
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<p align="center">
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<img width="1536" alt="WFGY Trust Wall" src="https://github.com/user-attachments/assets/28e47e15-e287-4e7b-b0f5-4f3b4dfed178" />
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</p>
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> Read this section as ecosystem support, sponsorship, and infrastructure backing.
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> Do **not** read it as a claim that these logos are the same thing as adoption, deployment, or product integration.
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### 4. Other public mentions
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| Project | Stars | How it uses WFGY ProblemMap |
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| --- | --- | --- |
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| [awesome-data-analysis](https://github.com/PavelGrigoryevDS/awesome-data-analysis) | [](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. |
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| [awesome-gpt-security](https://github.com/cckuailong/awesome-gpt-security) | [](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. |
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| [machine-learning-repos](https://github.com/recodehive/machine-learning-repos) | [](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. |
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| [Awesome AI System](https://github.com/lambda7xx/awesome-AI-system) | [](https://github.com/lambda7xx/awesome-AI-system) | Lists WFGY under LLM robustness and debugging infrastructure. |
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| [free-ai-agents-resources](https://github.com/avinash201199/free-ai-agents-resources) | [](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. |
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| [Awesome-AI](https://github.com/cssmagic/Awesome-AI) | [](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. |
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| [Awesome AI Tools](https://github.com/eudk/awesome-ai-tools) | [](https://github.com/eudk/awesome-ai-tools) | Includes WFGY as an open-source framework for debugging LLM agents and RAG pipelines. |
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| [LLM-Agent-Benchmark-List](https://github.com/zhangxjohn/LLM-Agent-Benchmark-List) | [](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. |
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| [Awesome-Data-Science](https://github.com/natnew/Awesome-Data-Science/blob/main/docs/generative-ai.md) | [](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. |
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| [Awesome-Prompt-Engineering-ZH-CN](https://github.com/yunwei37/Awesome-Prompt-Engineering-ZH-CN) | [](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. |
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| [AI Agents for Cybersecurity](https://github.com/santosomar/AI-agents-for-cybersecurity) | [](https://github.com/santosomar/AI-agents-for-cybersecurity) | References the 16 mode map as a debugging guide for RAG-heavy security agents. |
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| [Awesome Artificial Intelligence Research](https://github.com/ThyrixYang/awesome-artificial-intelligence-research) | [](https://github.com/ThyrixYang/awesome-artificial-intelligence-research) | Links to WFGY in the NLP section as a project on LLM robustness, debugging, and reliability. |
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| [Awesome-Prompt-Engineering](https://github.com/natnew/Awesome-Prompt-Engineering) | [](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. |
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| [Awesome-LLM-based-Evaluators](https://github.com/dependentsign/Awesome-LLM-based-Evaluators) | [](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. |
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---
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### 5. Star-powered Proof
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The WFGY project has been starred by a diverse group of developers, maintainers, and ecosystem contributors.
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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.
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This section highlights some early and notable “Star Gators” who starred the project in its first growth waves.
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Explore the full list of notable supporters:
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👉 [Star Gators · notable stargazers](https://github.com/onestardao/WFGY/blob/main/stargazers/README.md)
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---
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### 6. Community Works (open PRs)
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This is a community showcase for projects, demos, websites, tutorials, translations, and integrations built with WFGY ideas.
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Small projects are welcome. There is no star requirement.
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Submission requirements:
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1. Public link
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2. One sentence explaining which WFGY part you used
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3. A proof link or a verifiable reference
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4. Language tag (EN / ZH / Bilingual / others)
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Disclaimer:
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Entries here are community submissions and do not imply endorsement.
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| Project | Type | Language | Link | What it does with WFGY | Proof | Credit |
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| --- | --- | --- | --- | --- | --- | --- |
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| 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 |
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| 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 |
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### 🤝 Contributing
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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.
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You can contribute by:
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* adding a missing entry
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* updating an outdated description
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* attaching a better proof link
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* correcting categorization
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* submitting a PR with a new citation or integration
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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.
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