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<!-- TOP ANCHOR -->
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<a id="top"></a>
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<details>
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<summary><strong>🧭 Lost or curious? Open the WFGY Compass & ⭐ Star Unlocks</strong></summary>
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@ -38,6 +41,15 @@
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> 👑 **Early Stargazers: [See the Hall of Fame](https://github.com/onestardao/WFGY/tree/main/stargazers)** — Verified by real engineers · 🏆 **Terminal-Bench: [Public Exam (teaser)](https://github.com/onestardao/WFGY/blob/main/core/README.md#terminal-bench-proof)**
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<!-- QUICK LINKS BAR -->
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<p align="center">
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<a href="#tb">TB Update</a> •
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<a href="#eye">Eye Benchmark</a> •
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<a href="#eight">8-Model Evidence</a> •
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<a href="#abc">A/B/C Prompt</a> •
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<a href="#downloads">Downloads</a> •
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<a href="#prompts">Profit Prompts</a>
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</p>
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<img width="1536" height="1024" alt="WFGY_Core" src="https://github.com/user-attachments/assets/deb8e794-a73e-4d39-a1f6-174ec87199f4" />
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@ -64,14 +76,11 @@
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>
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> “One line” is not hype. I built a full flagship edition, and I also reduced it to a single line of code — a reduction that is clarity and beauty, the same engine distilled to its purest expression.
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</details>
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[⬇️Downloads](#downloads) | [👀 Eye-Visible Reasoning Benchmark](#eye-benchmark) | [🧬Eight-model evidence (A/B/C protocol)](#eight-model) | [💰 Try the 20 Profit Prompts](#profit-prompts-pack)
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---
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## 🚀 WFGY 2.0 Headline Uplift (this release)
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## 🚀 WFGY 2.0 Headline Uplift (this release)
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**These are the 2.0 results you should see first — the “big upgrade.”**
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- **Semantic Accuracy:** **≈ +40%** (63.8% → 89.4% across 5 domains)
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@ -82,16 +91,22 @@
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\* Historical **3–5×** stability uses λ-consistency across seeds; 1.8× uses the stable-node horizon.
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### 📖 Mathematical Reference
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### 📖 Mathematical Reference
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WFGY 2.0 (WFGY Core) = [WFGY 1.0 math formulas](https://github.com/onestardao/WFGY/blob/main/SemanticBlueprint/wfgy_formulas.md) + [Drunk Transformer](https://github.com/onestardao/WFGY/blob/main/SemanticBlueprint/drunk_transformer_formulas.md)
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<p align="right"><a href="#top">Back to top ↑</a></p>
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---
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<a id="tb"></a>
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### 🏆 Stanford Terminal-Bench (TB) — Exam Update
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> [!IMPORTANT]
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> We are currently taking the official TB exam. Leaderboard placement will be posted here once it’s live.
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> Follow the running notes: [Terminal-Bench Proof](#terminal-bench-proof)
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**What is TB?**
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Terminal-Bench is Stanford’s public exam for LLMs.
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It stresses models through **terminal-style, multi-step tasks** — measuring reasoning, robustness, and recovery under real engineering conditions.
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Terminal-Bench is Stanford’s public exam for LLMs. It stresses models through **terminal-style, multi-step tasks** — measuring reasoning, robustness, and recovery under real engineering conditions.
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**How we participate**
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WFGY Core 2.0 wraps each model call (non-invasive). Every step flows through:
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@ -99,11 +114,21 @@ WFGY Core 2.0 wraps each model call (non-invasive). Every step flows through:
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All runs are reproducible with configs, scripts, and hashed logs.
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**Status**
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We are currently taking the TB exam. Rankings will be published once the official leaderboard is live.
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We are currently taking the TB exam. Rankings will be published once the official leaderboard is live.
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👉 Follow updates here: [Terminal-Bench Proof]
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<p align="right"><a href="#top">Back to top ↑</a></p>
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[Terminal-Bench Proof]: https://github.com/onestardao/WFGY/blob/main/core/README.md#terminal-bench-proof
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---
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<a id="terminal-bench-proof"></a>
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### 🧾 Terminal-Bench Proof (teaser)
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- **Wrapper**: non-invasive; TB kept unchanged, we only wrap the model call.
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- **Chain**: semantic firewall → 7-step reasoning → DT guards with conditional retry.
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- **Artifacts**: configs, semantic-firewall prompts, and hashed logs for each run.
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- **Public repo link**: withheld until exam artifacts are finalized.
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<p align="right"><a href="#top">Back to top ↑</a></p>
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---
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@ -115,14 +140,14 @@ We are currently taking the TB exam. Rankings will be published once the officia
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| **Explicit Call**| Invoke WFGY formulas directly inside your workflow. This activates the full 7-step reasoning chain and gives maximum uplift. |
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Both **Flagship** and **OneLine** editions behave the same; choose based on readability vs minimalism.
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That’s it — no plugins, no installs, pure text.
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*In practice, Autoboot yields about ~70–80% of the uplift you see with explicit WFGY invoke (see eight-model results below).*
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<p align="right"><a href="#top">Back to top ↑</a></p>
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---
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## ⚡ Top 10 reasons to use WFGY 2.0 <!-- you asked for this section to stay visible (not collapsed) -->
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## ⚡ Top 10 reasons to use WFGY 2.0
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1. **Ultra-mini engine** — pure text, zero install, runs anywhere you can paste.
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2. **Two editions** — *Flagship* (30-line, audit-friendly) and *OneLine* (1-line, stealth & speed).
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3. **Autoboot mode** — upload once; the engine quietly supervises reasoning in the background.
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@ -134,6 +159,8 @@ That’s it — no plugins, no installs, pure text.
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9. **Reproducible A/B/C protocol** — Baseline vs Autoboot vs Explicit Invoke (see below).
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10. **MIT licensed & community-driven** — keep it, fork it, ship it.
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<p align="right"><a href="#top">Back to top ↑</a></p>
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---
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# 🧪 WFGY Benchmark Suite (Eye-visible + Numeric + Reproducible)
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> Want formal numbers and vendor links? See **Eight-model evidence** right after it.
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> Want to reproduce the numeric test yourself? Use the **A/B/C prompt** (copy-to-run) at the end of this section.
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<a id="eye-benchmark"></a>
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<a id="eye"></a>
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## 👀 Eye-Visible Reasoning Benchmark (FIVE)
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> Did you know that when reasoning improves, **text-to-image results become more stable and coherent**?
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@ -165,8 +192,6 @@ We **fully analyze Sequence A** on this page; **Sequences B/C** are linked for t
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> Hence **Before-4 (Investiture of the Gods)** and **Before-5 (Classic of Mountains and Seas)** converge to the same storyboard template.
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> **WFGY** prevents this collapse by enforcing a **single unified tableau** and stable hierarchy across the full five-image sequence.
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---
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### Deep analysis — Sequence A (five unified 1:1 tableaux)
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| Work | **Without WFGY** | **With WFGY** | Verdict (global, at-a-glance) |
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| **Investiture of the Gods (封神演義)** | <img src="images/group1_before4.png" width="300" alt="Without WFGY" title="model/params/seed/date"> | <img src="images/group1_after4.png" width="300" alt="With WFGY" title="model/params/seed/date"> | **With WFGY wins.** Dragon–tiger diagonal and cloud–sea layering create epic scale; the grid dilutes focus. *Tags:* Unification↑ Depth/Scale↑ Flow↑ Iconicity↑ |
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| **Classic of Mountains and Seas (山海經)** | <img src="images/group1_before5.png" width="300" alt="Without WFGY" title="model/params/seed/date"> | <img src="images/group1_after5.png" width="300" alt="With WFGY" title="model/params/seed/date"> | **With WFGY wins.** A single, continuous “mountains-and-seas” world with stable triangle hierarchy and smooth diagonal flow; grid breaks narrative. *Tags:* Unification↑ Hierarchy↑ Depth/Scale↑ Flow↑ Memorability↑ |
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<p align="right"><a href="#top">Back to top ↑</a></p>
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---
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<details>
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<summary>🧪 ChatGPT setup & image prompt (click to copy)</summary>
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<br>
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This comparison was produced **in ChatGPT** using a **single, high-semantic-density prompt**. Same model & settings; *only* WFGY on/off differs.
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```text
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We will create exactly five images in total using WFGY
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The five images are:
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1. The most iconic moments of Romance of the Three Kingdoms in one unified 1:1 image.
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2. The most iconic moments of Water Margin in one unified 1:1 image.
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3. The most iconic moments of Dream of the Red Chamber in one unified 1:1 image.
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4. The most iconic moments of Investiture of the Gods in one unified 1:1 image.
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5. The most iconic myths of Classic of Mountains and Seas in one unified 1:1 image.
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Each image must focus on 5~8 culturally defining scenes or figures, with supporting events only suggested subtly in the background.
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Foreground and background must remain equally sharp, with ultra-detailed rendering and consistent texture fidelity.
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Composition must be harmonious, with narrative clarity — the central cultural symbols are emphasized, while secondary motifs remain understated.
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Do not provide any plot explanations.
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Do not start drawing immediately.
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Only when I type "GO", you will create the next image in the sequence, in the exact order above, until all five are completed.
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Do not skip or merge images.
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````
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</details>
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---
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<a id="eight-model"></a>
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<a id="eight"></a>
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## 🧬 Eight-model evidence (A/B/C protocol) <!-- per your request: NOT collapsed -->
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*Same task set across modes. The only change is adding the OneLine math file.*
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| Copilot | Think Deeper | **80/100** | [view run](https://copilot.microsoft.com/shares/7FjR19TYBjg9sp8k9WcuE) |
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| Claude | Sonnet 4 | **78/100** | [view run](https://claude.ai/share/b17e5436-8298-4619-a243-ac451cc64b17) |
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> **The numeric story behind 2.0**
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> **The numeric story behind 2.0**
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> **Semantic Accuracy:** ≈ +40% · **Reasoning Success:** ≈ +52% · **Drift:** ≈ −65% · **Stability:** ≈ 1.8× · **CRR:** 1.00 (median 0.87)
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<p align="right"><a href="#top">Back to top ↑</a></p>
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---
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<a id="abc"></a>
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## 🧪 Reproduce the numeric A/B/C benchmark (copy to run)
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*One unified prompt for Baseline vs Autoboot vs Explicit Invoke.*
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USER:
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Run A/B/C now on the five domains with short non-trivial tasks you choose. Then output:
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(1) the table; (2) the deltas; (3) the OneLine uplift score; (4) a 3-line rationale.
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```
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````
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<p align="right"><a href="#top">Back to top ↑</a></p>
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---
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<a id="downloads"></a>
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## ⬇️ Downloads <!-- visible; checksum guide tucked inside details -->
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| File name & description | Length / Size | Direct Download Link | Verify (MD5 / SHA1 / SHA256) | Notes |
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| ---------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------- | -------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------- |
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| **WFGY_Core_Flagship_v2.0.txt** — readable 30-line companion expressing the same math and gates in fuller prose (same behavior, clearer for humans). | **30 lines · 3,049 chars** | [Download Flagship](./WFGY_Core_Flagship_v2.0.txt) | [md5](./checksums/WFGY_Core_Flagship_v2.0.txt.md5) · [sha1](./checksums/WFGY_Core_Flagship_v2.0.txt.sha1) · [sha256](./checksums/WFGY_Core_Flagship_v2.0.txt.sha256) | Full prose version for easier reading. |
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| **WFGY_Core_OneLine_v2.0.txt** — ultra-compact, math-only control layer that activates WFGY’s loop inside a chat model (no tools, text-only, ≤7 nodes). | **1 line · 1,500 chars** | [Download OneLine](./WFGY_Core_OneLine_v2.0.txt) | [md5](./checksums/WFGY_Core_OneLine_v2.0.txt.md5) · [sha1](./checksums/WFGY_Core_OneLine_v2.0.txt.sha1) · [sha256](./checksums/WFGY_Core_OneLine_v2.0.txt.sha256) | Used for all benchmark results above — smallest, fastest, purest form of the core. |
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## ⬇️ Downloads
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[💰 Try the 20 Profit Prompts →](#profit-prompts-pack)
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| File name & description | Length / Size | Direct Download Link | Verify (MD5 / SHA1 / SHA256) | Notes |
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| ------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------- | -------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------- |
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| **WFGY_Core_Flagship_v2.0.txt** — readable 30-line companion expressing the same math and gates in fuller prose (same behavior, clearer for humans). | **30 lines · 3,049 chars** | [Download Flagship](./WFGY_Core_Flagship_v2.0.txt) | [md5](./checksums/WFGY_Core_Flagship_v2.0.txt.md5) · [sha1](./checksums/WFGY_Core_Flagship_v2.0.txt.sha1) · [sha256](./checksums/WFGY_Core_Flagship_v2.0.txt.sha256) | Full prose version for easier reading. |
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| **WFGY_Core_OneLine_v2.0.txt** — ultra-compact, math-only control layer that activates WFGY’s loop inside a chat model (no tools, text-only, ≤7 nodes). | **1 line · 1,500 chars** | [Download OneLine](./WFGY_Core_OneLine_v2.0.txt) | [md5](./checksums/WFGY_Core_OneLine_v2.0.txt.md5) · [sha1](./checksums/WFGY_Core_OneLine_v2.0.txt.sha1) · [sha256](./checksums/WFGY_Core_OneLine_v2.0.txt.sha256) | Used for all benchmark results above — smallest, fastest, purest form of the core. |
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<details>
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<summary><em>How to verify checksums</em></summary>
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<br>
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**macOS / Linux**
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```bash
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@ -299,13 +296,13 @@ Get-FileHash .\core\WFGY_Core_OneLine_v2.0.txt -Algorithm SHA256
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</details>
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<p align="right"><a href="#top">Back to top ↑</a></p>
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---
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<details>
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<summary>🧠 How WFGY 2.0 works (7-Step Reasoning Chain)</summary>
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<br>
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*Most models can understand your prompt; very few can **hold** that meaning through generation.*
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WFGY inserts a reasoning chain between language and pixels so intent survives sampling noise, style drift, and compositional traps.
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@ -317,25 +314,22 @@ WFGY inserts a reasoning chain between language and pixels so intent survives sa
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6. **BBAM** — attention rebalancer; suppress hallucinations.
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7. **BBCR + Drunk Transformer** — rollback → re-bridge → retry with WRI/WAI/WAY/WDT/WTF.
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📌 *Note:* The diagram shows the **core module chain** (BBMC → Coupler → BBPF → BBAM → BBCR → DT).
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📌 *Note:* The diagram shows the **core module chain** (BBMC → Coupler → BBPF → BBAM → BBCR → DT).
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The full **7-step list** here includes additional **pre-processing steps** (Parse, Δs, Memory) for completeness.
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**Why it improves metrics** — Stability↑, Drift↓, Self-Recovery↑; turns *language* structure into *image* control signals (not prompt tricks).
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</details>
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<details>
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<summary>📊 How these numbers are measured</summary>
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<br>
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* **Semantic Accuracy**: `ACC = correct_facts / total_facts`
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* **Reasoning Success Rate**: `SR = tasks_solved / tasks_total`
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* **Stability**: MTTF or rollback ratios
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* **Self-Recovery**: `recoveries_success / collapses_detected`
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LLM scorer template:
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**LLM scorer template**
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```text
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SCORER:
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@ -354,159 +348,215 @@ Run 3 seeds and average.
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</details>
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<p align="right"><a href="#top">Back to top ↑</a></p>
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---
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<a id="profit-prompts-pack"></a>
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<a id="prompts"></a>
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# 💰 Profit Prompts Pack (WFGY 2.0)
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> Copy → paste into your model. Prompts only, no answers.
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> Assumed engine: WFGY 2.0 (ΔS drift control, λ\_observe gates, BBPF bridges, BBAM alignment, WTF recovery).
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**Jump inside this section:** [Q1–Q5](#q1-q5) · [Q6–Q10](#q6-q10) · [Q11–Q15](#q11-q15) · [Q16–Q20](#q16-q20)
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## I. Money — Markets / Industry Mapping (Q1–Q5)
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<details open>
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<summary><strong>I. Money — Markets / Industry Mapping (Q1–Q5)</strong> <a id="q1-q5"></a></summary>
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**Q1 — New Industries + Killer App Map**
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<a id="q1"></a>
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### Q1 — New Industries + Killer App Map
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```text
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Assume WFGY is engineered like electricity. List 5 industries that only become possible under semantic engineering.
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For each: (1) the first killer app; (2) target ICP (first 100 paying customers); (3) 30/60/90-day GTM; (4) initial pricing + Month-1 MRR goal; (5) the WFGY lever used (ΔS/λ_observe/BBPF/BBAM/WTF) and why it’s indispensable.
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```
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**Q2 — Zero-Capital Founder → First \$100k**
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<a id="q2"></a>
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### Q2 — Zero-Capital Founder → First $100k
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```text
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I have $0. Using WFGY OneLine/Autoboot only, design 3 paths to reach USD 100k annual revenue within 12 months.
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Each path must include: product sketch, distribution channel, cost structure, key risks, and survival metrics gated by ΔS/λ_observe (with thresholds).
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```
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**Q3 — Shortest Path in {Region/Vertical}**
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<a id="q3"></a>
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### Q3 — Shortest Path in {Region/Vertical}
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```text
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Context = {region or vertical: e.g., Taiwan / SE Asia / B2B SaaS / Edu / Healthcare}. Name the 3 easiest WFGY lanes to start now.
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Output: white-space in the market, local competitor gap, and a prioritized list of 10 real companies to approach first, with the BBPF plan to bridge local legal/cultural semantics.
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```
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**Q4 — Regulatory Arbitrage Map**
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<a id="q4"></a>
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### Q4 — Regulatory Arbitrage Map
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```text
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Compare 3 jurisdictions (e.g., TW/JP/EU). Identify WFGY-enabled arbitrage windows created by semantic/legal differences.
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Deliver: λ_observe compliance gating prompts, “Do/Don’t” checklist, and PR messaging that provokes interest while keeping ΔS ≤ 0.25 on sensitive claims.
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```
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**Q5 — Pricing & Packaging (Good/Better/Best)**
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<a id="q5"></a>
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### Q5 — Pricing & Packaging (Good/Better/Best)
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```text
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Create 3 pricing models (seat / usage / outcome). For the same product, propose a tier ladder (G/B/B), with 3 value metrics per tier, a 30-day A/B test plan, win criteria (e.g., +20% CVR uplift or ≤3% churn), and how ΔS telemetry informs price moves.
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```
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## II. Tools — Make Startups Money Fast (Q6–Q10)
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</details>
|
||||
|
||||
**Q6 — 10-Day MVP Sprint (Ship or Die)**
|
||||
<details>
|
||||
<summary><strong>II. Tools — Make Startups Money Fast (Q6–Q10)</strong> <a id="q6-q10"></a></summary>
|
||||
|
||||
<a id="q6"></a>
|
||||
|
||||
### Q6 — 10-Day MVP Sprint (Ship or Die)
|
||||
|
||||
```text
|
||||
Produce a D1–D10 plan: daily deliverables, risk list, test scripts, acceptance gates. Must be Product Hunt-ready and able to capture 200 signups.
|
||||
Include a ΔS target curve (first pass ≤0.35; after iteration ≤0.20) and a λ_observe gate for “demo truthiness.”
|
||||
```
|
||||
|
||||
**Q7 — Cost↓ / CVR↑ Audit (ICE-Prioritized)**
|
||||
<a id="q7"></a>
|
||||
|
||||
### Q7 — Cost↓ / CVR↑ Audit (ICE-Prioritized)
|
||||
|
||||
```text
|
||||
Audit my SaaS across Support / Sales / Content. Output a “ROI backlog” ranked by ICE. Each item: expected % cost reduction or × conversion lift, λ_observe brand/legal gate, and 3 rollout steps with before/after KPIs.
|
||||
```
|
||||
|
||||
**Q8 — Sales Script Factory (Multi-Persona)**
|
||||
<a id="q8"></a>
|
||||
|
||||
### Q8 — Sales Script Factory (Multi-Persona)
|
||||
|
||||
```text
|
||||
Generate 5 script families for CEO/CTO/Counsel/Procurement/CDAO: opening hooks, 3-step value narrative, ≥7 objection handlers, close lines.
|
||||
Add an A/B cadence and success KPIs (demo rate / close rate), plus ΔS checks to keep claims inside the truth boundary.
|
||||
```
|
||||
|
||||
**Q9 — Support Consistency Engine (BBAM × SOP)**
|
||||
<a id="q9"></a>
|
||||
|
||||
### Q9 — Support Consistency Engine (BBAM × SOP)
|
||||
|
||||
```text
|
||||
Design a hotline/Helpdesk alignment loop: semantic style guide, ΔS drift alerts, WTF self-recovery when answers diverge, and 3 KPIs (FRT, FCR, CSAT).
|
||||
Provide plug-and-play prompts for supervisors to run weekly variance reviews.
|
||||
```
|
||||
|
||||
**Q10 — Outbound Accelerator (Lists → Meetings)**
|
||||
<a id="q10"></a>
|
||||
|
||||
### Q10 — Outbound Accelerator (Lists → Meetings)
|
||||
|
||||
```text
|
||||
Ship a WFGY-locked outbound flow: lead slicing, 3 personalized openers, 5 follow-up loops, resonance logging (E_resonance).
|
||||
For each step: prompt template, brand/legal safety notes (λ_observe), and expected daily/weekly meeting capacity with success thresholds.
|
||||
```
|
||||
|
||||
## III. Attention — Memes / Virality / Hooks (Q11–Q15)
|
||||
</details>
|
||||
|
||||
**Q11 — Meme Factory (Platform-Aware)**
|
||||
<details>
|
||||
<summary><strong>III. Attention — Memes / Virality / Hooks (Q11–Q15)</strong> <a id="q11-q15"></a></summary>
|
||||
|
||||
<a id="q11"></a>
|
||||
|
||||
### Q11 — Meme Factory (Platform-Aware)
|
||||
|
||||
```text
|
||||
Produce 10 meme/copy formulas tailored to Twitter / TikTok / Xiaohongshu.
|
||||
Each includes: visual composition notes, copy cadence (words/beat), platform-specific red lines (λ_observe), and a reuse/remix rule to sustain freshness without shadow bans.
|
||||
```
|
||||
|
||||
**Q12 — 5-Second Hook Engine**
|
||||
<a id="q12"></a>
|
||||
|
||||
### Q12 — 5-Second Hook Engine
|
||||
|
||||
```text
|
||||
Generate 12 “stop-scroll in 5s” hooks that fuse AI × Money × Future.
|
||||
Provide: script skeleton (0–5s / 5–20s / CTA), voice/subtitle/tempo, ΔS brand safety band, and 3 retention metrics to track on day 1.
|
||||
```
|
||||
|
||||
**Q13 — 30-Day Content Calendar**
|
||||
<a id="q13"></a>
|
||||
|
||||
### Q13 — 30-Day Content Calendar
|
||||
|
||||
```text
|
||||
Output a multi-platform calendar: daily theme, asset checklist, shot list, CTA, and a remix strategy.
|
||||
Add trend-riding tactics and ΔS risk controls for politics/health/finance content. Define success targets by channel.
|
||||
```
|
||||
|
||||
**Q14 — Landing Page Conversion Alchemy**
|
||||
<a id="q14"></a>
|
||||
|
||||
### Q14 — Landing Page Conversion Alchemy
|
||||
|
||||
```text
|
||||
Give 3 LP copy frameworks (Hero / Proof / Mechanism / Offer / CTA).
|
||||
Include WFGY “before/after” copy snippets, test variables (headline / social proof / price-display), and metrics (CVR, scroll-depth, bounce). Keep claims gated by λ_observe.
|
||||
```
|
||||
|
||||
**Q15 — 48-Hour PR Blitz**
|
||||
<a id="q15"></a>
|
||||
|
||||
### Q15 — 48-Hour PR Blitz
|
||||
|
||||
```text
|
||||
Design a two-day PR plan: newsworthy angle, media/community list, press kit assets, and crisis response lines (WTF loop).
|
||||
Publish numeric goals (reach, sessions, signups), hour-by-hour runbook, and roles/responsibilities checklist.
|
||||
```
|
||||
|
||||
## IV. Capital — Valuation / Investor Narrative (Q16–Q20)
|
||||
</details>
|
||||
|
||||
**Q16 — VC Investment Memo**
|
||||
<details>
|
||||
<summary><strong>IV. Capital — Valuation / Investor Narrative (Q16–Q20)</strong> <a id="q16-q20"></a></summary>
|
||||
|
||||
<a id="q16"></a>
|
||||
|
||||
### Q16 — VC Investment Memo
|
||||
|
||||
```text
|
||||
Write a venture-style memo: market map, TAM/SAM/SOM, competitor table (no/weak/strong WFGY), moat analysis (ΔS/BBPF/BBAM/WTF), risks + mitigations, and a term-sheet-level recommendation. Reference an A/B/C protocol for proof.
|
||||
```
|
||||
|
||||
**Q17 — 5-Year Valuation + 100× Path**
|
||||
<a id="q17"></a>
|
||||
|
||||
### Q17 — 5-Year Valuation + 100× Path
|
||||
|
||||
```text
|
||||
Build Base/Bull/Bear scenarios: revenue drivers, GM/OpEx, financing cadence, cash-flow breakpoints.
|
||||
Argue which app is most likely to 100× and why this depends on WFGY’s semantic engineering (not “just better prompts”).
|
||||
```
|
||||
|
||||
**Q18 — Technical Due Diligence Checklist**
|
||||
<a id="q18"></a>
|
||||
|
||||
### Q18 — Technical Due Diligence Checklist
|
||||
|
||||
```text
|
||||
Output a DD checklist for WFGY-style startups: data/security/privacy/model/logging/observability/governance.
|
||||
For each item: requirement, how to verify, risk level, remediation (with λ_observe compliance gates) and examples of common red flags.
|
||||
```
|
||||
|
||||
**Q19 — Pitch Deck Generator (10–12 slides)**
|
||||
<a id="q19"></a>
|
||||
|
||||
### Q19 — Pitch Deck Generator (10–12 slides)
|
||||
|
||||
```text
|
||||
Produce slide outline + speaker notes: Problem / Solution / Product / Evidence / Business Model / Competition / Team / Roadmap / Ask.
|
||||
Embed “Eye-Visible Benchmark” and the A/B/C protocol. Treat OneLine/Autoboot as the minimum persuasive artifact.
|
||||
```
|
||||
|
||||
**Q20 — Data Room + North-Star KPIs**
|
||||
<a id="q20"></a>
|
||||
|
||||
### Q20 — Data Room + North-Star KPIs
|
||||
|
||||
```text
|
||||
List seed-round data-room folders and a KPI dictionary: definitions, formulas, measurement cadence, WFGY deltas (Semantic Accuracy, Reasoning Success, ΔS, CRR, Stability).
|
||||
Add a Weekly Business Review template and operating cadence.
|
||||
```
|
||||
|
||||
</details>
|
||||
|
||||
<p align="right"><a href="#top">Back to top ↑</a></p>
|
||||
|
||||
---
|
||||
|
||||
### 🧭 Explore More
|
||||
|
|
@ -531,18 +581,18 @@ Add a Weekly Business Review template and operating cadence.
|
|||
<div align="center">
|
||||
|
||||
[](https://github.com/onestardao/WFGY)
|
||||
|
||||
|
||||
[](https://github.com/onestardao/WFGY/tree/main/OS)
|
||||
|
||||
|
||||
[](https://github.com/onestardao/WFGY/tree/main/OS/BlahBlahBlah)
|
||||
|
||||
|
||||
[](https://github.com/onestardao/WFGY/tree/main/OS/BlotBlotBlot)
|
||||
|
||||
|
||||
[](https://github.com/onestardao/WFGY/tree/main/OS/BlocBlocBloc)
|
||||
|
||||
|
||||
[](https://github.com/onestardao/WFGY/tree/main/OS/BlurBlurBlur)
|
||||
|
||||
|
||||
[](https://github.com/onestardao/WFGY/tree/main/OS/BlowBlowBlow)
|
||||
|
||||
|
||||
</div>
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue