README: badge-artifact evidence table

README.md

@@ -36,7 +36,18 @@ V toggle camera · B judge panel · 1–5 sparring bots · 7 the Masher · 8 the
 9 the LLM · Enter rematch · M mute.
 
 *(This Space is a `gradio.Server` app — Gradio's engine serves the custom canvas at `/`,
-and the Analyst endpoint runs through Gradio's queue, callable with `gradio_client`.)*
+and the `trace_digest` endpoint runs through Gradio's queue, callable with `gradio_client`.)*
+
+## 🎖️ Badge artifacts (everything is public)
+
+| Badge | Evidence |
+|---|---|
+| 🔌 Off the Grid | All inference in YOUR browser: Tactician + imagination on WebGPU (WebLLM), the tuned Analyst on llama.cpp/WASM. `GET /healthz` → `"inference": "in-browser"` |
+| 🎯 Well-Tuned | The published fine-tune **runs in this app** as the Analyst — [parry-tactician-1.5b-merged](https://huggingface.co/Jainamshahhh/parry-tactician-1.5b-merged) (model card has the recipe, the six-generation honest eval arc, and `evals/` holds all 18 raw report JSONs) + [-lora](https://huggingface.co/Jainamshahhh/parry-tactician-1.5b-lora) |
+| 🦙 Llama Champion | [parry-tactician-1.5b-gguf](https://huggingface.co/Jainamshahhh/parry-tactician-1.5b-gguf) (Q4_K_M) runs through **llama.cpp's WASM runtime (wllama)** in-browser — look for "✦ tuned analyst (llama.cpp)" in the HUD |
+| 🎨 Off-Brand | The custom canvas you're looking at, served by `gr.Server` |
+| 📡 Sharing is Caring | [parry-traces](https://huggingface.co/datasets/Jainamshahhh/parry-traces) — real decision-by-decision agent traces; export your own with **B → Export trace**, validate via the `trace_digest` API |
+| 📓 Field Notes | [The full build report](https://huggingface.co/datasets/Jainamshahhh/parry-field-notes) — six model generations, three honestly-failed pre-registered gates, the engine-physics bug a playtest found, the imagination architecture, and the pose-mode saga |
 
 NOTE deploy: copy the built client (`npm run build` → `dist/`) into `static/` before
 pushing; `app.py` serves `static/index.html` at `/`.