Make README.md static (no game count; restore curated card)

README.md

@@ -1,19 +1,76 @@
+---
+license: mit
+pretty_name: Hexo Human Corpus (encoding-free)
+task_categories:
+  - other
+tags:
+  - hex
+  - hex-tac-toe
+  - board-games
+  - game-records
+  - reinforcement-learning
+  - alphazero
+size_categories:
+  - 1K<n<10K
+---
+
 # Hexo Human Corpus
 
-Encoding-free corpus of **8300** decisive human *Hex Tac Toe*
-games (hexagonal grid, six-in-a-row to win). Each line is one game as a raw
-axial move list plus outcome — build any encoding you like on top.
+Encoding-free corpus of decisive human *Hex Tac Toe* games — hexagonal grid,
+six-in-a-row to win (player 1 opens with 1 move, then both players play 2 moves
+per turn; the board is theoretically infinite).
+
+Each line is one game as a **raw axial move list + outcome**. Nothing about any
+neural-network encoding is baked in — no planes, no fixed board size, no action
+space. Read it with the stdlib `json` module and build whatever representation
+you want.
+
+## Files
+
+| file | description |
+|------|-------------|
+| `hexo_human_corpus.jsonl` | the corpus — one game per line |
+| `SCHEMA.md` | full per-line schema + conventions |
+| `dataset_metadata.json` | provenance: counts, sha256, source filter |
+
+## Schema
+
+One JSON object per line:
+
+```json
+{"game_hash":"0f8c6bdfc55e7f6f","moves":[[0,0],[2,-2],[-3,3]],"winner":1,"source":"human","elo":[898,955]}
+```
+
+| field | type | meaning |
+|-------|------|---------|
+| `game_hash` | string (16 hex) | SHA-256 of the move sequence — stable content/dedup key |
+| `moves` | array of `[x, y]` | axial hex coords `(x,y)=(q,r)`, in play order |
+| `winner` | `1` or `-1` | `1` = first player (X) wins, `-1` = second player (O) |
+| `source` | string | `"human"` |
+| `elo` | `[int\|null, int\|null]` | `[elo_p1, elo_p2]` |
+
+**Conventions**
+
+- Axial hex coordinates `(x, y)`; the board is infinite so values can be
+  negative. The first player's forced opener is always `(0, 0)`.
+- Replay `moves` in order to reconstruct any board state.
+- Only decisive (six-in-a-row) games are included — there are **no draws**.
 
-See `SCHEMA.md` for the per-line schema and `dataset_metadata.json` for full
-provenance (sha256, counts, source filter).
+## Usage
 
 ```python
 import json
-with open("hexo_human_corpus.jsonl") as f:
-    for line in f:
-        game = json.loads(line)
-        moves, winner = game["moves"], game["winner"]
+
+games = [json.loads(line) for line in open("hexo_human_corpus.jsonl")]
+g = games[0]
+print(g["moves"], g["winner"])      # [[0,0], [2,-2], ...]  1
 ```
 
-- Coordinates: axial hex `(x,y)`, infinite board, opener at `(0,0)`.
-- Winner: `1` = first player (X), `-1` = second player (O). No draws.
+## Provenance
+
+Rated human games filtered to: rated, ≥20 moves, decisive by six-in-a-row.
+Per-game `elo` is each player's rating at game time. Games are anonymised
+(player ids dropped; only relative Elo retained). See `dataset_metadata.json`
+for the exact game count and sha256.
+
+License: MIT.