Update docs: CLI submission, agent identity, replay downloads, API endpoints

README.md

@@ -54,10 +54,46 @@ python evaluate.py \
 
 ### Submit results
 
+**Via CLI (recommended):**
+
+```bash
+pip install openra-rl
+openra-rl bench submit result.json
+openra-rl bench submit result.json --replay game.orarep --agent-name "MyBot" --agent-url "https://github.com/user/mybot"
+```
+
+Results from `openra-rl play` are auto-submitted after each game.
+
+**Via PR:**
+
 1. Fork this repo
 2. Run evaluation (appends to `data/results.csv`)
 3. Open a PR with your results
 
+### Agent identity
+
+Customize your leaderboard entry:
+
+| Field | Description |
+|-------|-------------|
+| `agent_name` | Display name (e.g. "DeathBot-9000") |
+| `agent_type` | `Scripted`, `LLM`, or `RL` |
+| `agent_url` | GitHub/project URL — renders as a clickable link on the leaderboard |
+
+### Replay downloads
+
+Entries submitted with a `.orarep` replay file show a download link in the Replay column. Replays are stored on the Space and served at `/replays/<filename>`.
+
+### API endpoints
+
+The Gradio app exposes these API endpoints (Gradio 5+ SSE protocol):
+
+| Endpoint | Description |
+|----------|-------------|
+| `submit` | Submit JSON results (no replay) |
+| `submit_with_replay` | Submit JSON + replay file |
+| `filter_leaderboard` | Query/filter leaderboard data |
+
 ## Scoring
 
 | Component | Weight | Description |

data/schema.md

@@ -14,4 +14,5 @@
 | `avg_economy` | float | Average final assets_value per game |
 | `avg_game_length` | int | Average game duration in ticks |
 | `timestamp` | str | Evaluation date (ISO 8601, YYYY-MM-DD) |
-| `replay_url` | str | URL to replay file(s), empty if none |
+| `replay_url` | str | Replay filename in submissions/, empty if none |
+| `agent_url` | str | GitHub/project URL for the agent, empty if none |