feat: deploy training data to zoe root

AGENTS.md

@@ -21,6 +21,7 @@
 - Codex environment: `.codex/environments/environment.toml`
 - Training data dry run: `python3 scripts/generate_training_data.py --dry-run`
 - Local training data bridge: `python3 scripts/generate_training_data.py`
+- Deploy training data to Zoe: `scripts/deploy_training_data.sh`
 
 ## Environment
 
@@ -52,12 +53,14 @@ Use `.env` for local values and keep it out of git. Update `.env.example`, `READ
 
 - `SDG_BRIDGE_PLAN.md` documents the local-to-Data-Designer bridge design.
 - `scripts/generate_training_data.py` reads generated dictionary artifacts and produces instruction-format seed datasets.
-- Default output is `../workspace_Data/data/module_controller_intents_<unix_ts>/`.
-- Default manifest patch target is `../workspace_Data/manifest.llm.json`.
+- Default output is `/Volumes/Zoe/custom-local-llm/training-data/module_controller_intents_<unix_ts>/`.
+- Default manifest patch target is `/Volumes/Zoe/custom-local-llm/manifest.llm.json`.
+- `/Volumes/Zoe/custom-local-llm` has its own `README.md`, `AGENTS.md`, `manifest.llm.json`, and `llm.txt`.
 - Use `--dry-run` for validation; it must not write output data or patch manifests.
 - Mimir/Data Designer expansion only runs when `--sdg-host`, `--sdg-user`, and `--sdg-key` are all provided.
 - Do not start or restart Mimir llama.cpp/Keiro from this bridge.
 - If Mimir expansion fails, the bridge keeps the local seed dataset, writes `SDG_ERROR.txt`, patches the manifest with `generated_local_remote_failed`, and exits non-zero.
+- Woodpecker deploys training data on main-branch pushes with `scripts/deploy_training_data.sh`.
 
 ## Dispatch Rules