zero-token collaborator flow: deploy-key quickstart + auto results push (PUSH_RESULTS)

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01GkgLsACEF6CCP7EUfA5fZe

1 files changed, 13 insertions, 0 deletions

diff --git a/README.md b/README.md
index 7b4f7a3..240b6f2 100644
--- a/README.md
+++ b/README.md
@@ -54,6 +54,19 @@ Analysis (anywhere): `python scripts/plot_ladder.py --results results/h200node1`
 curves, and the gap-vs-scale figure (the paper's part-2 headline). If a specific checkpoint is needed for
 the estimator audits, scp just that `runs/<name>/ckpt.pt`.
 
+## Collaborator quickstart (zero tokens on the node)
+You receive ONE file: the deploy key `zbp_scaling_deploy` (scoped to this repo only, revocable). Then:
+```
+install -m 600 zbp_scaling_deploy ~/.ssh/zbp_scaling_deploy
+git clone -c core.sshCommand="ssh -i ~/.ssh/zbp_scaling_deploy -o IdentitiesOnly=yes" \
+    git@github.com:YurenHao0426/zbp-scaling.git
+cd zbp-scaling && ./scripts/run_ladder.sh   # env check -> data prep -> ladder -> results auto-pushed back
+```
+The `-c` persists `core.sshCommand` inside the clone, so the auto-push at the end works with no env setup
+(nohup-safe; set `PUSH_RESULTS=0` to disable). No GitHub account, no HF token on the node: results JSONL
+flow back through the deploy key; checkpoints stay on the node (scp on request) and HF uploads happen on
+the maintainer's machine.
+
 ## HF upload & security (shared nodes)
 Results (and optionally checkpoints) can go to a **private** HF repo: `HF_UPLOAD=1 [HF_CKPT=1] ./scripts/run_ladder.sh`
 or manually `python scripts/upload_hf.py --results results/<tag> [--with-ckpt runs]` (default repo