compare

# Compare: same-epoch run comparison across trackers The most common comparison error is reporting "run A is 4 percentage points behind baseline" when run A is at epoch 11 of 100 and the baseline number is from epoch 100. The student is _still training_; the comparison is meaningless. This skill enforces same-epoch alignment. The agentic Stop hook routes here from `reason` when an assistant reports a delta without aligning the runs. ## When to run The user just said any of: - "compare run A to baseline / to run B" - "is my run improving / catching up / falling behind" - "rank these experiments" - "X vs Y wandb / neptune" - "track lag against baseline" ## Auto-detect the tracker Check in this order: 1. `WANDB_API_KEY` env var set, or `wandb` imports in the project → **wandb** 2. `NEPTUNE_API_TOKEN` env var set → **neptune** 3. `MLFLOW_TRACKING_URI` env var set, or `mlruns/` dir present → **mlflow** 4. `runs/` or `lightning_logs/` dir present → **tensorboard** 5. `*results*.json` / `*meta*.json` files in run dirs → **local file format** If none, ask the user where metrics live before guessing. ## The protocol ### 1. Identify the runs Get full names (no shortcodes). If the user says "fvs-fm vs the baseline", clarify: - which `fvs-fm` run (project + entity + run-id) - which baseline (full run name; baselines often have several variants) ### 2. Fetch metric history (not just final value) You need the full curve, not the last reported value. Final-value-only comparis...