diff --git a/openspec/changes/ts-as-modality/.comet/handoff/build-checkpoint.json b/openspec/changes/ts-as-modality/.comet/handoff/build-checkpoint.json
index 177f9c2..146dc0a 100644
--- a/openspec/changes/ts-as-modality/.comet/handoff/build-checkpoint.json
+++ b/openspec/changes/ts-as-modality/.comet/handoff/build-checkpoint.json
@@ -1,21 +1,26 @@
 {
   "change": "ts-as-modality",
   "phase": "build",
-  "checkpoint": "M2-complete",
+  "checkpoint": "M2-complete + M3-code-complete",
   "date": "2026-06-30",
-  "status": "in-progress",
-  "milestone": "M2 (model) complete; proceeding to M3 (training)",
-  "summary": "M2 done: TS Encoder + Projector + Multimodal splice + Wrapper (end-to-end, LoRA) + Collator. 91 tests passing. Stage ① fwd+bwd peak 2.34 GB (<5GB budget). Qwen2.5-0.5B-Instruct downloaded via socks proxy 10.66.66.4:1080 to ~/models/.",
-  "next_action": "T3.1 losses.py (lm_loss + contrastive_loss), T3.2 stage1 training script + smoke.",
+  "status": "paused-awaiting-user-decision",
+  "summary": "All M2 + M3 code written and smoke-verified. 100 tests passing. Remaining work (T3.3 onward) requires multi-hour GPU training of stage 1 (500k align samples), then M4 SFT (100k), then M5 eval.",
+  "next_action": "T3.3 TS-token effectiveness check — REQUIRES a trained stage 1 checkpoint (compute-heavy).",
+  "blocker": {
+    "reason": "T3.3+ need actual model training, not just code. Stage 1 design = 500k align.jsonl samples, ~10k steps. At ~3-5 it/s on RTX 3060 this is hours. Then M4 stage 2 (LoRA SFT, similar scale), then M5 full eval pipeline.",
+    "decision_pending": "User must decide training scope: (A) full design-scale training (generate 500k+100k data, train to completion, hours of GPU); (B) reduced-scale training (e.g. 50k samples, 2k steps — enough to produce a checkpoint and validate T3.3 effectiveness signal, defers full-quality); (C) write the remaining M4/M5 CODE now (stage2.py, eval modules) and smoke-verify, defer ALL training to user; (D) pause build.",
+    "recommendation": "C then B — finish all remaining code + smoke first (so everything is wired and verified), then do a reduced-scale stage1+stage2 training run to validate the end-to-end effectiveness signal, leaving full-scale training as a later user-initiated run."
+  },
   "environment": {
     "venv": ".venv (CUDA torch 2.5.1+cu121, transformers 5.12.1, peft 0.19.1)",
     "llm": "/home/zhangzp/models/Qwen2.5-0.5B-Instruct (hidden=896, 494M, bf16)",
-    "gpu": "RTX 3060 12GB (freed: killed vLLM + ts-abnormal procs)",
-    "proxy": "socks5h://10.66.66.4:1080 (for any further HF downloads)"
+    "gpu": "RTX 3060 12GB (~11.6 GB free)",
+    "proxy": "socks5h://10.66.66.4:1080"
   },
   "resume_instructions": {
-    "find_next_task": "grep -n '\\- \\[ \\]' openspec/changes/ts-as-modality/tasks.md | head -1  (expect T3.1)",
+    "find_next_task": "grep -n '\\- \\[ \\]' openspec/changes/ts-as-modality/tasks.md | head -1  (expect T3.3)",
     "venv": ".venv/bin/python",
+    "pythonpath": "export PYTHONPATH=src (needed for scripts; tests use pyproject pythonpath)",
     "branch": "feature/20260629/ts-as-modality",
     "build_mode": "executing-plans",
     "tdd_mode": "tdd",
@@ -23,15 +28,8 @@
     "isolation": "branch"
   },
   "completed_milestones": ["M1", "M2"],
-  "completed_tasks": ["1.1-1.7", "2.1-2.6"],
-  "test_count": 91,
-  "spec_clarifications_recorded": [
-    "n_patches = (T-P)//S+1 = 127 (design said 128)",
-    "channel-independent = shared per-channel patch embed + mean-pool → C-free output",
-    "encoder params ≈2.1M (design said ~4M)",
-    "multimodal splice appends answer+EOS for training",
-    "wrapper batch contract = {series, attributes, timestamps, events, question, answer}",
-    "encoder/projector fp32, output cast to LLM dtype (bf16)",
-    "build embedding layer with len(tokenizer) not vocab_size (special tokens)"
-  ]
+  "completed_tasks": ["1.1-1.7", "2.1-2.6", "3.1", "3.2"],
+  "test_count": 100,
+  "remaining_code_tasks": ["T4.1 stage2.py", "T5.1 parse_answer.py", "T5.2 ts_metrics.py", "T5.3 qa_judge.py", "T5.4 baselines.py", "T5.5 run_eval.sh"],
+  "remaining_compute_tasks": ["T3.3 effectiveness check (needs trained ckpt)", "T3.4 M3 exit", "T4.2 SFT instruction-following check", "M4 exit", "M5 exit"]
 }