docs: plan v1.2 trajectory recognition workflow

docs/superpowers/plans/2026-05-29-v1.2-trajectory-recognition.md

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+# v1.2 Trajectory Recognition Implementation Plan
+
+> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.
+
+**Goal:** Add source-zone trajectory evidence so alarmed items moved to the trash are discarded by their actual source zone, while keeping YOLO as a future optional backend.
+
+**Architecture:** Extend `Observation` with backend-neutral `disposal_evidence`, make `BatchEngine` consume matching evidence before generic trash fallback, then add a no-dependency motion trajectory tracker in the vision layer. Runtime writes diagnostics and uses faster sampling only while trajectory candidates are active.
+
+**Tech Stack:** Python 3.11+ standard library, existing `Frame` RGB bytes, `unittest`, Vite/Node tests only if frontend files change.
+
+---
+
+### Task 1: Data Contract And Engine Evidence Handling
+
+**Files:**
+- Modify: `src/cold_display_guard/models.py`
+- Modify: `src/cold_display_guard/engine.py`
+- Test: `tests/test_engine.py`
+
+- [ ] **Step 1: Write failing tests**
+
+Add tests for:
+- `Observation.from_dict()` normalizes `disposal_evidence`.
+- Matching evidence discards the pending batch for the same source zone.
+- Evidence for zone 4 does not discard pending zone 1.
+- Same-observation removal plus evidence closes the newly pending batch.
+- Low-confidence evidence is ignored.
+
+- [ ] **Step 2: Run RED tests**
+
+Run: `PYTHONPATH=src python3 -m unittest tests.test_engine -v`
+
+Expected: FAIL because `Observation` has no `disposal_evidence` and engine ignores evidence.
+
+- [ ] **Step 3: Implement minimal contract and engine logic**
+
+Add a `DisposalEvidence` dataclass and `Observation.disposal_evidence`. In `BatchEngine.process()`, apply evidence to matching `pending_disposal` before generic trash deposits and again after zone transitions for same-frame removals.
+
+- [ ] **Step 4: Run GREEN tests**
+
+Run: `PYTHONPATH=src python3 -m unittest tests.test_engine -v`
+
+Expected: PASS.
+
+- [ ] **Step 5: Commit phase**
+
+Run:
+
+```bash
+git add src/cold_display_guard/models.py src/cold_display_guard/engine.py tests/test_engine.py
+git commit -m "feat: add disposal evidence engine handling"
+```
+
+### Task 2: Lightweight Motion Trajectory Backend
+
+**Files:**
+- Modify: `src/cold_display_guard/vision.py`
+- Test: `tests/test_vision.py`
+
+- [ ] **Step 1: Write failing tests**
+
+Add synthetic RGB-frame tests for:
+- Motion from source zone to trash ROI emits evidence.
+- Motion that starts away from source zone is rejected.
+- Motion that never reaches trash ROI is rejected.
+- One-frame reflection flash is rejected.
+- Multiple active candidates do not cross-close each other.
+
+- [ ] **Step 2: Run RED tests**
+
+Run: `PYTHONPATH=src python3 -m unittest tests.test_vision -v`
+
+Expected: FAIL because no trajectory tracker exists.
+
+- [ ] **Step 3: Implement minimal motion tracker**
+
+Add trajectory settings, candidate state, motion blob extraction from frame deltas, confidence scoring, and diagnostics. Keep the implementation standard-library only.
+
+- [ ] **Step 4: Run GREEN tests**
+
+Run: `PYTHONPATH=src python3 -m unittest tests.test_vision -v`
+
+Expected: PASS.
+
+- [ ] **Step 5: Commit phase**
+
+Run:
+
+```bash
+git add src/cold_display_guard/vision.py tests/test_vision.py
+git commit -m "feat: add lightweight trajectory tracking"
+```
+
+### Task 3: Runtime Configuration And Diagnostics Integration
+
+**Files:**
+- Modify: `src/cold_display_guard/main.py`
+- Modify: `src/cold_display_guard/vision.py`
+- Modify: `config/example.toml`
+- Test: `tests/test_vision.py`
+- Test: `tests/test_main.py`
+
+- [ ] **Step 1: Write failing tests**
+
+Add tests that verify runtime defaults include trajectory settings with YOLO disabled and diagnostics rows include emitted evidence when present.
+
+- [ ] **Step 2: Run RED tests**
+
+Run: `PYTHONPATH=src python3 -m unittest tests.test_vision tests.test_main -v`
+
+Expected: FAIL because runtime does not pass evidence into `Observation` or expose trajectory sampling state.
+
+- [ ] **Step 3: Implement runtime integration**
+
+Return `disposal_evidence` from vision observation, write it to diagnostics, pass it to `Observation`, and use `trajectory_sample_interval_seconds` while candidates are active.
+
+- [ ] **Step 4: Run GREEN tests**
+
+Run: `PYTHONPATH=src python3 -m unittest tests.test_vision tests.test_main -v`
+
+Expected: PASS.
+
+- [ ] **Step 5: Commit phase**
+
+Run:
+
+```bash
+git add src/cold_display_guard/main.py src/cold_display_guard/vision.py config/example.toml tests/test_vision.py tests/test_main.py
+git commit -m "feat: integrate trajectory runtime diagnostics"
+```
+
+### Task 4: Documentation, Full Verification, And Deployment Prep
+
+**Files:**
+- Modify: `README_zh.md`
+- Modify: `docs/project.md`
+- Modify: `task_plan.md`
+- Modify: `findings.md`
+- Modify: `progress.md`
+- Modify: `memories.md`
+
+- [ ] **Step 1: Update docs**
+
+Document v1.2 trajectory settings, evidence semantics, tests, and remote deployment notes.
+
+- [ ] **Step 2: Run full verification**
+
+Run:
+
+```bash
+PYTHONPATH=src python3 -m unittest discover -s tests -v
+node --test web/test/zone-state.test.js
+cd web && pnpm build
+```
+
+Expected: PASS for all commands. If frontend files did not change, frontend commands still provide regression coverage for the management console.
+
+- [ ] **Step 3: Commit phase**
+
+Run:
+
+```bash
+git add README_zh.md docs/project.md task_plan.md findings.md progress.md memories.md docs/superpowers/plans/2026-05-29-v1.2-trajectory-recognition.md
+git commit -m "docs: document v1.2 trajectory recognition"
+```
+
+- [ ] **Step 4: Prepare remote deploy**
+
+Use rsync excluding `config/example.toml`, rebuild runtime/API, and verify Docker services. Record the exact commands and results in `progress.md`.