Restore archived tasks, fix dashboard scroll-reset, bind ornith, add Playwright smoke test
- **Restore 82 completed tasks** from tasks/complete/ back to tasks/ top level (all <7 days old per the cleanup policy; premature bulk archive was fixed). - **Dashboard: fix scroll-reset on auto-refresh** — renderBoard rebuilds the board via innerHTML every 2s, destroying each column-body's scrollTop. Now snapshots column-body scrollTop + board.scrollLeft + view.scrollTop before rebuild and restores after (matched by PHASE_GROUPS index). - **Dashboard UI additions** (pre-existing unstaged work): approval section cards, transition buttons, inline artifact editor (textarea for writing missing SPEC/VERDICT/etc from the detail modal). - **Bind ornith as Implement model** — config.md: Model explicit to omlx/Ornith-1.0-35B-4bit-mlx, context window 32768. Interactive autopilot already used ornith via opencode default; now explicit. - **Fix cleanup stub** — automaton-cleanup.sh had a stale --project arg pointing at a pytest temp dir (test isolation leak). Rewired to point at ~/.automaton. - **Fix plist-isolation test** — test asserted host plist doesn't exist, but a real install creates it. Now snapshots mtime before run, asserts unchanged after (only a write during the test counts as bleed). - **New Playwright smoke test** (tests/test_dashboard_ui.py) — 2 tests: board renders tasks, column scroll survives auto-refresh tick. Verified the test fails without the scroll fix (scrollTop resets to 0). Skipped via importorskip when playwright is absent (main CI stays green). - **Clarify SI loop scope in README** — new-project onboarding section documents the framework-scoped self-improvement loop and options (leave/pause/create project loop). - **CHANGELOG** documents all changes including the known model-divergence gap (mde tasks marked complete but per-role model binding was never implemented).
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# DECOMPOSITION — model-divergence-enforcement
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## Method
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Decompose by **dependency layer**, not by file. Each subtask builds on the previous
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one's foundation. The SPEC (`tasks/model-divergence-enforcement/SPEC.md`) defines 3
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sequential subtasks with strict dependency ordering.
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## Sub-tasks (3, sequential)
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### subtask-1: `mde-manifest-detection` (→ independent task)
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**Scope:** `models.json` schema + loader + `scripts/detect_models.py` probe + install integration.
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**Files touched:**
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- `scripts/detect_models.py` (new — probe opencode.json providers + localhost endpoints 8080/11434/1234/8000)
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- `scripts/status.py` (add `_load_models_manifest()` helper, `_get_mode()` — single vs multi-LLM)
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- `scripts/install.sh` (call `detect_models.py` after `vram_detect.py`)
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- `scripts/update.sh` (same)
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- `scripts/upgrade.sh` (same)
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- `config.md` (add `## Available Models` section template)
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- `prompts/onboarding.md` (Step 2d — model config check)
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- `tests/test_model_divergence.py` (new — manifest loading, single vs multi mode, missing file backward compat)
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**Not touched:** `status.py --transition`, `--claim`, `--audit`, `loop-runner.py`, dashboard code.
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**Acceptance:**
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1. `models.json` missing → `_get_mode()` returns `"single"`, all model commands are no-ops.
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2. `models.json` with 0-1 models → `_get_mode()` returns `"single"`.
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3. `models.json` with 2+ models → `_get_mode()` returns `"multi"`.
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4. `detect_models.py` probes localhost endpoints and prints a candidate manifest (JSON to stdout).
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5. `pytest tests/test_model_divergence.py -v` green.
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6. `pytest tests/ -q` green (no regressions).
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**Peak context estimate:** ~6k tokens (new script + status.py helper + tests).
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**Run order:** first. Foundational — subtasks 2 and 3 depend on this.
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### subtask-2: `mde-interactive-enforcement`
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**Scope:** `.state.models` schema + conflict matrix + `--transition --model` / `--claim --model` enforcement + audit category + dashboard badges.
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**Depends on:** subtask-1 (needs `_load_models_manifest()` and `_get_mode()`).
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**Files touched:**
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- `scripts/status.py`:
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- `CONFLICT_MATRIX` constant (locked matrix from SPEC §15)
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- `_check_conflict(current_phase, current_model, next_phase, next_model)` helper
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- `cmd_transition`: add `--model` arg; in multi-LLM mode, check conflict matrix before allowing transition
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- `cmd_claim`: add `--model` arg; refuse if model conflicts with existing `.state.models` entry
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- `cmd_audit`: add `model_divergence` category (scan `.state.models` for violations)
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- `.state.models` writer (JSON: `{implementer: "model-name", code_reviewer: "model-name", ...}`)
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- `automaton/dashboard/html/dashboard.js`: model badge on task cards (read from `.state.models`)
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- `automaton/dashboard/ui/app.py`: include `.state.models` in `/api/tasks` response
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- `tests/test_model_divergence.py`: conflict matrix tests, auto-assign tests, audit category tests, dashboard badge tests
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**Not touched:** `loop-runner.py`, `loop.json` schema, `--check-gate`.
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**Acceptance:**
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1. Single-LLM mode: `--transition --model <name>` records model but never refuses. Advisory printed once if `advised: true`.
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2. Multi-LLM mode: `--transition --model <name>` refuses if `<name>` conflicts with `.state.models` for a conflicting phase.
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3. Multi-LLM mode: `--claim --model <name>` refuses on conflict.
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4. `--audit` flags `model_divergence` violations (e.g., same model in implementer + code_reviewer).
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5. Dashboard task cards show model badges when `.state.models` exists.
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6. `pytest tests/test_model_divergence.py -v` green.
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7. `pytest tests/ -q` green (no regressions).
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**Peak context estimate:** ~8k tokens (status.py surgery + dashboard + tests).
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**Run order:** second, AFTER subtask-1.
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### subtask-3: `mde-loop-enforcement`
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**Scope:** `loop.json` per-role model field + `{model}` substitution in loop-runner + `--check-gate` model-divergence brake.
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**Depends on:** subtask-2 (needs `CONFLICT_MATRIX` and `_check_conflict`).
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**Files touched:**
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- `scripts/loop-runner.py`:
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- `_invoke_harness` (line 366-404): add `{model}` placeholder substitution from `loop.json` role config
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- `_find_work_backlog`: no change (already supports `work_source.area`)
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- `scripts/status.py`:
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- `--check-gate`: add model-divergence brake gate (loop-verify model ≠ loop-implement model in multi-LLM mode)
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- `cmd_install_schedule` / `cmd_create_loop`: validate `loop.json` per-role `model` fields against `models.json`
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- `templates/loops/`: update loop templates with `roles` schema example
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- `design/loops/technical.md`: document `{model}` substitution
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- `tests/test_model_divergence.py`: loop model binding tests, `{model}` substitution tests, check-gate halt tests
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**Not touched:** interactive `--transition` / `--claim` (already done in subtask-2), dashboard badges (already done in subtask-2).
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**Acceptance:**
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1. `loop.json` with `roles.implementer.model: "llama-3.3-70b"` → `_invoke_harness` substitutes `{model}` in harness command.
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2. `loop.json` without per-role `model` → defaults to `models.json` `default` model.
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3. `--check-gate` in multi-LLM mode halts loop if loop-verify model = loop-implement model.
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4. `--check-gate` in single-LLM mode does NOT halt (advisory only).
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5. `pytest tests/test_model_divergence.py -v` green.
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6. `pytest tests/ -q` green (no regressions).
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**Peak context estimate:** ~6k tokens (loop-runner + check-gate + tests).
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**Run order:** third, AFTER subtask-2.
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## Dependency graph
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```
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subtask-1 (manifest+detection)
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│
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▼
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subtask-2 (interactive enforcement+audit)
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│
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▼
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subtask-3 (loop enforcement+dashboard)
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│
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▼
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parent model-divergence-enforcement → complete
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```
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Parent is complete only when ALL three subtasks pass their acceptance criteria AND
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`pytest tests/ -q` is green.
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## Parent non-goals
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- No rule agents (FW-2, FW-3) — separate backlog items that *consume* this feature.
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- No agent tab redesign (FW-1) — separate backlog item, no dependency on this task.
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- No model capability inspection — framework never inspects capability/size/provider (decision D8).
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- No `detect_models.py` auto-writing `models.json` — detection is advisory; user confirms the manifest.
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## Fallback
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If any subtask hits a blocker (e.g., `status.py` surgery is too large for context budget),
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it must report back to the Orchestrator via `human_intervention` rather than skipping
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enforcement logic. Partial enforcement is worse than no enforcement — it creates a
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false sense of security.
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