checkpoint

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stages/007-verify_data@1/diff.patch

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+diff --git a/.ai/verify_data.md b/.ai/verify_data.md
+new file mode 100644
+index 000000000..aa6dfcaf0
+--- /dev/null
++++ b/.ai/verify_data.md
+@@ -0,0 +1,59 @@
++# Data Structures and Core Game State Verification Findings
++
++## 1. Overview and Command Execution
++We verified the core card game data structures, domain model classes, and test suite. The compilation and automated test run executed successfully:
++
++```bash
++cd card-game-app && python3 -m pytest tests/ -v && python3 -m py_compile main.py src/card_game_tui/*.py
++```
++
++**Results:**
++- **Pytest:** 13/13 tests passed successfully.
++- **Python Compilation:** All files compiled cleanly without syntax or import errors.
++
++---
++
++## 2. Core Game-State Types Defined
++
++The following models and enum types are defined in `src/card_game_tui/domain.py`:
++
++### Enums
++- **`Suit`**: Enum representing the four suits: `HEARTS` ("H"), `DIAMONDS` ("D"), `CLUBS` ("C"), and `SPADES` ("S"). Includes color classification (`RED` or `BLACK`) and UTF-8 symbols (`♥`, `♦`, `♣`, `♠`).
++- **`Rank`**: Enum representing ranks `ACE` (1) to `KING` (13) with appropriate alphanumeric labels (`A`, `J`, `Q`, `K`, or numeric string).
++- **`LocationType`**: Enum classifying board areas: `TABLEAU`, `FREECELL`, and `FOUNDATION`.
++
++### Core Data Classes & Entities
++- **`Card`**: Frozen dataclass containing `suit` and `rank`, with custom representation `[Rank][Suit]` (e.g., `A♥`, `10♠`).
++- **`Position`**: Frozen dataclass packaging `LocationType` and `index` for explicit target and source identification during gameplay.
++- **`MoveRecord`**: Stores move history containing `from_pos`, `to_pos`, moving cards list (`cards`), and a list of nested, cascaded `auto_moves` resulting from auto-homing.
++- **`Deck`**: Builds a standard 52-card deck, supports deterministic random seeding, and deals cards into the 8 Tableau columns (four columns of 7 cards, four columns of 6 cards).
++- **`GameState`**: Main orchestrator of the board. Holds state for:
++  - 8 Tableau columns
++  - 4 Free cells
++  - Foundations mapped by Suit
++  - Undo/Redo history stacks
++
++---
++
++## 3. Basic & Advanced Operations Verified
++
++### Move Validation and Rules Execution
++- **Single Card Moves:** Correctly validates moving a card to free cells (if empty) and to foundations (Aces first, then sequential cards of the matching suit).
++- **Tableau Placement rules:** Strictly enforces alternating colors and descending ranks (e.g., moving a Red 8 onto a Black 9).
++- **Sequence/Multi-Card Moves:** Computes valid transit capacities based on the exact FreeCell Solitaire formula:
++  $$\text{Max Cards} = (1 + \text{empty\_freecells}) \times 2^{\text{transit\_empty\_tableaus}}$$
++  Tested and verified that moves exceeding this threshold or violating sequential alternating order are rejected.
++
++### Cascade Auto-Homing
++- Safely moves cards to foundations automatically after a successful player move.
++- Avoids preemptive/unsafe auto-homing: a card is only auto-homed if its rank does not exceed $N+1$, where $N$ is the rank of the highest cards of the *opposite* color already placed in foundations. This prevents burying cards that might still be needed as Tableau anchors.
++- Cascades until no further eligible cards can be home-bound.
++
++### Command History (Undo / Redo)
++- Seamlessly reverts and reapplies moves.
++- Accurately tracks nested auto-homed moves so that undoing a player's move rolls back the cascading auto-homing moves in precise reverse order.
++
++---
++
++## 4. Conclusion
++The data model is fully complete, mathematically sound, robustly tested, and perfectly ready for consumption by the TUI layer.

stages/008-check_data@1/status.json

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+{
+  "outcome": "succeeded",
+  "notes": "Conditional node evaluated: check_data",
+  "failure_reason": null,
+  "timestamp": "2026-06-04T18:51:24.388447Z"
+}

stages/009-impl_logic@1/prompt.md

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+Goal: Build a terminal-based FreeCell solitaire game in Python
+
+## Completed stages
+- **expand_spec**: succeeded
+  - Model: gemini-3.5-flash, 85.9k tokens in / 8.3k out
+  - Files: /home/daytona/workspace/fabro/.ai/card-game-spec.md, /home/daytona/workspace/fabro/status.json
+- **impl_setup**: succeeded
+  - Model: gemini-3.5-flash, 144.1k tokens in / 6.8k out
+  - Files: /home/daytona/workspace/fabro/card-game-app/README.md, /home/daytona/workspace/fabro/card-game-app/main.py, /home/daytona/workspace/fabro/card-game-app/pyproject.toml, /home/daytona/workspace/fabro/card-game-app/src/card_game_tui/__init__.py, /home/daytona/workspace/fabro/card-game-app/src/card_game_tui/domain.py, /home/daytona/workspace/fabro/card-game-app/src/card_game_tui/tui.py, /home/daytona/workspace/fabro/card-game-app/tests/__init__.py, /home/daytona/workspace/fabro/card-game-app/tests/test_domain.py, /home/daytona/workspace/fabro/status.json
+- **verify_setup**: succeeded
+  - Model: gemini-3.5-flash, 185.9k tokens in / 2.2k out
+  - Files: /home/daytona/workspace/fabro/.ai/verify_setup.md, /home/daytona/workspace/fabro/status.json
+- **check_setup**: succeeded
+- **impl_data**: succeeded
+  - Model: gemini-3.5-flash, 179.9k tokens in / 32.0k out
+  - Files: /home/daytona/workspace/fabro/card-game-app/src/card_game_tui/domain.py, /home/daytona/workspace/fabro/card-game-app/tests/test_domain.py, /home/daytona/workspace/fabro/status.json
+- **verify_data**: succeeded
+  - Model: gemini-3.5-flash, 140.2k tokens in / 3.2k out
+  - Files: /home/daytona/workspace/fabro/.ai/verify_data.md, /home/daytona/workspace/fabro/status.json
+- **check_data**: succeeded
+
+
+Read .ai/card-game-spec.md and the current card-game-app implementation.
+
+Implement the requested card game's rules:
+- Initial setup/deal where applicable
+- Move/action validation
+- Auto-complete or helper actions where applicable
+- Win/loss condition
+- Undo
+
+Add tests for legal actions, illegal actions, win/loss detection, and edge cases.
+
+Run:
+cd card-game-app && python3 -m pytest tests/ -v
+
+Write status.json at workspace root: outcome=succeeded if all tests pass and rules are implemented, outcome=failed with failure_reason otherwise.

stages/009-impl_logic@1/provider_used.json

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+{
+  "mode": "agent",
+  "provider": "gemini",
+  "model": "gemini-3.5-flash"
+}

stages/009-impl_logic@1/response.md

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+I have successfully completed the tasks:
+
+1. **Reviewed Specifications & Game Rules:** Read `.ai/card-game-spec.md` and verified the domain models (`Card`, `Deck`, `LocationType`, `Position`, `MoveRecord`, and `GameState`).
+2. **Implemented/Enhanced Game Rules:**
+   - **Initial setup/deal:** Fully handled inside `Deck` and `GameState` constructor, dealing 52 unique cards deterministically.
+   - **Move/action validation:** Fully covered for tableau, free cell, and foundation moves, including proper transit and capacity calculations based on empty free cells/tableaus.
+   - **Auto-complete helper actions:** Standard auto-homing behavior is implemented, moving eligible cards to foundations automatically and cleanly nesting them in `MoveRecord` so they are fully undoable/redoable.
+   - **Win/loss condition:** Implemented and tested both `check_win()` and `check_loss()`. `check_loss()` correctly detects when the game has no legal moves remaining and is not yet won.
+   - **Undo/Redo:** Reverts and reapplies both the primary action and any nested auto-homing steps.
+3. **Tests:** Added comprehensive test cases to `tests/test_domain.py` to cover `check_loss` under various conditions (not lost, won, and fully locked/lost).
+4. **Validation:** Ran all tests with `pytest` successfully, and confirmed that the `--smoke` test successfully initializes and validates the game.
+5. **Status File:** Wrote `status.json` with `"outcome": "succeeded"`.