checkpoint

⚒️ Generated with [Fabro](https://fabro.sh)
This commit is contained in:
Fabro 2026-06-04 14:43:25 -04:00
parent 23318747ba
commit 84b9439e7b
5 changed files with 417 additions and 7 deletions

380
run.json
View file

@ -751,14 +751,145 @@
}
},
"web_url": "http://127.0.0.1:32276/runs/01KT9YT14FHDYA4VTV9DSFG0FY",
"start": null,
"status": {
"kind": "starting"
"start": {
"start_time": "2026-06-04T18:37:50.931282Z",
"run_branch": "fabro/run/01KT9YT14FHDYA4VTV9DSFG0FY",
"base_sha": "497aaba6f20c1fac052346c39f52e08fabadb179"
},
"status_updated_at": "2026-06-04T18:37:24.554599Z",
"last_event_at": "2026-06-04T18:37:50.090486Z",
"status": {
"kind": "running"
},
"status_updated_at": "2026-06-04T18:37:50.931347Z",
"last_event_at": "2026-06-04T18:43:25.295472Z",
"pending_control": null,
"checkpoints": [],
"checkpoints": [
{
"seq": 21,
"checkpoint": {
"timestamp": "2026-06-04T18:37:54.373323Z",
"current_node": "start",
"completed_nodes": [
"start"
],
"node_retries": {},
"context_values": {
"failure_signature": "",
"internal.run_id": "01KT9YT14FHDYA4VTV9DSFG0FY",
"internal.work_dir": "/home/daytona/workspace/fabro",
"internal.thread_id": null,
"graph.goal": "Build a terminal-based FreeCell solitaire game in Python",
"graph.fallback_retry_target": "impl_logic",
"internal.node_visit_count": 1,
"graph.default_max_retries": "3",
"internal.fidelity": "compact",
"failure_class": "",
"graph.retry_target": "impl_setup",
"graph.rankdir": "LR",
"internal.retry_count.start": 0,
"outcome": "succeeded",
"current_node": "start"
},
"node_outcomes": {
"start": {
"status": "succeeded",
"usage": null
}
},
"next_node_id": "expand_spec",
"node_visits": {
"start": 1
}
},
"diff": {}
},
{
"seq": 0,
"checkpoint": {
"timestamp": "2026-06-04T18:43:25.384822Z",
"current_node": "expand_spec",
"completed_nodes": [
"start",
"expand_spec"
],
"node_retries": {},
"context_values": {
"failure_class": "",
"graph.retry_target": "impl_setup",
"internal.thread_id": "start",
"last_response": "I have successfully written a comprehensive, detailed implementation specification for building a terminal-based FreeCell Solitaire game in Python.\n\nThe spec has been written to:\n- **Specification Doc",
"graph.default_max_retries": "3",
"current_node": "expand_spec",
"internal.fidelity": "compact",
"graph.goal": "Build a terminal-based FreeCell solitaire game in Python",
"graph.rankdir": "LR",
"failure_signature": "",
"last_stage": "expand_spec",
"internal.node_visit_count": 1,
"thread.start.current_node": "expand_spec",
"internal.retry_count.expand_spec": 0,
"internal.run_id": "01KT9YT14FHDYA4VTV9DSFG0FY",
"graph.fallback_retry_target": "impl_logic",
"internal.work_dir": "/home/daytona/workspace/fabro",
"internal.retry_count.start": 0,
"response.expand_spec": "I have successfully written a comprehensive, detailed implementation specification for building a terminal-based FreeCell Solitaire game in Python.\n\nThe spec has been written to:\n- **Specification Document**: `.ai/card-game-spec.md`\n- **Execution Status**: `status.json` with `\"outcome\": \"succeeded\"`\n\n### Key Specification Highlights:\n1. **Core Domain Model & Game Logic**: Complete decoupling from the curses framework. Classes like `Card`, `Suit`, `Rank`, `Deck`, `Position`, and `GameState` manage state transitions, move constraints, and game rules natively and cleanly, making them fully testable in headless CI environments.\n2. **Move Validation & Rule Logic**: Enforces all FreeCell moves, empty pile behavior, card stacking (alternating colors and descending ranks), and includes the mathematical sequence-movement rule constraint formula: \n $$\\text{Max Cards} = (1 + \\text{Empty Free Cells}) \\times 2^{\\text{Empty Tableau Columns}}$$\n3. **Auto-Homing Mechanics**: An optional, safe automated helper that automatically moves cards to the foundations once they can no longer act as sequence-building stepping stones.\n4. **Interactive Curses UI/TUI**: A detailed layout conforming to $80 \\times 24$ terminal dimensions using memory-efficient double-buffered updates via curses, rich color pair rendering for Red vs Black suits, and a versatile keyboard cursor-based layout navigation system.\n5. **Non-Interactive Smoke Mode**: Specifies the exact behavior of `python3 main.py --smoke` for fast automated integration checks without launching interactive screens.\n6. **Robust Testing Strategy**: Details unit tests covering edge cases for game rules, deterministic seed validation, and UI input mocking scenarios.",
"outcome": "succeeded"
},
"node_outcomes": {
"expand_spec": {
"status": "succeeded",
"context_updates": {
"last_stage": "expand_spec",
"response.expand_spec": "I have successfully written a comprehensive, detailed implementation specification for building a terminal-based FreeCell Solitaire game in Python.\n\nThe spec has been written to:\n- **Specification Document**: `.ai/card-game-spec.md`\n- **Execution Status**: `status.json` with `\"outcome\": \"succeeded\"`\n\n### Key Specification Highlights:\n1. **Core Domain Model & Game Logic**: Complete decoupling from the curses framework. Classes like `Card`, `Suit`, `Rank`, `Deck`, `Position`, and `GameState` manage state transitions, move constraints, and game rules natively and cleanly, making them fully testable in headless CI environments.\n2. **Move Validation & Rule Logic**: Enforces all FreeCell moves, empty pile behavior, card stacking (alternating colors and descending ranks), and includes the mathematical sequence-movement rule constraint formula: \n $$\\text{Max Cards} = (1 + \\text{Empty Free Cells}) \\times 2^{\\text{Empty Tableau Columns}}$$\n3. **Auto-Homing Mechanics**: An optional, safe automated helper that automatically moves cards to the foundations once they can no longer act as sequence-building stepping stones.\n4. **Interactive Curses UI/TUI**: A detailed layout conforming to $80 \\times 24$ terminal dimensions using memory-efficient double-buffered updates via curses, rich color pair rendering for Red vs Black suits, and a versatile keyboard cursor-based layout navigation system.\n5. **Non-Interactive Smoke Mode**: Specifies the exact behavior of `python3 main.py --smoke` for fast automated integration checks without launching interactive screens.\n6. **Robust Testing Strategy**: Details unit tests covering edge cases for game rules, deterministic seed validation, and UI input mocking scenarios.",
"last_response": "I have successfully written a comprehensive, detailed implementation specification for building a terminal-based FreeCell Solitaire game in Python.\n\nThe spec has been written to:\n- **Specification Doc"
},
"notes": "Stage completed: expand_spec",
"usage": {
"input": {
"usage": {
"model": {
"provider": "gemini",
"model_id": "gemini-3.5-flash"
},
"tokens": {
"input_tokens": 85925,
"output_tokens": 4840,
"reasoning_tokens": 3421,
"cache_read_tokens": 20271,
"cache_write_tokens": 0
}
},
"facts": {
"algorithm": "gemini",
"storage_segments": []
}
},
"total_usd_micros": 206276
},
"files_touched": [
"/home/daytona/workspace/fabro/.ai/card-game-spec.md",
"/home/daytona/workspace/fabro/status.json"
],
"timing": {
"wall_time_ms": 0,
"inference_time_ms": 111896,
"tool_time_ms": 4207,
"active_time_ms": 116103
}
},
"start": {
"status": "succeeded",
"usage": null
}
},
"next_node_id": "impl_setup",
"node_visits": {
"start": 1,
"expand_spec": 1
}
},
"diff": {}
}
],
"conclusion": null,
"sandbox": {
"kind": "ready",
@ -784,5 +915,240 @@
"pull_request": null,
"superseded_by": null,
"pending_interviews": {},
"stages": {}
"stages": {
"expand_spec@1": {
"first_event_seq": 22,
"prompt": null,
"response": null,
"completion": null,
"provider_used": {
"mode": "agent",
"provider": "gemini",
"model": "gemini-3.5-flash"
},
"diff": null,
"script_invocation": null,
"script_timing": null,
"parallel_results": null,
"output": null,
"started_at": "2026-06-04T18:37:54.373477Z",
"handler": "agent",
"usage": {
"input_tokens": 85925,
"output_tokens": 4840,
"total_tokens": 114457,
"reasoning_tokens": 3421,
"cache_read_tokens": 20271,
"cache_write_tokens": 0,
"total_usd_micros": 206276
},
"model": {
"provider": "gemini",
"model_id": "gemini-3.5-flash"
},
"permission_level": "full",
"agent_tools": [
{
"name": "close_agent",
"description": "Close a running subagent that is no longer needed.",
"source": {
"kind": "native"
},
"category": "subagent",
"invoked": false
},
{
"name": "edit_file",
"description": "Edit a file by replacing an exact string. The old_string must be an exact match and unique unless replace_all is true; include surrounding context when needed. Read the file first and preserve existing indentation.",
"source": {
"kind": "native"
},
"category": "write",
"invoked": false
},
{
"name": "glob",
"description": "Find files by file names using a glob pattern. Use path to choose the search root. Prefer this over shell find or ls when locating repository files.",
"source": {
"kind": "native"
},
"category": "read",
"invoked": true
},
{
"name": "grep",
"description": "Search file contents with a regex pattern. Use path to choose the search root, glob_filter to limit matching files, case_insensitive for case folding, and max_results to cap output.",
"source": {
"kind": "native"
},
"category": "read",
"invoked": false
},
{
"name": "list_dir",
"description": "List directory contents with depth control",
"source": {
"kind": "native"
},
"category": "read",
"invoked": true
},
{
"name": "read_file",
"description": "Read files before editing them. Returns line-numbered text and supports offset/limit for large files. Use this instead of shell cat, head, tail, or sed when inspecting repository files.",
"source": {
"kind": "native"
},
"category": "read",
"invoked": true
},
{
"name": "read_many_files",
"description": "Read multiple files at once",
"source": {
"kind": "native"
},
"category": "read",
"invoked": false
},
{
"name": "send_input",
"description": "Send a follow-up message to a running subagent when new information or corrected instructions are needed.",
"source": {
"kind": "native"
},
"category": "subagent",
"invoked": false
},
{
"name": "shell",
"description": "Execute shell commands for terminal operations, package managers, tests and builds. Use dedicated tools for file reads, file edits, filename searches, and content searches. Provide timeout_ms for long-running commands.",
"source": {
"kind": "native"
},
"category": "shell",
"invoked": false
},
{
"name": "spawn_agent",
"description": "Spawn a subagent for independent work or context isolation. Use it for tasks that can proceed separately, and avoid duplicating the same work in the parent session.",
"source": {
"kind": "native"
},
"category": "subagent",
"invoked": false
},
{
"name": "wait",
"description": "Wait for a subagent to complete, then use the result to synthesize the outcome for the user.",
"source": {
"kind": "native"
},
"category": "subagent",
"invoked": false
},
{
"name": "web_fetch",
"description": "Fetch content from a URL that starts with http:// or https://. Pass a prompt to extract specific information or summarize the page; omit prompt to return the page content.",
"source": {
"kind": "native"
},
"category": "other",
"invoked": false
},
{
"name": "web_search",
"description": "Search the web using Brave Search when current external information is needed. Returns result titles, URLs, and descriptions; use web_fetch for a specific URL.",
"source": {
"kind": "native"
},
"category": "other",
"invoked": false
},
{
"name": "write_file",
"description": "Create new files, or overwrite an existing file only when replacement is explicitly intended. Prefer edit_file for targeted changes to existing files because write_file overwrites the full file content.",
"source": {
"kind": "native"
},
"category": "write",
"invoked": true
}
],
"context_window": {
"provider": "gemini",
"model": "gemini-3.5-flash",
"context_window_tokens": 1048576,
"input_tokens": 18078,
"usage_percent": 1.7240524291992188,
"count_method": "response_usage_scaled_breakdown",
"staleness": "live",
"generated_at": "2026-06-04T18:43:25.295278Z",
"event_seq": 56,
"breakdown": [
{
"category": "system_prompt",
"tokens": 1344,
"usage_percent": 0.128173828125
},
{
"category": "tools",
"tokens": 1421,
"usage_percent": 0.13551712036132812
},
{
"category": "memory",
"tokens": 3849,
"usage_percent": 0.3670692443847656
},
{
"category": "conversation",
"tokens": 11458,
"usage_percent": 1.0927200317382812
},
{
"category": "other",
"tokens": 6,
"usage_percent": 0.00057220458984375
}
],
"warnings": []
},
"state": "running"
},
"start@1": {
"first_event_seq": 18,
"prompt": null,
"response": null,
"completion": {
"outcome": "succeeded",
"notes": null,
"failure_reason": null,
"timestamp": "2026-06-04T18:37:54.373021Z"
},
"provider_used": null,
"diff": null,
"script_invocation": null,
"script_timing": null,
"parallel_results": null,
"output": null,
"started_at": "2026-06-04T18:37:54.372698Z",
"handler": "start",
"timing": {
"wall_time_ms": 0,
"inference_time_ms": 0,
"tool_time_ms": 0,
"active_time_ms": 0
},
"usage": {
"input_tokens": 0,
"output_tokens": 0,
"total_tokens": 0,
"reasoning_tokens": 0,
"cache_read_tokens": 0,
"cache_write_tokens": 0
},
"state": "succeeded"
}
}
}

View file

@ -0,0 +1,6 @@
{
"outcome": "succeeded",
"notes": null,
"failure_reason": null,
"timestamp": "2026-06-04T18:37:54.373021Z"
}

View file

@ -0,0 +1,19 @@
Goal: Build a terminal-based FreeCell solitaire game in Python
Goal: $goal
Create a detailed implementation spec for the requested Python terminal card game.
Cover:
- Game rules and data structures (Card, Deck, Pile or equivalent state types)
- Terminal rendering approach using the standard-library curses module
- Input handling and move/action validation
- Win/loss detection
- UI layout
- Test strategy
Keep game rules testable without curses. Include a smoke mode so `python3 main.py --smoke` starts enough of the app to prove imports and setup without requiring an interactive terminal.
Write the spec to .ai/card-game-spec.md.
Write status.json at workspace root: outcome=succeeded if the spec is complete, outcome=failed with failure_reason otherwise.

View file

@ -0,0 +1,5 @@
{
"mode": "agent",
"provider": "gemini",
"model": "gemini-3.5-flash"
}

View file

@ -0,0 +1,14 @@
I have successfully written a comprehensive, detailed implementation specification for building a terminal-based FreeCell Solitaire game in Python.
The spec has been written to:
- **Specification Document**: `.ai/card-game-spec.md`
- **Execution Status**: `status.json` with `"outcome": "succeeded"`
### Key Specification Highlights:
1. **Core Domain Model & Game Logic**: Complete decoupling from the curses framework. Classes like `Card`, `Suit`, `Rank`, `Deck`, `Position`, and `GameState` manage state transitions, move constraints, and game rules natively and cleanly, making them fully testable in headless CI environments.
2. **Move Validation & Rule Logic**: Enforces all FreeCell moves, empty pile behavior, card stacking (alternating colors and descending ranks), and includes the mathematical sequence-movement rule constraint formula:
$$\text{Max Cards} = (1 + \text{Empty Free Cells}) \times 2^{\text{Empty Tableau Columns}}$$
3. **Auto-Homing Mechanics**: An optional, safe automated helper that automatically moves cards to the foundations once they can no longer act as sequence-building stepping stones.
4. **Interactive Curses UI/TUI**: A detailed layout conforming to $80 \times 24$ terminal dimensions using memory-efficient double-buffered updates via curses, rich color pair rendering for Red vs Black suits, and a versatile keyboard cursor-based layout navigation system.
5. **Non-Interactive Smoke Mode**: Specifies the exact behavior of `python3 main.py --smoke` for fast automated integration checks without launching interactive screens.
6. **Robust Testing Strategy**: Details unit tests covering edge cases for game rules, deterministic seed validation, and UI input mocking scenarios.