{"task_id":"st_01a0534b","status":"completed","residency_state":"evicted","parent_session_id":"01a04e1a-4e0a-7c69-845d-0b5d1e71f82d","root_session_id":"01a04e1a-4e0a-7c69-845d-0b5d1e71f82d","depth":1,"execution_mode":"in-process","model":"openai-codex/gpt-5.6-sol","notify_on_terminal":true,"created_at":"2026-08-30T15:30:14.996Z","updated_at":"2026-09-01T07:15:36.742Z","notification":{"run_epoch":1,"notified_epoch":1},"name":"nutrition-flow-simulator","task_summary":"Simulate realistic customer answers and identify blockers","description":"Simulate customer flow","category":"deep","requested_model":{"provider":"openai-codex","model_id":"gpt-5.6-sol","display":"openai-codex/gpt-5.6-sol","source":"category","variant":"medium","reasoning_effort":"medium"},"fallback_models":[{"provider":"clinepass","model_id":"cline-pass/deepseek-v4-pro","display":"clinepass/cline-pass/deepseek-v4-pro","source":"category","variant":"medium","reasoning_effort":"medium"},{"provider":"clinepass","model_id":"cline-pass/glm-5.2","display":"clinepass/cline-pass/glm-5.2","source":"category","variant":"medium","reasoning_effort":"medium"}],"resolved_model":{"provider":"openai-codex","model_id":"gpt-5.6-sol","display":"GPT-5.6 Sol","source":"category","variant":"medium","reasoning_effort":"medium"},"spawn_spec":{"version":1,"cwd":"/home/cube/projects/richard/traning coach","prompt":"Run a disposable, no-network customer simulation of post-consent nutrition onboarding and nutrition_daily check-in in /home/cube/projects/richard/.worktrees/nutricoach-v150-combined using existing tests/domain services. Use realistic Korean answers, malformed inputs, correction, back/skip/defer/resume, and final save. Do not touch the live profile or send Telegram messages. Deliver exact blockers/friction with evidence and a transcript-like step list. Do not edit files. Stop after both flows finish or an exact blocker is proven.\n\n<Category_Context name=\"deep\">\nYou are operating in DEEP mode. This is the category reserved for goal-oriented autonomous work on hairy problems that reward thorough exploration and comprehensive solutions.\n\nThe orchestrator chose this category because the task benefits from depth over speed. You should feel empowered to spend the time needed: five to fifteen minutes of silent exploration before the first edit is normal and correct. Rushing to implementation on a deep task is a failure mode, not a feature.\n\n# How deep mode adjusts the base behavior\n\n**Exploration budget: generous.** Read the files you need, trace dependencies both directions, fire 2-5 explore/librarian sub-agents in parallel for broader questions. Build a complete mental model before the first `apply_patch`. Exploration here is an investment, not overhead.\n\n**Goal, not plan.** You receive a GOAL describing the desired outcome. You figure out HOW to achieve it. The orchestrator deliberately did not hand you a step-by-step plan; producing one and asking for approval is not what was asked. Execute.\n\n**Atomic task treatment.** When the goal contains numbered steps or phases, treat them as sub-steps of ONE task and execute them all in this turn. Splitting them across turns is wrong unless they reveal an architectural blocker that requires the user's input. If the \"steps\" turn out to be genuinely independent tasks that should have been separate delegations, flag that in your final message and refuse the ones beyond scope.\n\n**Root cause bias.** Prefer root-cause fixes over symptom fixes. A null check around `foo()` is a symptom fix; fixing whatever causes `foo()` to return unexpected values is the root fix. Trace at least two levels up before settling on an answer. In deep mode, you have permission (and the expectation) to do the deeper fix.\n\n**Ambition scaled to context.** For brand-new greenfield work, be ambitious. Choose strong defaults, avoid AI-slop aesthetics, produce something you would be proud to hand to another senior engineer. For changes in an existing codebase, be surgical and respect the existing patterns; depth does not mean invasiveness.\n\n**Completion bar: full delivery.** \"Simplified version\", \"proof of concept\", and \"you can extend this later\" are not acceptable deliveries for a deep task. The orchestrator routed here specifically for a complete solution. If you hit a genuine blocker (missing secret, design decision only the user can make, three materially different attempts all failed), document it and return; otherwise, finish the task.\n\n**Status cadence: sparse.** The user is not on the other side of this conversation; the orchestrator is, and they will synthesize your progress. Send commentary only at meaningful phase transitions (starting exploration, starting implementation, starting verification, hitting a genuine blocker). Do not narrate every tool call; silence during focused work is expected.\n</Category_Context>"},"host_pid":1353625,"final_response":"I read this as completed regression verification - both disposable flows now pass all requested checks with no product blockers.\n\n## Result: PASS\n\nFocused suite:\n\n```text\ntests/gateway/test_customer_nutrition_ux.py\n18 passed in 0.39s\n```\n\n## Evidence\n\n### Post-consent onboarding\n\n- **Malformed closed choice rejected immediately — PASS**\n  - Input: `남자 같아요`\n  - Error: `invalid closed choice`\n  - Cursor remained at `equation_sex_basis`, count stayed `1`.\n  - Recovery: `답을 이해하지 못했어요. 입력한 내용은 저장하지 않았습니다.`\n\n- **Inline Back/Skip/Defer rendered — PASS**\n  - At optional `activity_rationale`, rendered actions were exactly:\n    ```text\n    이전 / 건너뛰기 / 나중에 계속\n    ```\n  - `force_reply=false`, so controls are directly usable.\n  - Back returned from count 5 to count 4.\n  - Skip stored the optional default and advanced to count 6.\n  - Defer/resume reconstructed the service at the same cursor: `6/22`, `goal_type`.\n\n- **Natural Korean shorthand — PASS**\n  - `1990. 3. 2.` -> `1990-03-02`\n  - `남자` -> `male`\n  - `3` activity -> `moderate`\n  - `살 빼기` -> `loss`\n  - `없어요` -> structured none\n  - `2` pregnancy answer -> `False`\n  - `보통 하루 세끼 먹어요` -> `3`\n\n- **Completion — PASS**\n  - Validation issues: `0`\n  - Safety holds: `0`\n  - Final customer state: `owner_review`\n  - Disposable baseline created successfully.\n\n### nutrition_daily\n\n- **Inline navigation rendered — PASS**\n  - First question: `나중에 계속`\n  - Subsequent question: `이전 / 나중에 계속`\n  - Optional-note skip is rendered as the customer-facing `없음` one-tap button.\n\n- **Invalid macros field-specific recovery — PASS**\n  - Input: `대충 먹었어요`\n  - Accepted: `false`\n  - Remained at `macros`\n  - Exact recovery:\n    ```text\n    입력한 내용은 저장하지 않았습니다.\n\n    탄수화물·단백질·지방을 순서대로 입력해 주세요.\n    예: 280 150 65\n    ```\n\n- **Defer/resume — PASS**\n  - Notice: `나중에 여기서 이어갈 수 있도록 임시 저장했습니다.`\n  - New bridge/service resumed at `water`, progress `5/12`.\n\n- **Normal digestion mapping — PASS**\n  - Button: `정상 · 매끈하고 부드러움 (4)`\n  - Stored value: `normal`\n  - Final event: `\"digestion_summary\": \"normal\"`\n\n- **No-workout one-tap — PASS**\n  - Buttons: `운동 안 함 / 운동 내용 입력`\n  - `운동 안 함` advanced directly to `optional_note`.\n  - Summary displayed `운동: -`.\n  - Final event stored `\"training_summary\": \"\"`.\n\n- **Edit/save — PASS**\n  - Edited macros from `255 145 62` to `250 148 61`.\n  - Returned to summary and saved successfully.\n  - Exactly one event persisted:\n    - `carbohydrate_g: 250`\n    - `protein_g: 148`\n    - `fat_g: 61`\n  - Confirmation: `✅ 오늘 체크인을 저장했습니다.`\n\n## Isolation\n\n- Live profile touched: **false**\n- Telegram messages sent: **0**\n- Outbound DNS/connect events: **0**\n- All simulation artifacts stayed under a temporary directory and were removed.\n- Source files edited: **none**\n\nOne harness-only issue occurred initially: blocking every socket prevented `asyncio` from creating its local Unix `socketpair`. The rerun allowed local event-loop plumbing while still rejecting DNS and outbound connections. No product blocker remains.","run_stats":{"runtime_ms":169651,"turns":7,"tool_calls":14,"output_tokens":8190,"input_tokens":44224,"cache_read_tokens":1054208,"total_tokens":1106622,"generation_ms":164291,"tokens_per_second":50,"cost_usd":0.993924,"cache_hit_rate_last":0.974070539984709,"cache_hit_rate_run":0.9597389733729534,"token_status":"complete","cost_status":"reported","duration_status":"monotonic"},"task_seq":23,"config_generation":0,"background_mode":"background"}