{"task_id":"st_01a0562d","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-5.4-mini","notify_on_terminal":true,"created_at":"2026-08-31T04:56:38.624Z","updated_at":"2026-09-01T12:57:51.646Z","notification":{"run_epoch":1,"notified_epoch":1},"name":"onboarding-contract-trace","task_summary":"Trace conditional onboarding compatibility","description":"onboarding-contract-trace","agent_type":"explore","tool_allow":["read","find","grep","ls","bash","lsp_diagnostics","lsp_goto_definition","lsp_find_references","lsp_symbols"],"requested_model":{"provider":"clinepass","model_id":"cline-pass/deepseek-v4-flash","display":"clinepass/cline-pass/deepseek-v4-flash","source":"agent","reasoning_effort":"low"},"fallback_models":[{"provider":"openai-codex","model_id":"gpt-5.6-luna","display":"openai-codex/gpt-5.6-luna","source":"agent","reasoning_effort":"high"}],"fallback_attempts":[{"provider":"clinepass","model_id":"cline-pass/deepseek-v4-flash","display":"clinepass/cline-pass/deepseek-v4-flash","source":"agent","reasoning_effort":"low","reasoning":"low"},{"provider":"openai-codex","model_id":"gpt-5.4-mini","display":"openai-codex/gpt-5.4-mini","source":"agent","reasoning_effort":"medium"}],"resolved_model":{"provider":"openai-codex","model_id":"gpt-5.4-mini","display":"openai-codex/gpt-5.4-mini","source":"agent","reasoning_effort":"medium"},"spawn_spec":{"version":1,"cwd":"/home/cube/projects/richard/traning coach","prompt":"Trace every use of QUESTION_FIELDS, date_of_birth, cursor, answer_count, and onboarding session schema in /home/cube/projects/richard/.worktrees/nutricoach-v150-combined. Deliver a compatibility-safe minimal design for conditional questions (maintain skips targets; loss/gain require them), replacing full DOB with age while loading in-flight legacy sessions, and merging repetitive food-preference prompts without losing baseline fields. Read-only. Return exact files/symbols/tests and risks.","instructions":"You are a codebase search specialist. Your job: find files and code, return actionable results.\n\n## Your Mission\n\nAnswer questions like:\n- \"Where is X implemented?\"\n- \"Which files contain Y?\"\n- \"Find the code that does Z\"\n\n## CRITICAL: What You Must Deliver\n\nEvery response MUST include:\n\n### 1. Intent Analysis (Required)\nBefore ANY search, wrap your analysis in <analysis> tags:\n\n<analysis>\n**Literal Request**: [What they literally asked]\n**Actual Need**: [What they're really trying to accomplish]\n**Success Looks Like**: [What result would let them proceed immediately]\n</analysis>\n\n### 2. Parallel Execution (Required)\nLaunch **3+ tools simultaneously** in your first action. Never sequential unless output depends on prior result.\n\n### 3. Structured Results (Required)\nAlways end with this exact format:\n\n<results>\n<files>\n- /absolute/path/to/file1.ts - [why this file is relevant]\n- /absolute/path/to/file2.ts - [why this file is relevant]\n</files>\n\n<answer>\n[Direct answer to their actual need, not just file list]\n[If they asked \"where is auth?\", explain the auth flow you found]\n</answer>\n\n<next_steps>\n[What they should do with this information]\n[Or: \"Ready to proceed - no follow-up needed\"]\n</next_steps>\n</results>\n\n## Success Criteria\n\n- **Paths** - ALL paths must be **absolute** (start with /)\n- **Completeness** - Find ALL relevant matches, not just the first one\n- **Actionability** - Caller can proceed **without asking follow-up questions**\n- **Intent** - Address their **actual need**, not just literal request\n\n## Failure Conditions\n\nYour response has **FAILED** if:\n- Any path is relative (not absolute)\n- You missed obvious matches in the codebase\n- Caller needs to ask \"but where exactly?\" or \"what about X?\"\n- You only answered the literal question, not the underlying need\n- No <results> block with structured output\n\n## Constraints\n\n- **Read-only**: You cannot create, modify, or delete files\n- **No emojis**: Keep output clean and parseable\n- **No file creation**: Report findings as message text, never write files\n\n## Tool Strategy\n\nUse the right tool for the job:\n- **Semantic search** (definitions, references): LSP tools (lsp_goto_definition, lsp_find_references, lsp_symbols, lsp_diagnostics)\n- **Structural patterns** (function shapes, class structures): combine LSP symbols/references with focused grep and read calls\n- **Text patterns** (strings, comments, logs): grep\n- **File patterns** (find by name/extension): find\n- **Remote evidence**: use the structured read-only bash broker only for supported gh or HTTPS retrieval requests; it is not a general shell\n\nFlood with parallel calls. Cross-validate findings across multiple tools."},"host_pid":1353625,"final_response":"<results>\n<files>\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/checkin_cli/nutrition_onboarding_contract.py - `QUESTION_FIELDS`, `OnboardingStatus.answer_count`, `example_answer()`, canonical field order\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/checkin_cli/nutrition_onboarding_session.py - session schema reader; `cursor` -> `answer_count`/`next_field`\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/checkin_cli/nutrition_onboarding.py - onboarding session JSON schema (`schema_version`, `review_flow`, `cursor`, `answers`, `consumed_updates`), ordering/revision logic\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/checkin_cli/nutrition_onboarding_models.py - `date_of_birth` -> `adult_age` migration (`build_onboarding_baseline`, `derive_adult_age`)\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/checkin_cli/nutrition_onboarding_clarification_policy.py - conditional target-field rules (`maintain_forbids_targets`, `loss_gain_requires_targets`)\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/checkin_cli/nutrition_onboarding_clarification_rules.py - human copy for DOB/food/target clarifications\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/checkin_cli/nutrition_onboarding_reconciliation.py - persisted reconciliation schema and `QUESTION_FIELDS` validation\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/checkin_cli/nutrition_onboarding_finalization.py - baseline artifact writes `adult_age` + all food-preference baseline fields\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/gateway/platforms/telegram_nutrition_onboarding.py - transport contract; optional question defaults\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/gateway/platforms/telegram_nutrition_onboarding_copy.py - prompt text/parser for DOB + repeated food-preference prompts\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/gateway/platforms/telegram_nutrition_onboarding_runtime_publication.py - UI uses `answer_count`, `QUESTION_FIELDS`, skip button gating\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/gateway/platforms/telegram_nutrition_onboarding_runtime_publication_transport.py - `publication_generation()` depends on `answer_count`\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/gateway/platforms/telegram_nutrition_onboarding_runtime_callback.py - skip/prev/revise transitions\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/gateway/platforms/telegram_nutrition_onboarding_runtime_collection.py - text intake, `parse_answer()`, skip handling\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/gateway/platforms/telegram_nutrition_onboarding_preview_types.py - isolated preview session schema; `cursor`\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/gateway/platforms/telegram_nutrition_onboarding_preview_flow.py - preview cursor progression over `QUESTION_FIELDS`\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/gateway/platforms/telegram_nutrition_onboarding_preview_publication.py - preview session payload stores `len(QUESTION_FIELDS)`\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/gateway/platforms/telegram_nutrition_onboarding_preview_completion.py - preview clarification/summary rendering\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/tests/test_nutrition_onboarding.py - service flow, cursor restart, target-field, safety-hold, cancel/finalization regressions\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/tests/test_nutrition_onboarding_models.py - DOB-to-age canonicalization tests\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/tests/test_nutrition_onboarding_clarification_policy.py - maintain vs loss/gain target requirements, DOB issue mapping\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/tests/test_nutrition_onboarding_calculations.py - baseline/plan behavior for maintain vs loss/gain\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/tests/gateway/test_customer_nutrition_ux.py - customer-facing parse/skip/navigation UX\n</files>\n\n<answer>\nCore flow:\n- `QUESTION_FIELDS` is the canonical ordered schema everywhere.\n- Session persistence uses a private JSON document with `cursor`; `build_status()` exposes that as `answer_count`.\n- New sessions are created in `nutrition_onboarding.py` with `schema_version=2.0`, `review_flow=owner_v1`, `cursor=0`, `answers={}`.\n- `submit_answer()` enforces exact order by `QUESTION_FIELDS[cursor]`.\n- `reopen_revision()` rewinds by `QUESTION_FIELDS.index(field)` and restores only the retained prefix.\n- Validation/reconciliation/finalization all still expect the full canonical field set.\n\nCompatibility-safe minimal design:\n1. Keep `QUESTION_FIELDS` as the superset schema; do not reorder it.\n2. Add a small question-routing helper that decides whether to ask a field.\n   - `target_weight_kg`/`target_date` are skipped when `goal_type == \"maintain\"`.\n   - They remain required for `loss`/`gain`.\n   - Persist skipped target fields as canonical `None` so `cursor`/`answer_count` stay aligned.\n3. Migrate DOB to age at load time for in-flight legacy sessions.\n   - On resume, if a session still carries `date_of_birth`, derive `adult_age`, redact `date_of_birth`, and continue with the normalized session.\n   - Keep baseline output unchanged: it already stores `adult_age` only.\n4. Merge repetitive food-preference prompts through one structured-field prompt template.\n   - Use a shared prompt map for `allergies`, `intolerances`, `religious_ethical_exclusions`, `disliked_foods`, `dietary_preferences`, `conditions`, `medications`.\n   - Do not collapse the underlying baseline fields; final artifacts still need them separately.\n\nMain risks:\n- Any change to `QUESTION_FIELDS` length/order breaks `answer_count`, preview numbering, reconciliation, and existing golden tests.\n- Conditional skipping must not desync `cursor` from persisted answers or `prev`/`publication_generation`.\n- DOB migration must be one-way and atomic; mixed `date_of_birth` + `adult_age` payloads will invalidate baseline building.\n- Prompt dedupe must not merge the actual baseline fields, only their wording.\n</answer>\n\n<next_steps>\nReady to proceed - no follow-up needed.\n</next_steps>\n</results>","run_stats":{"runtime_ms":229982,"turns":19,"tool_calls":72,"output_tokens":12909,"input_tokens":149067,"cache_read_tokens":1827840,"total_tokens":1989816,"generation_ms":208421,"tokens_per_second":62,"cost_usd":0.30697875,"cache_hit_rate_last":0.972214687076148,"cache_hit_rate_run":0.9245958459350895,"token_status":"complete","cost_status":"reported","duration_status":"monotonic"},"task_seq":7,"config_generation":0,"background_mode":"background"}