{"task_id":"st_01a0577c","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":"2026-08-31T11:02:48.890Z","updated_at":"2026-09-01T16:35:13.994Z","notification":{"run_epoch":1,"notified_epoch":1},"name":"st_01a0577c","task_summary":"Map existing unknown-answer and handoff seams","description":"unknown-handoff-architecture","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":"Inspect the NutriCoach onboarding code in /home/cube/projects/richard/.worktrees/nutricoach-v150-combined for existing mechanisms that can support: (1) formal customer 'I don't know' answers by field type, (2) persistent invalid-answer attempt counters, (3) after two failures an operator handoff without activation, and (4) later customer correction. Do not edit. Return exact files/functions/tests and the smallest architecture-consistent design, including safety risks and observable test seams. Stop when the implementation map is decision-complete.","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.py - core onboarding state machine; `submit_answer`, `rewind_collection`, `record_reconciliation`, `replace_stale_reconciliation`, `revise_reconciliation_answer`, `attest_baseline`\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/checkin_cli/nutrition_onboarding_copy.py - field-type parsing and error copy; `parse_answer`, `answer_error`, `card`\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/checkin_cli/nutrition_onboarding_clarification_policy.py - canonical \"unknown/ambiguous\" classification; `canonicalize_answer`, `_valid_structured`, `_type_reasons`, `compile_clarification_policy`\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/checkin_cli/nutrition_onboarding_reconciliation.py - persisted clarification/correction record; `build_reconciliation`, `recompute_reconciliation`, `require_resolved_reconciliation`\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/checkin_cli/nutrition_onboarding_session.py - durable session load/save surface; `build_status`, `load_mutable_session`, `save_session`\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/gateway/platforms/telegram_nutrition_onboarding_runtime_collection.py - live invalid-answer handling; `_handle_text_locked`\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/gateway/platforms/telegram_nutrition_onboarding_runtime_publication.py - operator/customer publication routing; `_publish`, `_operator_attention_payload`, `recover_operator_status`\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/gateway/platforms/telegram_nutrition_onboarding_runtime_callback.py - correction/handoff callbacks; `_handle_callback_locked`\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/gateway/platforms/telegram_nutrition_onboarding_runtime_publication_transport.py - durable send/uncertain recovery; `_send_publication`, `_mark_unknown`, `publication_generation`\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/gateway/platforms/telegram_nutrition_onboarding_operator_ack.py - persistent operator acknowledgement store; `GatewayOperatorAttentionStore.acknowledge`\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/gateway/platforms/telegram_nutrition_onboarding_operator_recovery.py - gated operator-recovery capability loader; `load_operator_notification_recovery`\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/tests/test_nutrition_onboarding_clarification_policy.py - best existing seams for ambiguous/invalid/correctable answers\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/tests/test_nutrition_onboarding.py - end-to-end onboarding/revision/safety-hold seams\n- /home/cube/projects/richard/.worktrees/nutricoach-v150-combined/dualcoach/profile/tests/test_nutrition_onboarding_store.py - analogous durable uncertainty semantics (`UNCERTAIN`) for transport, not answer validation\n</files>\n\n<answer>\nWhat exists today:\n- Formal field-type \"I don't know\"/unknown handling already exists in parsing:\n  - structured fields map to `{\"status\":\"none\",\"items\":[]}` via `parse_answer`\n  - booleans support `확실하지 않음` -> `None`\n  - `target_weight_kg` / `target_date` accept none-like inputs\n  - `equation_sex_basis` has a decline path, but `submit_answer` rejects decline in `customer_v2`\n- Customer correction already exists, but only after reconciliation/attestation:\n  - `revise_reconciliation_answer` reopens one field and recomputes the reconciliation digest\n  - `rewind_collection` reopens earlier questions and drops later answers\n- Operator handoff without activation already exists as a publication/state pattern:\n  - `owner_review` and `safety_hold` are non-ready states\n  - publication carries `operator_attention_identity` / `operator_delivery_epoch`\n  - `GatewayOperatorAttentionStore` persists acknowledgements\n  - `recover_operator_status` can republish owner-facing cards durably\n\nWhat is missing:\n- No persistent invalid-answer attempt counter exists in the onboarding domain/session model.\n- No automatic \"after two failures, hand off to operator\" transition exists.\n- The text path currently just replies with `answer_error(...)` and returns; it does not persist failure counts.\n\nSmallest architecture-consistent design:\n1. Add a per-session/per-field attempt counter in the onboarding session JSON and expose it on `OnboardingStatus`.\n2. Increment it in the same locked path that currently rejects invalid text (`_handle_text_locked` / `submit_answer`).\n3. On first failure: keep current behavior, no state change.\n4. On second failure: transition into an existing non-activation operator-facing state (`owner_review` is the cleanest fit; `safety_hold` is reserved for clinical risk).\n5. Reuse the existing publication pipeline so the operator card is durably receipted and recoverable.\n6. Let later customer correction reuse the existing correction seam:\n   - if still in clarification flow, `revise_reconciliation_answer`\n   - if the operator rewinds the questionnaire, `rewind_collection`\n\nSafety risks:\n- Do not overload `safety_hold` for ordinary invalid input; it is already reserved for clinical clearance and owner-risk flows.\n- Keep counters durable and monotonic; replay/duplicate updates must not double-count.\n- Preserve digest binding; otherwise stale corrections will silently mutate the wrong answer.\n- Keep operator handoff publication gated by current authority/receipt, or recovery will desync.\n\nObservable test seams:\n- Unit-level parser seams: `parse_answer`, `answer_error`, `compile_clarification_policy`\n- State-machine seam: `NutritionOnboardingService.submit_answer`\n- Correction seam: `revise_reconciliation_answer`, `rewind_collection`\n- Gateway seam: `_handle_text_locked`, `_publish`, `_handle_callback_locked`\n- Durability seam: `load_mutable_session` / `save_session`, plus `GatewayOperatorAttentionStore`\n- Existing tests to extend:\n  - `test_mixed_ambiguity_and_invalid_value_compile_complete_ordered_issue_set`\n  - `test_noncanonical_equation_basis_keeps_clarification_and_requires_enum_resolution`\n  - `test_reconciliation_revision_is_digest_bound_and_customer_authorized`\n  - `test_customer_v2_group_submission_is_atomic_restartable_and_rewindable`\n  - `test_safety_hold_requires_scoped_owner_clinical_clearance`\n\nDecision-complete read:\n- Existing code already covers field-type unknown answers and later correction.\n- It does not yet persist invalid-attempt counts or auto-handoff after two failures.\n- The cleanest integration point is the existing collection handler plus the owner-review/safety-hold publication path, not a new parallel workflow.\n</answer>\n\n<next_steps>\nImplement the counter in the session document and wire the second-failure transition through the existing gateway publication path; add regression tests at the parser, service, and runtime seams above.\n</next_steps>\n</results>","run_stats":{"runtime_ms":236494,"turns":25,"tool_calls":74,"output_tokens":14400,"input_tokens":150708,"cache_read_tokens":1615360,"total_tokens":1780468,"generation_ms":221715,"tokens_per_second":65,"cost_usd":0.298983,"cache_hit_rate_last":0.9916654593147833,"cache_hit_rate_run":0.9146646674986467,"token_status":"complete","cost_status":"reported","duration_status":"monotonic"},"task_seq":16,"config_generation":0,"background_mode":"background"}