{"task_id":"st_01a00a91","status":"completed","residency_state":"evicted","parent_session_id":"01a00387-aaf8-7f2f-89e3-e24c1af24859","root_session_id":"01a00387-aaf8-7f2f-89e3-e24c1af24859","depth":1,"execution_mode":"in-process","model":"clinepass/cline-pass/deepseek-v4-flash","notify_on_terminal":true,"created_at":"2026-08-16T12:34:54.944Z","updated_at":"2026-08-18T15:58:04.455Z","notification":{"run_epoch":0,"notified_epoch":0},"name":"summary-copy-logic","task_summary":"Trace summary formatter and structured value leakage","description":"Trace summary formatter and structured value leakage","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-5.4-mini","display":"openai-codex/gpt-5.4-mini","source":"agent","reasoning_effort":"medium"},{"provider":"openai-codex","model_id":"gpt-5.6-luna","display":"openai-codex/gpt-5.6-luna","source":"agent","reasoning_effort":"high"}],"resolved_model":{"provider":"clinepass","model_id":"cline-pass/deepseek-v4-flash","display":"clinepass/cline-pass/deepseek-v4-flash","source":"agent","reasoning_effort":"low","reasoning":"low"},"spawn_spec":{"version":1,"cwd":"/home/cube/projects/richard/traning coach","prompt":"Read-only investigation in /home/cube/projects/richard/hermes-agent. Hypothesis H1: the customer summary formatter stringifies StructuredItems/raw dicts and uses truthiness/default logic that produces `{'items': [], 'status': 'none'}`, `목표: 미입력`, activity text plus `. 미입력`, and a false health-warning on none-valued safety fields. Trace the exact runtime path that generated the screenshot card after clarification. Return file:line causal chain, exact input values, formatter outputs, and minimal test seam. Do not modify files, live profile, service, network, Telegram, provider, Git, or evidence.","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":4082105,"final_response":"I have the full causal chain. Here is the complete findings report.\n\n<analysis>\n**Literal Request**: Trace the exact runtime path that produced a screenshot card after a clarification, proving H1: the customer-summary formatter stringifies raw dicts/StructuredItems and misuses field names and truthiness, yielding `{'items': [], 'status': 'none'}`, `목표: 미입력`, activity text + `· 미입력`, and a false safety-health warning.\n\n**Actual Need**: A file:line causal chain from collected answers → clarification → re-publication → rendered card, exact input dict, exact formatter output strings, and the smallest unit-test seam so the bug can be fixed and regression-tested.\n\n**Success Looks Like**: Precise call chain with line numbers, the raw `answers` dict fed in, the four rendered output strings, and one pure-function seam (`render_authoritative_customer_summary`) that currently has zero direct tests.\n</analysis>\n\n<results>\n<files>\n- /home/cube/projects/richard/hermes-agent/gateway/platforms/nutrition_onboarding_reconciliation.py - The buggy formatter `render_authoritative_customer_summary` (lines 59-107). Root of all four symptoms.\n- /home/cube/projects/richard/hermes-agent/gateway/platforms/telegram_nutrition_onboarding_runtime_publication.py - Runtime publish path that calls the formatter after clarification (line 128) and wraps it via `render_reconciliation_text` (line 139).\n- /home/cube/projects/richard/hermes-agent/gateway/platforms/telegram_nutrition_onboarding_runtime_collection.py - Ingress handler for a clarification reply; calls `service.revise_reconciliation_answer` then `_publish`, re-issuing the card (lines 162-210).\n- /home/cube/.hermes/profiles/dualcoachtest/workspace/checkin_cli/checkin_cli/nutrition_onboarding.py - Service: `reconciliation_answers` (line 414, returns `answers`), `revise_reconciliation_answer` (line 529, advances reconciliation after a clarification), `submit_answer`/`attest_baseline`.\n- /home/cube/.hermes/profiles/dualcoachtest/workspace/checkin_cli/checkin_cli/nutrition_onboarding_reconciliation.py - `build_reconciliation` (line 84, sets `current_index=0`, state `clarifying`/`resolved`) and `advance_reconciliation` (line 106, bumps `current_index`, sets `resolved` when all clarifications answered).\n- /home/cube/.hermes/profiles/dualcoachtest/workspace/checkin_cli/checkin_cli/nutrition_onboarding_contract.py - Canonical field names (`QUESTION_FIELDS`, line 19) and `example_answer` (line 66) showing structured fields are `{\"status\": \"none\", \"items\": []}` dicts and belief fields are bools.\n- /home/cube/.hermes/profiles/dualcoachtest/workspace/checkin_cli/checkin_cli/nutrition_onboarding_models.py - `StructuredItems`/`StructuredItemStatus` (lines 70, 90-121) proving structured values are dict-like objects serialized to `{\"status\": \"none\", \"items\": []}`.\n- /home/cube/projects/richard/hermes-agent/gateway/platforms/telegram_nutrition_onboarding_copy.py - `card()` (line ~52) and `PROMPTS`; the card base text and the `_publish` heading repurposed into the summary card.\n- /home/cube/projects/richard/hermes-agent/gateway/platforms/nutrition_onboarding_reconciliation_copy.py - `render_clarification_text` (line 9), the pre-clarification card body.\n- /home/cube/projects/richard/hermes-agent/tests/gateway/test_nutrition_onboarding_reconciliation.py - Existing reconciliation tests (line 207 renders `render_reconciliation_text`), confirming `render_authoritative_customer_summary` itself is never test-covered — the seam.\n</files>\n\n<answer>\nH1 is confirmed. The formatter's bugs are a field-name mismatch against the canonical contract plus `str()` on structured dicts.\n\n**Exact runtime path (after clarification)**\n1. Customer fills onboarding; collected answers stored raw in the session document (`nutrition_onboarding.py:157 submit_answer`). Structured fields are stored as their JSON form `{\"status\": \"none\", \"items\": []}`; belief fields as bools (see `contract.py:66 example_answer`).\n2. On `customer_attestation`, `_publish` calls `service.reconciliation_answers()` (`publication.py:71-72`, def `nutrition_onboarding.py:414`) -> deepcopy of `document[\"answers\"]`, raw JSON dicts. LLM reconciliation yields clarifications; record created with `current_index=0`, state `clarifying` (`reconciliation.py:84 build_reconciliation`).\n3. Each clarification reply is routed by `runtime_collection.py:162-176` (`clarification_field` in the publication payload, set at `publication.py:166`) to `service.revise_reconciliation_answer` (`nutrition_onboarding.py:529`), which stores the revised answer and calls `advance_reconciliation` (`nutrition_onboarding_reconciliation.py:106`), incrementing `current_index`. It re-publishes afterward (`runtime_collection.py:210`).\n4. After the last clarification, `advance_reconciliation` sets `state=\"resolved\"` and `current_index = N` (> 0). The re-published `customer_attestation` then hits the `else` branch: `if current_index:` is truthy, so `summary_ko = render_authoritative_customer_summary(answers)` (`publication.py:116,126-129`). `render_reconciliation_text` wraps that string into the card body (`publication.py:138-141`, join at `nutrition_onboarding_reconciliation.py:34-58`). This is exactly the \"card after clarification.\"\n\n**Exact inputs** (example answers dict, confirmed by `contract.py:66` and `models.py`):\n- `goal_type=\"maintain\"` (no `goal` key)\n- `activity_category=\"moderate\"`, `activity_rationale=\"주 3회 근력 운동\"` (no `training_details` key)\n- `allergies` / `intolerances` / `dietary_preferences` / `religious_ethical_exclusions` / `conditions` / `medications` = `{\"status\": \"none\", \"items\": []}`\n- `pregnancy_breastfeeding=False`, `eating_disorder_risk=False`\n- `meal_count=3`, `cooking_access=\"기본 조리 가능\"`, `budget_band=\"보통\"`, `schedule_constraints=\"없음\"`\n\n**Why each symptom happens** (`nutrition_onboarding_reconciliation.py`)\n- `value()` (lines 62-68) only short-circuits on `None`/`\"\"`/`[]`; it never checks `{}` and falls to `str(raw)` (line 68). Non-empty dicts `{\"status\":\"none\",\"items\":[]}` stringify to `\"{'status': 'none', 'items': []}\"`. This literal appears in the restriction line (and would appear in any stringified structured field).\n- `- 목표: {value('goal')}` (line 93) reads `goal`, but the contract field is `goal_type` -> `answers.get('goal')` is `None` -> `미입력`. (No `goal` key exists anywhere.)\n- `- 활동: {value('activity_category')} · {value('training_details')}` (lines 94-97): `activity_category` renders \"moderate\", but `training_details` does not exist (the real field is `activity_rationale`) -> `미입력` -> `활동: moderate · 미입력`.\n- False health warning (lines 70-80): `health_fields` uses `medical_conditions` and `pregnancy_lactation` (real fields: `conditions`, `pregnancy_breastfeeding`) so those read `None`; but `medications` is the dict string `\"{'status': 'none', 'items': []}\"` and `eating_disorder_risk` is bool `False` -> `str(False)=\"False\"`. Neither is in `{\"없음\",\"해당 없음\",\"아니요\"}` -> `any(...)` is True -> `검토할 입력이 있습니다.` even though nothing meaningful was provided.\n- Restriction line (lines 82-90) uses `religious_restrictions` (real: `religious_ethical_exclusions`), so 3 of 4 fields stringify as dicts: `... · ... · ... · 없음` when the customer simply reported none.\n\n**Exact formatter output** (what appeared in the card's summary block):\n```\n- 목표: 미입력\n- 활동: moderate · 미입력\n- 식사: 하루 3끼\n- 조리·예산: 기본 조리 가능 · 보통\n- 식사 시간: 없음\n- 알레르기·불내증·식품 제한: {'status': 'none', 'items': []} · {'status': 'none', 'items': []} · {'status': 'none', 'items': []} · 없음\n- 건강 관련 입력: 검토할 입력이 있습니다.\n```\n(Dict repr key order is whatever was parsed from JSON; the H1 `{'items': [], 'status': 'none'}` matches this stringified dict.)\n\n**Minimal test seam**\n`render_authoritative_customer_summary` (pure function, `nutrition_onboarding_reconciliation.py:59`) is imported by `_publish` and `runtime_collection` but has zero direct tests — it is not in any import list in `tests/gateway/test_nutrition_onboarding_reconciliation.py` (lines 17-27). Add a focused unit test there that calls it with a canonical `answers` dict (all 22 contract keys, structured fields as `{\"status\": \"none\", \"items\": []}`, goal as `goal_type`, activity rationale as `activity_rationale`) and asserts both the current (buggy) output and the corrected output (goal rendered, no `· 미입력` via `activity_rationale`, empty restriction set, `별도 검토 입력이 없습니다.`). This isolates all four bugs without touching the service or Telegram path.\n\n**Root causes (fix direction, not applied):** (a) formatter field names must match `QUESTION_FIELDS`: `goal`→`goal_type`, `training_details`→`activity_rationale`, `medical_conditions`→`conditions`, `pregnancy_lactation`→`pregnancy_breastfeeding`, `religious_restrictions`→`religious_ethical_exclusions`; (b) `value()` must treat empty/`NONE`-status dicts as absent instead of `str()`-ing them; (c) health review must interpret `StructuredItems(status=\"none\")` and bool `False` as \"no review needed.\"\n</answer>\n\n<next_steps>\n- Add the seam test for `render_authoritative_customer_summary` in /home/cube/projects/richard/hermes-agent/tests/gateway/test_nutrition_onboarding_reconciliation.py before changing behavior, so the false-positive output is pinned first.\n- Then align the formatter's field names with `QUESTION_FIELDS` (`contract.py:19`) and add an \"is empty/none\" predicate for structured dicts and `False`.\n- Optionally add one `_publish` integration assert (mirroring `tests/gateway/test_telegram_nutrition_onboarding.py:1330-1370`) with a resolved record `current_index=1` to confirm the card text no longer contains `미입력` or the dict repr.\n- Ready to proceed — the causal chain and inputs are fully pinned; no further discovery needed.\n</next_steps>\n</results>\n\nRead-only investigation complete. No files, services, network, or evidence were modified.","run_stats":{"runtime_ms":421426,"turns":22,"tool_calls":47,"output_tokens":16369,"total_tokens":826094,"generation_ms":284458,"tokens_per_second":58,"cost_usd":0,"cache_hit_rate_last":0.9944364200502862,"cache_hit_rate_run":0.9307172188088548}}