{"task_id":"st_01a02bf0","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":"openai-codex/gpt-5.6-sol","notify_on_terminal":true,"created_at":"2026-08-23T00:05:09.256Z","updated_at":"2026-08-25T03:40:28.131Z","notification":{"run_epoch":0,"notified_epoch":0},"name":"feature-epoch-hypothesis","task_summary":"Compare live feature epoch inputs with Golden Path fixtures","description":"Trace feature epoch mismatch","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":"Investigate hypothesis H2 read-only: live feature_epoch/capability material differs from Golden Path and causes finalization rejection. Worktree: /home/cube/projects/richard/.worktrees/nutricoach-v111-impl. Live profile: /home/cube/.hermes/profiles/dualcoachtest. Find feature_epoch_digest implementation, all files it reads, exact live values, and corresponding Golden Path fixture values. Do not edit, run git, or mutate live state. Return confirmed/refuted verdict with exact paths/values and reachable exception site. Stop once the hypothesis is decisively classified.\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":1082531,"final_response":"I read this as a read-only H2 classification - I traced live and Golden Path epoch/capability inputs through the rejection path.\n\n## Verdict: H2 refuted\n\n### Feature epoch\n\nImplementation:\n\n- `/home/cube/projects/richard/.worktrees/nutricoach-v111-impl/gateway/platforms/telegram_nutrition_onboarding_authority.py:32`\n- Installed live copy is byte-identical, SHA-256:\n  `7a670aea26f55e23760308e34848aef7acfdd7e53fc9d2ebd73b43878456a4d2`\n\nIt reads only:\n\n`<profile>/data/customers/<customer_key>/nutrition-plans/feature-epoch.json`\n\nLive path:\n\n`/home/cube/.hermes/profiles/dualcoachtest/data/customers/pilot_20260820_01/nutrition-plans/feature-epoch.json`\n\nThis path and its parent `nutrition-plans/` are absent. Therefore the implementation hashes the canonical fallback:\n\n```json\n{\"activation\":false,\"analytics_shadow\":false,\"delivery\":false,\"epoch\":0,\"operator_candidates\":false}\n```\n\nResult:\n\n`2092cad6375cbbf617b88668a3103ad7fb07d854c20bdefa1b3b074b0ee135ac`\n\nGolden Path fixture creation at:\n\n`/home/cube/projects/richard/.worktrees/nutricoach-v111-impl/scripts/dualcoach_v111_disposable_fixture.py`\n\nalso creates no `disposable_001/nutrition-plans/feature-epoch.json`. It therefore produces the identical fallback digest:\n\n`2092cad6375cbbf617b88668a3103ad7fb07d854c20bdefa1b3b074b0ee135ac`\n\n### Capability material\n\nLive candidate is consistently:\n\n`9dcf52724fcc8fb9abc7d3789d765e1ec7cf54d5573ca6e1cb38be5d1f41a189`\n\nConfirmed in:\n\n- `/home/cube/.hermes/profiles/dualcoachtest/config.yaml:684`\n- `/home/cube/.hermes/profiles/dualcoachtest/preexecution-product-binding.json`\n- `/run/user/1000/credentials/hermes-gateway-dualcoachtest.service/owner-risk-acceptance.json`\n- `/home/cube/.hermes/profiles/dualcoachtest/data/customers/pilot_20260820_01/nutrition-onboarding/transient/workflow.json`\n\nThe credential SHA is exactly the configured value:\n\n`e501ba143fc22e978cae0ee99faddd43a8b5809ca714533b31d0ef4fd63b456a`\n\nIts authorization seal is valid:\n\n`9a69836b29be20eabb1ddb831aa97c693a0a053207552b11367daf8d51126fec`\n\nThe persisted owner-risk receipt is internally valid:\n\n- acceptance identity stored/computed:\n  `3998f193eb90b8342435d57ad2cb700906058b55916c053691b7dce4bfe2795f`\n- receipt digest stored/computed:\n  `4700c0dfc7f85b04a25d7f3f713b7749bc80eb004bf68998ba1e8977136963ed`\n\nGolden Path candidate:\n\n`66a770590a50bcbdb30ecdb646e1a795e0c828fea756577034e2ad57323c0410`\n\nfrom:\n\n- `.omo/evidence/v1.2.0-operator-notification-hotfix/golden-path-canonical/candidate-binding.json`\n- `.omo/evidence/v1.2.0-operator-notification-hotfix/capability-receipt.json`\n\nThat per-candidate difference is expected. Golden Path does not provide an owner-risk capability fixture, and finalization does not compare the live candidate epoch against Golden Path. It only validates that the persisted epoch is lowercase 64-hex and that the receipt’s binding and digest are internally consistent; live passes those checks.\n\n### Reachable rejection path\n\nOwner approval reaches:\n\n1. `telegram_nutrition_onboarding_runtime_callback.py:528`\n2. `telegram_nutrition_onboarding_runtime.py:270-281`\n3. `nutrition_onboarding_finalization.py`\n\nA finalization `ValueError` is caught at:\n\n`gateway/platforms/telegram_nutrition_onboarding_runtime_callback.py:544-548`\n\nand reported as `transition_rejected`.\n\nThe downstream generic exception site is:\n\n`dualcoach/profile/checkin_cli/nutrition_onboarding_finalization.py:292`\n\n```python\nraise ValueError(f\"readiness finalization failed: {','.join(audit.reason_codes)}\")\n```\n\nNeither feature epoch nor candidate capability is part of that readiness audit. The feature digest is only format-checked and written into the receipt. Thus the live/Golden capability difference cannot cause this finalization rejection. No files were modified and no Git commands were run.","run_stats":{"runtime_ms":233138,"turns":17,"tool_calls":70,"output_tokens":9662,"total_tokens":1648669,"generation_ms":193817,"tokens_per_second":50,"cost_usd":1.743391,"cache_hit_rate_last":0.9841252823831221,"cache_hit_rate_run":0.91403636470131}}