{"task_id":"st_019fd78d","status":"cancelled","residency_state":"disposed","parent_session_id":"019fd78b-bc20-7f7e-baca-b4bb0dc6b301","root_session_id":"019fd78b-bc20-7f7e-baca-b4bb0dc6b301","depth":1,"execution_mode":"in-process","model":"openai-codex/gpt-5.6-terra","notify_on_terminal":true,"created_at":"2026-08-06T14:50:11.388Z","updated_at":"2026-08-06T14:53:21.605Z","notification":{"run_epoch":0,"notified_epoch":-1},"name":"dualcoach-manifest-executor","task_summary":"Dirty worktree 전체를 분류하고 immutable candidate manifest 생성","category":"unspecified-high","requested_model":{"provider":"openai-codex","model_id":"gpt-5.6-terra","display":"openai-codex/gpt-5.6-terra","source":"category","variant":"max","reasoning_effort":"xhigh"},"fallback_models":[{"provider":"openai-codex","model_id":"gpt-5.6-sol","display":"openai-codex/gpt-5.6-sol","source":"category","variant":"max","reasoning_effort":"xhigh"}],"resolved_model":{"provider":"openai-codex","model_id":"gpt-5.6-terra","display":"GPT-5.6 Terra","source":"category","variant":"max","reasoning_effort":"xhigh"},"spawn_spec":{"version":1,"cwd":"/home/cube/projects/richard/traning coach","prompt":"You are the executor for plan task `1. Build the immutable-candidate manifest`.\n\nGoal and scope:\n- Execution repository (READ-ONLY for this task): `/home/cube/projects/richard/hermes-agent`.\n- Evidence repository (the only place you may edit): `/home/cube/projects/richard/traning coach`.\n- Read the plan at `/home/cube/projects/richard/traning coach/.omo/plans/dualcoach-production-readiness.md`, Foundation Specification 1 and Todo 1.\n- Read `/home/cube/projects/richard/hermes-agent/AGENTS.md` and obey it.\n- Create exactly these retained artifacts using apply_patch for all writes: `.omo/evidence/dualcoach-candidate-manifest.md` and `.omo/evidence/dualcoach-candidate-manifest.json` under the evidence repository.\n- Do not edit any product/test file. Do not run commit, push, reset, stash, clean, checkout, restore, or any destructive Git operation.\n\nRequired behavior:\n1. Capture a single coherent `git status --porcelain=v1 --untracked-files=all` snapshot and base HEAD for the execution repository.\n2. Inventory every tracked and untracked DualCoach-related file in the current dirty worktree, including all primary input glob families from Specification 1. Also include every status entry, classifying it as product implementation, automated test, migration/configuration, diagnostic-only instrumentation, temporary recovery code, or unrelated change. Record path, exact Git status, classification, owner (`DualCoach candidate`, `unrelated user/agent change`, or `needs release decision`), and concrete reason.\n3. Explicitly list diagnostic/recovery files that must be removed before release review; do not remove them now.\n4. Build a machine-readable JSON artifact containing schema version, captured timestamp, repo path, base HEAD, status counts, entries, DualCoach candidate path list, removal list, and candidate digest.\n5. Candidate digest must be deterministic over the manifest's sorted candidate path records and the exact bytes of each existing listed file (content digest, not a commit). State the precise digest algorithm/canonicalization so an independent verifier can recompute it. Do not include volatile timestamps in digest input.\n6. Reconcile total entry/status counts exactly against the captured porcelain snapshot. Every untracked DualCoach implementation/test file must appear as candidate or needs-release-decision, never omitted.\n\nTesting and evidence:\n- This is a documentation/data task, so no behavior-changing failing test is required. Still establish a baseline by recording HEAD and status count before artifact creation.\n- Validate JSON parsing and schema fields with an exact local command.\n- Run a deterministic recomputation script/command and show the computed digest equals the stored digest.\n- Compare manifest counts to a fresh status snapshot. If the worktree changes during inventory, detect it and retry from a new coherent snapshot rather than claiming success.\n- Manual QA channel: use a small Python driver that parses the JSON, checks every current porcelain path is represented exactly once, verifies every candidate file exists, recomputes the digest, and prints a binary `PASS` or exits nonzero. Include the literal invocation and output in your DoneClaim.\n\nAdversarial probes:\n- dirty_worktree: prove unrelated entries are classified and untouched.\n- stale_state: prove the ending status snapshot hash/count matches the captured snapshot used by the artifact.\n- misleading_success_output: independent recomputation must verify stored counts and digest, not trust generator stdout.\n- Mark the other six ultraqa classes not applicable with one-line reasons.\n\nCleanup:\n- Remove any temporary scripts/files you created. Retain only the two declared evidence artifacts. Report a cleanup receipt (paths checked and no temp resources/processes).\n\nReturn a strict DoneClaim object with task, changed_files, tests (exact command + result), manual_qa (artifact and exact invocation), cleanup, risks, baseline, status_snapshot_hash, candidate_digest, and status counts. Stop only when all acceptance criteria pass.\n\n<Category_Context>\nYou are working on tasks that don't fit specific categories but require substantial effort.\n\n<Selection_Gate>\nBEFORE selecting this category, VERIFY ALL conditions:\n1. Task does NOT fit: quick (trivial), visual-engineering (UI), ultrabrain (deep logic), artistry (creative), writing (docs)\n2. Task requires substantial effort across multiple systems/modules\n3. Changes have broad impact or require careful coordination\n4. NOT just \"complex\" - must be genuinely unclassifiable AND high-effort\n\nIf task fits ANY other category, DO NOT select unspecified-high.\nIf task is unclassifiable but moderate-effort, use unspecified-low instead.\n</Selection_Gate>\n</Category_Context>"},"host_pid":489237,"error_message":"No required artifacts were created after prolonged serial reconnaissance and an explicit finish-now steer; replacing with a bounded executor.","run_stats":{"runtime_ms":190204,"turns":4,"tool_calls":17,"output_tokens":7638,"total_tokens":209976,"generation_ms":149480,"tokens_per_second":51,"cost_usd":0.3267576,"cache_hit_rate_last":0.61051959514018,"cache_hit_rate_run":0.46559716909329935}}