# Conversation — agent-acompact-d80c4d91b1126d65.jsonl L33
**When:** 2026-03-15T01:23:55.494Z
{
"model": "claude-sonnet-4-6",
"id": "msg_01GuCcoBWCnmrSQFmgnHPjcN",
"type": "message",
"role": "assistant",
"content": [
{
"type": "tool_use",
"id": "toolu_01Bg7mUF4dkUNigCBqTXHKBr",
"name": "Bash",
"input": {
"command": "python3 -c \"\nimport json, sys\nsys.stdout.reconfigure(encoding='utf-8')\n\nwith open(r'C:\\Users\\Praxillax\\Documents\\apps\\Anothen\\Gemini-Leora\\session-2026-03-01T11-03-3ce72f8a.json', 'r', encoding='utf-8') as f:\n data = json.load(f)\nmsgs = data.get('messages', [])\n\n# Find ALL occurrences of the formula or Y(M_L) notation across all messages\n# Print surrounding context to determine if derived or given\nfor i, msg in enumerate(msgs):\n role = msg.get('type', '?')\n content = msg.get('content', '')\n if isinstance(content, list):\n text = ' '.join(p.get('text','') for p in content if isinstance(p, dict))\n else:\n text = str(content)\n if 'Y(M_L)' in text or 'Y(M_' in text:\n idx = text.find('Y(M_')\n start = max(0, idx-400)\n end = min(len(text), idx+600)\n print(f'--- MSG {i} ({role}) ---')\n print(text[start:end])\n print()\n\"\n",
"description": "Find every occurrence of Y(M_L) in the 2026-03-01 session with context"
},
"caller": {
"type": "direct"
}
}
],
"stop_reason": "tool_use",
"stop_sequence": null,
"usage": {
"input_tokens": 1,
"cache_creation_input_tokens": 1977,
"cache_read_input_tokens": 48946,
"output_tokens": 551,
"server_tool_use": {
"web_search_requests": 0,
"web_fetch_requests": 0
},
"service_tier": "standard",
"cache_creation": {
"ephemeral_1h_input_tokens": 1977,
"ephemeral_5m_input_tokens": 0
},
"inference_geo": "",
"iterations": [],
"speed": "standard"
}
}
---
## Canonical spine (M_L)
**PRIMUS:** Willful avoidance of harm of self and others equally.
**SECUNDUS:** Willful seeking of healing of self and others equally.
**TERTIUM:** Willful pursuit of benefit of self and others equally.
Love is the sole logic that produces mutual prosperity without a zero-sum trade.
- Full paper: `MASTER DOCS/PAPER/Another_Paper_Draft_v1.md`
- OSF preregistration: https://osf.io/qa54c
- Corpus phase: extract v0.1 (mined from local Braid archive)