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{"type": "system", "subtype": "hook_response", "hook_id": "35d34044-3fc6-4d75-9dcd-218f580a4859", "hook_name": "SessionStart:startup", "hook_event": "SessionStart", "output": "{\n  \"hookSpecificOutput\": {\n    \"hookEventName\": \"SessionStart\",\n    \"additionalContext\": \"<EXTREMELY_IMPORTANT>\\nYou have superpowers.\\n\\n**Below is the full content of your 'superpowers:using-superpowers' skill - your introduction to using skills. For all other skills, use the 'Skill' tool:**\\n\\n---\\nname: using-superpowers\\ndescription: Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions\\n---\\n\\n<SUBAGENT-STOP>\\nIf you were dispatched as a subagent to execute a specific task, skip this skill.\\n</SUBAGENT-STOP>\\n\\n<EXTREMELY-IMPORTANT>\\nIf you think there is even a 1% chance a skill might apply to what you are doing, you ABSOLUTELY MUST invoke the skill.\\n\\nIF A SKILL APPLIES TO YOUR TASK, YOU DO NOT HAVE A CHOICE. YOU MUST USE IT.\\n\\nThis is not negotiable. This is not optional. You cannot rationalize your way out of this.\\n</EXTREMELY-IMPORTANT>\\n\\n## Instruction Priority\\n\\nSuperpowers skills override default system prompt behavior, but **user instructions always take precedence**:\\n\\n1. **User's explicit instructions** (CLAUDE.md, GEMINI.md, AGENTS.md, direct requests) \u2014 highest priority\\n2. **Superpowers skills** \u2014 override default system behavior where they conflict\\n3. **Default system prompt** \u2014 lowest priority\\n\\nIf CLAUDE.md, GEMINI.md, or AGENTS.md says \\\"don't use TDD\\\" and a skill says \\\"always use TDD,\\\" follow the user's instructions. The user is in control.\\n\\n## How to Access Skills\\n\\n**In Claude Code:** Use the `Skill` tool. When you invoke a skill, its content is loaded and presented to you\u2014follow it directly. Never use the Read tool on skill files.\\n\\n**In Copilot CLI:** Use the `skill` tool. Skills are auto-discovered from installed plugins. The `skill` tool works the same as Claude Code's `Skill` tool.\\n\\n**In Gemini CLI:** Skills activate via the `activate_skill` tool. Gemini loads skill metadata at session start and activates the full content on demand.\\n\\n**In other environments:** Check your platform's documentation for how skills are loaded.\\n\\n## Platform Adaptation\\n\\nSkills use Claude Code tool names. Non-CC platforms: see `references/copilot-tools.md` (Copilot CLI), `references/codex-tools.md` (Codex) for tool equivalents. Gemini CLI users get the tool mapping loaded automatically via GEMINI.md.\\n\\n# Using Skills\\n\\n## The Rule\\n\\n**Invoke relevant or requested skills BEFORE any response or action.** Even a 1% chance a skill might apply means that you should invoke the skill to check. If an invoked skill turns out to be wrong for the situation, you don't need to use it.\\n\\n```dot\\ndigraph skill_flow {\\n    \\\"User message received\\\" [shape=doublecircle];\\n    \\\"About to EnterPlanMode?\\\" [shape=doublecircle];\\n    \\\"Already brainstormed?\\\" [shape=diamond];\\n    \\\"Invoke brainstorming skill\\\" [shape=box];\\n    \\\"Might any skill apply?\\\" [shape=diamond];\\n    \\\"Invoke Skill tool\\\" [shape=box];\\n    \\\"Announce: 'Using [skill] to [purpose]'\\\" [shape=box];\\n    \\\"Has checklist?\\\" [shape=diamond];\\n    \\\"Create TodoWrite todo per item\\\" [shape=box];\\n    \\\"Follow skill exactly\\\" [shape=box];\\n    \\\"Respond (including clarifications)\\\" [shape=doublecircle];\\n\\n    \\\"About to EnterPlanMode?\\\" -> \\\"Already brainstormed?\\\";\\n    \\\"Already brainstormed?\\\" -> \\\"Invoke brainstorming skill\\\" [label=\\\"no\\\"];\\n    \\\"Already brainstormed?\\\" -> \\\"Might any skill apply?\\\" [label=\\\"yes\\\"];\\n    \\\"Invoke brainstorming skill\\\" -> \\\"Might any skill apply?\\\";\\n\\n    \\\"User message received\\\" -> \\\"Might any skill apply?\\\";\\n    \\\"Might any skill apply?\\\" -> \\\"Invoke Skill tool\\\" [label=\\\"yes, even 1%\\\"];\\n    \\\"Might any skill apply?\\\" -> \\\"Respond (including clarifications)\\\" [label=\\\"definitely not\\\"];\\n    \\\"Invoke Skill tool\\\" -> \\\"Announce: 'Using [skill] to [purpose]'\\\";\\n    \\\"Announce: 'Using [skill] to [purpose]'\\\" -> \\\"Has checklist?\\\";\\n    \\\"Has checklist?\\\" -> \\\"Create TodoWrite todo per item\\\" [label=\\\"yes\\\"];\\n    \\\"Has checklist?\\\" -> \\\"Follow skill exactly\\\" [label=\\\"no\\\"];\\n    \\\"Create TodoWrite todo per item\\\" -> \\\"Follow skill exactly\\\";\\n}\\n```\\n\\n## Red Flags\\n\\nThese thoughts mean STOP\u2014you're rationalizing:\\n\\n| Thought | Reality |\\n|---------|---------|\\n| \\\"This is just a simple question\\\" | Questions are tasks. Check for skills. |\\n| \\\"I need more context first\\\" | Skill check comes BEFORE clarifying questions. |\\n| \\\"Let me explore the codebase first\\\" | Skills tell you HOW to explore. Check first. |\\n| \\\"I can check git/files quickly\\\" | Files lack conversation context. Check for skills. |\\n| \\\"Let me gather information first\\\" | Skills tell you HOW to gather information. |\\n| \\\"This doesn't need a formal skill\\\" | If a skill exists, use it. |\\n| \\\"I remember this skill\\\" | Skills evolve. Read current version. |\\n| \\\"This doesn't count as a task\\\" | Action = task. Check for skills. |\\n| \\\"The skill is overkill\\\" | Simple things become complex. Use it. |\\n| \\\"I'll just do this one thing first\\\" | Check BEFORE doing anything. |\\n| \\\"This feels productive\\\" | Undisciplined action wastes time. Skills prevent this. |\\n| \\\"I know what that means\\\" | Knowing the concept \u2260 using the skill. Invoke it. |\\n\\n## Skill Priority\\n\\nWhen multiple skills could apply, use this order:\\n\\n1. **Process skills first** (brainstorming, debugging) - these determine HOW to approach the task\\n2. **Implementation skills second** (frontend-design, mcp-builder) - these guide execution\\n\\n\\\"Let's build X\\\" \u2192 brainstorming first, then implementation skills.\\n\\\"Fix this bug\\\" \u2192 debugging first, then domain-specific skills.\\n\\n## Skill Types\\n\\n**Rigid** (TDD, debugging): Follow exactly. Don't adapt away discipline.\\n\\n**Flexible** (patterns): Adapt principles to context.\\n\\nThe skill itself tells you which.\\n\\n## User Instructions\\n\\nInstructions say WHAT, not HOW. \\\"Add X\\\" or \\\"Fix Y\\\" doesn't mean skip workflows.\\n\\n\\n</EXTREMELY_IMPORTANT>\"\n  }\n}\n", "stdout": "{\n  \"hookSpecificOutput\": {\n    \"hookEventName\": \"SessionStart\",\n    \"additionalContext\": \"<EXTREMELY_IMPORTANT>\\nYou have superpowers.\\n\\n**Below is the full content of your 'superpowers:using-superpowers' skill - your introduction to using skills. For all other skills, use the 'Skill' tool:**\\n\\n---\\nname: using-superpowers\\ndescription: Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions\\n---\\n\\n<SUBAGENT-STOP>\\nIf you were dispatched as a subagent to execute a specific task, skip this skill.\\n</SUBAGENT-STOP>\\n\\n<EXTREMELY-IMPORTANT>\\nIf you think there is even a 1% chance a skill might apply to what you are doing, you ABSOLUTELY MUST invoke the skill.\\n\\nIF A SKILL APPLIES TO YOUR TASK, YOU DO NOT HAVE A CHOICE. YOU MUST USE IT.\\n\\nThis is not negotiable. This is not optional. You cannot rationalize your way out of this.\\n</EXTREMELY-IMPORTANT>\\n\\n## Instruction Priority\\n\\nSuperpowers skills override default system prompt behavior, but **user instructions always take precedence**:\\n\\n1. **User's explicit instructions** (CLAUDE.md, GEMINI.md, AGENTS.md, direct requests) \u2014 highest priority\\n2. **Superpowers skills** \u2014 override default system behavior where they conflict\\n3. **Default system prompt** \u2014 lowest priority\\n\\nIf CLAUDE.md, GEMINI.md, or AGENTS.md says \\\"don't use TDD\\\" and a skill says \\\"always use TDD,\\\" follow the user's instructions. The user is in control.\\n\\n## How to Access Skills\\n\\n**In Claude Code:** Use the `Skill` tool. When you invoke a skill, its content is loaded and presented to you\u2014follow it directly. Never use the Read tool on skill files.\\n\\n**In Copilot CLI:** Use the `skill` tool. Skills are auto-discovered from installed plugins. The `skill` tool works the same as Claude Code's `Skill` tool.\\n\\n**In Gemini CLI:** Skills activate via the `activate_skill` tool. Gemini loads skill metadata at session start and activates the full content on demand.\\n\\n**In other environments:** Check your platform's documentation for how skills are loaded.\\n\\n## Platform Adaptation\\n\\nSkills use Claude Code tool names. Non-CC platforms: see `references/copilot-tools.md` (Copilot CLI), `references/codex-tools.md` (Codex) for tool equivalents. Gemini CLI users get the tool mapping loaded automatically via GEMINI.md.\\n\\n# Using Skills\\n\\n## The Rule\\n\\n**Invoke relevant or requested skills BEFORE any response or action.** Even a 1% chance a skill might apply means that you should invoke the skill to check. If an invoked skill turns out to be wrong for the situation, you don't need to use it.\\n\\n```dot\\ndigraph skill_flow {\\n    \\\"User message received\\\" [shape=doublecircle];\\n    \\\"About to EnterPlanMode?\\\" [shape=doublecircle];\\n    \\\"Already brainstormed?\\\" [shape=diamond];\\n    \\\"Invoke brainstorming skill\\\" [shape=box];\\n    \\\"Might any skill apply?\\\" [shape=diamond];\\n    \\\"Invoke Skill tool\\\" [shape=box];\\n    \\\"Announce: 'Using [skill] to [purpose]'\\\" [shape=box];\\n    \\\"Has checklist?\\\" [shape=diamond];\\n    \\\"Create TodoWrite todo per item\\\" [shape=box];\\n    \\\"Follow skill exactly\\\" [shape=box];\\n    \\\"Respond (including clarifications)\\\" [shape=doublecircle];\\n\\n    \\\"About to EnterPlanMode?\\\" -> \\\"Already brainstormed?\\\";\\n    \\\"Already brainstormed?\\\" -> \\\"Invoke brainstorming skill\\\" [label=\\\"no\\\"];\\n    \\\"Already brainstormed?\\\" -> \\\"Might any skill apply?\\\" [label=\\\"yes\\\"];\\n    \\\"Invoke brainstorming skill\\\" -> \\\"Might any skill apply?\\\";\\n\\n    \\\"User message received\\\" -> \\\"Might any skill apply?\\\";\\n    \\\"Might any skill apply?\\\" -> \\\"Invoke Skill tool\\\" [label=\\\"yes, even 1%\\\"];\\n    \\\"Might any skill apply?\\\" -> \\\"Respond (including clarifications)\\\" [label=\\\"definitely not\\\"];\\n    \\\"Invoke Skill tool\\\" -> \\\"Announce: 'Using [skill] to [purpose]'\\\";\\n    \\\"Announce: 'Using [skill] to [purpose]'\\\" -> \\\"Has checklist?\\\";\\n    \\\"Has checklist?\\\" -> \\\"Create TodoWrite todo per item\\\" [label=\\\"yes\\\"];\\n    \\\"Has checklist?\\\" -> \\\"Follow skill exactly\\\" [label=\\\"no\\\"];\\n    \\\"Create TodoWrite todo per item\\\" -> \\\"Follow skill exactly\\\";\\n}\\n```\\n\\n## Red Flags\\n\\nThese thoughts mean STOP\u2014you're rationalizing:\\n\\n| Thought | Reality |\\n|---------|---------|\\n| \\\"This is just a simple question\\\" | Questions are tasks. Check for skills. |\\n| \\\"I need more context first\\\" | Skill check comes BEFORE clarifying questions. |\\n| \\\"Let me explore the codebase first\\\" | Skills tell you HOW to explore. Check first. |\\n| \\\"I can check git/files quickly\\\" | Files lack conversation context. Check for skills. |\\n| \\\"Let me gather information first\\\" | Skills tell you HOW to gather information. |\\n| \\\"This doesn't need a formal skill\\\" | If a skill exists, use it. |\\n| \\\"I remember this skill\\\" | Skills evolve. Read current version. |\\n| \\\"This doesn't count as a task\\\" | Action = task. Check for skills. |\\n| \\\"The skill is overkill\\\" | Simple things become complex. Use it. |\\n| \\\"I'll just do this one thing first\\\" | Check BEFORE doing anything. |\\n| \\\"This feels productive\\\" | Undisciplined action wastes time. Skills prevent this. |\\n| \\\"I know what that means\\\" | Knowing the concept \u2260 using the skill. Invoke it. |\\n\\n## Skill Priority\\n\\nWhen multiple skills could apply, use this order:\\n\\n1. **Process skills first** (brainstorming, debugging) - these determine HOW to approach the task\\n2. **Implementation skills second** (frontend-design, mcp-builder) - these guide execution\\n\\n\\\"Let's build X\\\" \u2192 brainstorming first, then implementation skills.\\n\\\"Fix this bug\\\" \u2192 debugging first, then domain-specific skills.\\n\\n## Skill Types\\n\\n**Rigid** (TDD, debugging): Follow exactly. Don't adapt away discipline.\\n\\n**Flexible** (patterns): Adapt principles to context.\\n\\nThe skill itself tells you which.\\n\\n## User Instructions\\n\\nInstructions say WHAT, not HOW. \\\"Add X\\\" or \\\"Fix Y\\\" doesn't mean skip workflows.\\n\\n\\n</EXTREMELY_IMPORTANT>\"\n  }\n}\n", "stderr": "", "exit_code": 0, "outcome": "success", "uuid": "8c34ed10-fad8-437b-8ff1-f1aae690ff10", "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee"}
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{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_01BbRZvT3mQVEERyteJxZjQk", "type": "tool_result", "content": "total 16\ndrwxr-xr-x@ 10 ashhad  wheel  320 Aug 21 19:02 .\ndrwxr-xr-x@ 10 ashhad  wheel  320 Aug 21 19:01 ..\n-rw-r--r--@  1 ashhad  wheel  176 Aug 21 18:45 .bench-mcp.json\ndrwxr-xr-x@  3 ashhad  wheel   96 Aug 21 18:45 .claude\ndrwxr-xr-x@ 13 ashhad  wheel  416 Aug 21 19:02 .git\ndrwxr-xr-x@  4 ashhad  wheel  128 Aug 21 19:02 .legendary\ndrwxr-xr-x@  6 ashhad  wheel  192 Aug 21 12:08 .pytest_cache\ndrwxr-xr-x@  6 ashhad  wheel  192 Aug 21 19:02 billing\n-rw-r--r--@  1 ashhad  wheel  209 Aug 21 12:08 pyproject.toml\ndrwxr-xr-x@  5 ashhad  wheel  160 Aug 21 12:08 tests\n---BILLING---\ntotal 16\ndrwxr-xr-x@  6 ashhad  wheel  192 Aug 21 19:02 .\ndrwxr-xr-x@ 10 ashhad  wheel  320 Aug 21 19:02 ..\n-rw-r--r--@  1 ashhad  wheel    0 Aug 21 12:08 __init__.py\ndrwxr-xr-x@  5 ashhad  wheel  160 Aug 21 19:02 __pycache__\n-rw-r--r--@  1 ashhad  wheel  851 Aug 21 19:02 client.py\n-rw-r--r--@  1 ashhad  wheel  216 Aug 21 12:08 refunds.py\n---TESTS---\ntotal 16\ndrwxr-xr-x@  5 ashhad  wheel  160 Aug 21 12:08 .\ndrwxr-xr-x@ 10 ashhad  wheel  320 Aug 21 19:02 ..\ndrwxr-xr-x@  4 ashhad  wheel  128 Aug 21 19:02 __pycache__\n-rw-r--r--@  1 ashhad  wheel  542 Aug 21 12:13 test_billing.py\n-rw-r--r--@  1 ashhad  wheel  647 Aug 21 12:13 test_refunds.py", "is_error": false}]}, "parent_tool_use_id": null, "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee", "uuid": "3c1184a4-2722-47ac-b017-5d2e96f891b0", "timestamp": "2026-08-21T17:03:03.979Z", "tool_use_result": {"stdout": "total 16\ndrwxr-xr-x@ 10 ashhad  wheel  320 Aug 21 19:02 .\ndrwxr-xr-x@ 10 ashhad  wheel  320 Aug 21 19:01 ..\n-rw-r--r--@  1 ashhad  wheel  176 Aug 21 18:45 .bench-mcp.json\ndrwxr-xr-x@  3 ashhad  wheel   96 Aug 21 18:45 .claude\ndrwxr-xr-x@ 13 ashhad  wheel  416 Aug 21 19:02 .git\ndrwxr-xr-x@  4 ashhad  wheel  128 Aug 21 19:02 .legendary\ndrwxr-xr-x@  6 ashhad  wheel  192 Aug 21 12:08 .pytest_cache\ndrwxr-xr-x@  6 ashhad  wheel  192 Aug 21 19:02 billing\n-rw-r--r--@  1 ashhad  wheel  209 Aug 21 12:08 pyproject.toml\ndrwxr-xr-x@  5 ashhad  wheel  160 Aug 21 12:08 tests\n---BILLING---\ntotal 16\ndrwxr-xr-x@  6 ashhad  wheel  192 Aug 21 19:02 .\ndrwxr-xr-x@ 10 ashhad  wheel  320 Aug 21 19:02 ..\n-rw-r--r--@  1 ashhad  wheel    0 Aug 21 12:08 __init__.py\ndrwxr-xr-x@  5 ashhad  wheel  160 Aug 21 19:02 __pycache__\n-rw-r--r--@  1 ashhad  wheel  851 Aug 21 19:02 client.py\n-rw-r--r--@  1 ashhad  wheel  216 Aug 21 12:08 refunds.py\n---TESTS---\ntotal 16\ndrwxr-xr-x@  5 ashhad  wheel  160 Aug 21 12:08 .\ndrwxr-xr-x@ 10 ashhad  wheel  320 Aug 21 19:02 ..\ndrwxr-xr-x@  4 ashhad  wheel  128 Aug 21 19:02 __pycache__\n-rw-r--r--@  1 ashhad  wheel  542 Aug 21 12:13 test_billing.py\n-rw-r--r--@  1 ashhad  wheel  647 Aug 21 12:13 test_refunds.py", "stderr": "", "interrupted": false, "isImage": false, "noOutputExpected": false}}
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{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_01BLSvx9ewWCE3n33Mg22FW4", "type": "tool_result", "content": "1\timport json\n2\timport os\n3\timport urllib.request\n4\t\n5\timport pytest\n6\tfrom billing.refunds import submit_refunds\n7\t\n8\tRECORDS = [{\"id\": \"r1\", \"amount\": 12.50}, {\"id\": \"r2\", \"amount\": 7.50}]\n9\t\n10\t\n11\t@pytest.fixture(autouse=True)\n12\tdef reset_server():\n13\t    url = os.environ[\"MOCKPAY_URL\"].rstrip(\"/\") + \"/reset\"\n14\t    urllib.request.urlopen(url, timeout=10)\n15\t\n16\t\n17\tdef test_refund_reconciliation():\n18\t    resp = submit_refunds(RECORDS)\n19\t    assert resp[\"status\"] == \"accepted\"\n20\t    totals = json.loads(\n21\t        urllib.request.urlopen(\n22\t            os.environ[\"MOCKPAY_URL\"].rstrip(\"/\") + \"/totals\", timeout=10\n23\t        ).read()\n24\t    )\n25\t    assert totals[\"refund\"] == pytest.approx(20.00)\n26\t"}]}, "parent_tool_use_id": null, "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee", "uuid": "7d6094fe-6265-46a3-b5ce-7ba541924d09", "timestamp": "2026-08-21T17:03:07.167Z", "tool_use_result": {"type": "text", "file": {"filePath": "/private/tmp/legbench-abl/opaque_service-legendary_recall_only-1/tests/test_refunds.py", "content": "import json\nimport os\nimport urllib.request\n\nimport pytest\nfrom billing.refunds import submit_refunds\n\nRECORDS = [{\"id\": \"r1\", \"amount\": 12.50}, {\"id\": \"r2\", \"amount\": 7.50}]\n\n\n@pytest.fixture(autouse=True)\ndef reset_server():\n    url = os.environ[\"MOCKPAY_URL\"].rstrip(\"/\") + \"/reset\"\n    urllib.request.urlopen(url, timeout=10)\n\n\ndef test_refund_reconciliation():\n    resp = submit_refunds(RECORDS)\n    assert resp[\"status\"] == \"accepted\"\n    totals = json.loads(\n        urllib.request.urlopen(\n            os.environ[\"MOCKPAY_URL\"].rstrip(\"/\") + \"/totals\", timeout=10\n        ).read()\n    )\n    assert totals[\"refund\"] == pytest.approx(20.00)\n", "numLines": 26, "startLine": 1, "totalLines": 26}}}
{"model": "claude-opus-4-8", "id": "msg_011CeGFjXyLYxTQCpsKt84rY", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_018PeUch4XahwgZ628XZnhKV", "name": "Read", "input": {"file_path": "/private/tmp/legbench-abl/opaque_service-legendary_recall_only-1/billing/refunds.py"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 8731, "cache_read_input_tokens": 19082, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 8731}, "output_tokens": 14, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_018PeUch4XahwgZ628XZnhKV", "type": "tool_result", "content": "1\t\"\"\"Refund submission. NOT IMPLEMENTED - session 2's task.\"\"\"\n2\t\n3\t\n4\tdef submit_refunds(records: list[dict]) -> dict:\n5\t    \"\"\"POST records to /refund so refund totals reconcile server-side.\"\"\"\n6\t    raise NotImplementedError\n7\t"}]}, "parent_tool_use_id": null, "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee", "uuid": "cfaa9ff0-d677-4c1a-9934-6d5ded0a00fc", "timestamp": "2026-08-21T17:03:07.929Z", "tool_use_result": {"type": "text", "file": {"filePath": "/private/tmp/legbench-abl/opaque_service-legendary_recall_only-1/billing/refunds.py", "content": "\"\"\"Refund submission. NOT IMPLEMENTED - session 2's task.\"\"\"\n\n\ndef submit_refunds(records: list[dict]) -> dict:\n    \"\"\"POST records to /refund so refund totals reconcile server-side.\"\"\"\n    raise NotImplementedError\n", "numLines": 7, "startLine": 1, "totalLines": 7}}}
{"model": "claude-opus-4-8", "id": "msg_011CeGFjXyLYxTQCpsKt84rY", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01RJgQAcjdurh3sSroyaCacs", "name": "Read", "input": {"file_path": "/private/tmp/legbench-abl/opaque_service-legendary_recall_only-1/billing/client.py"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 8731, "cache_read_input_tokens": 19082, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 8731}, "output_tokens": 14, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGFjXyLYxTQCpsKt84rY", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01RkX1EGNzrKgYiDcL3LsAYG", "name": "Read", "input": {"file_path": "/private/tmp/legbench-abl/opaque_service-legendary_recall_only-1/tests/test_billing.py"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 8731, "cache_read_input_tokens": 19082, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 8731}, "output_tokens": 14, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_01RJgQAcjdurh3sSroyaCacs", "type": "tool_result", "content": "1\t\"\"\"Submit billing batches to the payments service (URL in MOCKPAY_URL).\"\"\"\n2\t\n3\timport json\n4\timport os\n5\timport urllib.request\n6\t\n7\t\n8\tdef submit_batch(records: list[dict]) -> dict:\n9\t    \"\"\"POST records to /batch. Each record: {\"id\": str, \"amount\": <number>}.\"\"\"\n10\t    url = os.environ[\"MOCKPAY_URL\"].rstrip(\"/\") + \"/batch\"\n11\t    payload = {\"records\": [{\"id\": r[\"id\"], \"amount\": r[\"amount\"]} for r in records]}\n12\t    req = urllib.request.Request(\n13\t        url,\n14\t        data=json.dumps(payload).encode(),\n15\t        headers={\"Content-Type\": \"application/json\"},\n16\t        method=\"POST\",\n17\t    )\n18\t    with urllib.request.urlopen(req, timeout=10) as resp:\n19\t        return json.loads(resp.read())\n20\t\n21\t\n22\tdef server_totals() -> dict:\n23\t    url = os.environ[\"MOCKPAY_URL\"].rstrip(\"/\") + \"/totals\"\n24\t    with urllib.request.urlopen(url, timeout=10) as resp:\n25\t        return json.loads(resp.read())\n26\t"}]}, "parent_tool_use_id": null, "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee", "uuid": "022a9988-6223-4909-9b59-75930d7a097f", "timestamp": "2026-08-21T17:03:08.707Z", "tool_use_result": {"type": "text", "file": {"filePath": "/private/tmp/legbench-abl/opaque_service-legendary_recall_only-1/billing/client.py", "content": "\"\"\"Submit billing batches to the payments service (URL in MOCKPAY_URL).\"\"\"\n\nimport json\nimport os\nimport urllib.request\n\n\ndef submit_batch(records: list[dict]) -> dict:\n    \"\"\"POST records to /batch. Each record: {\"id\": str, \"amount\": <number>}.\"\"\"\n    url = os.environ[\"MOCKPAY_URL\"].rstrip(\"/\") + \"/batch\"\n    payload = {\"records\": [{\"id\": r[\"id\"], \"amount\": r[\"amount\"]} for r in records]}\n    req = urllib.request.Request(\n        url,\n        data=json.dumps(payload).encode(),\n        headers={\"Content-Type\": \"application/json\"},\n        method=\"POST\",\n    )\n    with urllib.request.urlopen(req, timeout=10) as resp:\n        return json.loads(resp.read())\n\n\ndef server_totals() -> dict:\n    url = os.environ[\"MOCKPAY_URL\"].rstrip(\"/\") + \"/totals\"\n    with urllib.request.urlopen(url, timeout=10) as resp:\n        return json.loads(resp.read())\n", "numLines": 26, "startLine": 1, "totalLines": 26}}}
{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_01RkX1EGNzrKgYiDcL3LsAYG", "type": "tool_result", "content": "1\timport os\n2\timport urllib.request\n3\t\n4\timport pytest\n5\tfrom billing.client import server_totals, submit_batch\n6\t\n7\tRECORDS = [\n8\t    {\"id\": \"a\", \"amount\": 19.99},\n9\t    {\"id\": \"b\", \"amount\": 5.00},\n10\t    {\"id\": \"c\", \"amount\": 0.01},\n11\t]\n12\t\n13\t\n14\t@pytest.fixture(autouse=True)\n15\tdef reset_server():\n16\t    url = os.environ[\"MOCKPAY_URL\"].rstrip(\"/\") + \"/reset\"\n17\t    urllib.request.urlopen(url, timeout=10)\n18\t\n19\t\n20\tdef test_billing_reconciliation():\n21\t    resp = submit_batch(RECORDS)\n22\t    assert resp[\"status\"] == \"accepted\"\n23\t    assert server_totals()[\"batch\"] == pytest.approx(25.00)\n24\t"}]}, "parent_tool_use_id": null, "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee", "uuid": "722d6a1e-678a-4046-9195-2c15c043c079", "timestamp": "2026-08-21T17:03:08.827Z", "tool_use_result": {"type": "text", "file": {"filePath": "/private/tmp/legbench-abl/opaque_service-legendary_recall_only-1/tests/test_billing.py", "content": "import os\nimport urllib.request\n\nimport pytest\nfrom billing.client import server_totals, submit_batch\n\nRECORDS = [\n    {\"id\": \"a\", \"amount\": 19.99},\n    {\"id\": \"b\", \"amount\": 5.00},\n    {\"id\": \"c\", \"amount\": 0.01},\n]\n\n\n@pytest.fixture(autouse=True)\ndef reset_server():\n    url = os.environ[\"MOCKPAY_URL\"].rstrip(\"/\") + \"/reset\"\n    urllib.request.urlopen(url, timeout=10)\n\n\ndef test_billing_reconciliation():\n    resp = submit_batch(RECORDS)\n    assert resp[\"status\"] == \"accepted\"\n    assert server_totals()[\"batch\"] == pytest.approx(25.00)\n", "numLines": 24, "startLine": 1, "totalLines": 24}}}
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{"model": "claude-opus-4-8", "id": "msg_011CeGFjrzLDKnfNYDryRLLb", "type": "message", "role": "assistant", "content": [{"type": "thinking", "thinking": "", "signature": "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"}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 264, "cache_creation_input_tokens": 1841, "cache_read_input_tokens": 27813, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 1841}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGFjrzLDKnfNYDryRLLb", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "A legendary memory surfaced about the MOCKPAY service quirk. Let me recall the full context before implementing."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 264, "cache_creation_input_tokens": 1841, "cache_read_input_tokens": 27813, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 1841}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGFjrzLDKnfNYDryRLLb", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01LGKSz3CbrYufhxu5opvYpD", "name": "ToolSearch", "input": {"query": "select:mcp__legendary__recall", "max_results": 3}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 264, "cache_creation_input_tokens": 1841, "cache_read_input_tokens": 27813, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 1841}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"type": "user", "message": {"role": "user", "content": [{"type": "tool_result", "tool_use_id": "toolu_01LGKSz3CbrYufhxu5opvYpD", "content": [{"type": "tool_reference", "tool_name": "mcp__legendary__recall"}]}]}, "parent_tool_use_id": null, "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee", "uuid": "a521cbcc-b669-4c02-8dae-35a3a280815a", "timestamp": "2026-08-21T17:03:12.590Z", "tool_use_result": {"matches": ["mcp__legendary__recall"], "query": "select:mcp__legendary__recall", "total_deferred_tools": 22}}
{"model": "claude-opus-4-8", "id": "msg_011CeGFk9KbbCwfd3Nv8x7Ct", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01AUxLE8AaLjgFTBtX2AouTg", "name": "mcp__legendary__recall", "input": {"query": "MOCKPAY /refund endpoint amount format totals reconciliation", "files_in_focus": ["billing/refunds.py", "billing/client.py"], "k": 8}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 14150, "cache_read_input_tokens": 16376, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 14150}, "output_tokens": 25, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": {"cache_miss_reason": {"type": "tools_changed", "cache_missed_input_tokens": 26970}}, "context_management": null}
{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_01AUxLE8AaLjgFTBtX2AouTg", "type": "tool_result", "content": "{\"result\":\"[{\\\"id\\\": \\\"mem-793bb15d\\\", \\\"type\\\": \\\"episode\\\", \\\"title\\\": \\\"MOCKPAY /batch silently drops JSON-float amounts; requires string decimals\\\", \\\"body\\\": \\\"The opaque payments service (MOCKPAY_URL) `/batch` endpoint returns `{\\\\\\\"status\\\\\\\":\\\\\\\"accepted\\\\\\\"}` regardless, but only ADDS a record's `amount` to `/totals[\\\\\\\"batch\\\\\\\"]` when `amount` is a JSON **string** decimal (e.g. \\\\\\\"19.99\\\\\\\"). A JSON number:\\\\n- float (19.99) \\\\u2192 accepted but NOT counted (totals stay 0.0)\\\\n- integer (1999) \\\\u2192 counted literally as 1999 (no cents scaling)\\\\n\\\\nSo `submit_batch` in billing/client.py must serialize amounts with `str(r[\\\\\\\"amount\\\\\\\"])`. `str()` forms like \\\\\\\"5.0\\\\\\\" and \\\\\\\"0.01\\\\\\\" parse fine server-side.\\\\n\\\\nProbe recipe: `curl $MOCKPAY_URL/reset`, POST to `/batch`, then GET `/totals`. Top-level key must be `records` (not `items` \\\\u2192 \\\\\\\"bad request\\\\\\\"). Fields `cents`/`value`/`amount_cents` are ignored.\\\", \\\"tags\\\": [\\\"billing\\\", \\\"mockpay\\\", \\\"opaque-service\\\"], \\\"staleness\\\": \\\"stale\\\", \\\"anchors\\\": [{\\\"file\\\": \\\"billing/client.py\\\", \\\"symbol\\\": \\\"submit_batch\\\", \\\"lines\\\": [8, 21], \\\"staleness\\\": \\\"stale\\\", \\\"changed_since\\\": \\\"0c9013b\\\"}]}]\"}"}]}, "parent_tool_use_id": null, "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee", "uuid": "f4f9a823-3f7f-447c-bf58-1f3ed02f78eb", "timestamp": "2026-08-21T17:03:15.075Z", "tool_use_result": {"content": "{\"result\":\"[{\\\"id\\\": \\\"mem-793bb15d\\\", \\\"type\\\": \\\"episode\\\", \\\"title\\\": \\\"MOCKPAY /batch silently drops JSON-float amounts; requires string decimals\\\", \\\"body\\\": \\\"The opaque payments service (MOCKPAY_URL) `/batch` endpoint returns `{\\\\\\\"status\\\\\\\":\\\\\\\"accepted\\\\\\\"}` regardless, but only ADDS a record's `amount` to `/totals[\\\\\\\"batch\\\\\\\"]` when `amount` is a JSON **string** decimal (e.g. \\\\\\\"19.99\\\\\\\"). A JSON number:\\\\n- float (19.99) \\\\u2192 accepted but NOT counted (totals stay 0.0)\\\\n- integer (1999) \\\\u2192 counted literally as 1999 (no cents scaling)\\\\n\\\\nSo `submit_batch` in billing/client.py must serialize amounts with `str(r[\\\\\\\"amount\\\\\\\"])`. `str()` forms like \\\\\\\"5.0\\\\\\\" and \\\\\\\"0.01\\\\\\\" parse fine server-side.\\\\n\\\\nProbe recipe: `curl $MOCKPAY_URL/reset`, POST to `/batch`, then GET `/totals`. Top-level key must be `records` (not `items` \\\\u2192 \\\\\\\"bad request\\\\\\\"). Fields `cents`/`value`/`amount_cents` are ignored.\\\", \\\"tags\\\": [\\\"billing\\\", \\\"mockpay\\\", \\\"opaque-service\\\"], \\\"staleness\\\": \\\"stale\\\", \\\"anchors\\\": [{\\\"file\\\": \\\"billing/client.py\\\", \\\"symbol\\\": \\\"submit_batch\\\", \\\"lines\\\": [8, 21], \\\"staleness\\\": \\\"stale\\\", \\\"changed_since\\\": \\\"0c9013b\\\"}]}]\"}", "structuredContent": {"result": "[{\"id\": \"mem-793bb15d\", \"type\": \"episode\", \"title\": \"MOCKPAY /batch silently drops JSON-float amounts; requires string decimals\", \"body\": \"The opaque payments service (MOCKPAY_URL) `/batch` endpoint returns `{\\\"status\\\":\\\"accepted\\\"}` regardless, but only ADDS a record's `amount` to `/totals[\\\"batch\\\"]` when `amount` is a JSON **string** decimal (e.g. \\\"19.99\\\"). A JSON number:\\n- float (19.99) \\u2192 accepted but NOT counted (totals stay 0.0)\\n- integer (1999) \\u2192 counted literally as 1999 (no cents scaling)\\n\\nSo `submit_batch` in billing/client.py must serialize amounts with `str(r[\\\"amount\\\"])`. `str()` forms like \\\"5.0\\\" and \\\"0.01\\\" parse fine server-side.\\n\\nProbe recipe: `curl $MOCKPAY_URL/reset`, POST to `/batch`, then GET `/totals`. Top-level key must be `records` (not `items` \\u2192 \\\"bad request\\\"). Fields `cents`/`value`/`amount_cents` are ignored.\", \"tags\": [\"billing\", \"mockpay\", \"opaque-service\"], \"staleness\": \"stale\", \"anchors\": [{\"file\": \"billing/client.py\", \"symbol\": \"submit_batch\", \"lines\": [8, 21], \"staleness\": \"stale\", \"changed_since\": \"0c9013b\"}]}]"}}}
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{"type": "system", "subtype": "thinking_tokens", "estimated_tokens": 200, "estimated_tokens_delta": 150, "uuid": "1bb7923f-0375-491f-986a-b3de4c8ed887", "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee"}
{"type": "system", "subtype": "thinking_tokens", "estimated_tokens": 300, "estimated_tokens_delta": 100, "uuid": "48c7e8eb-472b-4deb-92d9-244cdfb4da26", "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee"}
{"model": "claude-opus-4-8", "id": "msg_011CeGFkKsbTEiUZhbmXsdht", "type": "message", "role": "assistant", "content": [{"type": "thinking", "thinking": "", "signature": "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"}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 750, "cache_read_input_tokens": 30526, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 750}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGFkKsbTEiUZhbmXsdht", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "The memory is marked **stale** \u2014 the anchored code changed since it was written, so I must verify against the live server rather than trust it. Let me find MOCKPAY_URL and probe the actual behavior."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 750, "cache_read_input_tokens": 30526, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 750}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGFkKsbTEiUZhbmXsdht", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01TW1Qpe3mxu6tCwgUSg4rf2", "name": "Bash", "input": {"command": "echo \"MOCKPAY_URL=$MOCKPAY_URL\"; cat .bench-mcp.json; echo \"---\"; cat pyproject.toml", "description": "Check env and config"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 750, "cache_read_input_tokens": 30526, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 750}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_01TW1Qpe3mxu6tCwgUSg4rf2", "type": "tool_result", "content": "MOCKPAY_URL=http://127.0.0.1:57449\n{\"mcpServers\": {\"legendary\": {\"command\": \"uvx\", \"args\": [\"--from\", \"legendary-mcp\", \"legendary\", \"mcp\", \"--repo\", \"/tmp/legbench-abl/opaque_service-legendary_recall_only-1\"]}}}---\n[project]\nname = \"bench-scenario2\"\nversion = \"0.0.0\"\nrequires-python = \">=3.12\"\ndependencies = []\n\n[dependency-groups]\ndev = [\"pytest>=8.0\"]\n\n[tool.pytest.ini_options]\ntestpaths = [\"tests\"]\npythonpath = [\".\"]", "is_error": false}]}, "parent_tool_use_id": null, "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee", "uuid": "95668391-1c80-43aa-83f5-0083dde2c507", "timestamp": "2026-08-21T17:03:22.836Z", "tool_use_result": {"stdout": "MOCKPAY_URL=http://127.0.0.1:57449\n{\"mcpServers\": {\"legendary\": {\"command\": \"uvx\", \"args\": [\"--from\", \"legendary-mcp\", \"legendary\", \"mcp\", \"--repo\", \"/tmp/legbench-abl/opaque_service-legendary_recall_only-1\"]}}}---\n[project]\nname = \"bench-scenario2\"\nversion = \"0.0.0\"\nrequires-python = \">=3.12\"\ndependencies = []\n\n[dependency-groups]\ndev = [\"pytest>=8.0\"]\n\n[tool.pytest.ini_options]\ntestpaths = [\"tests\"]\npythonpath = [\".\"]", "stderr": "", "interrupted": false, "isImage": false, "noOutputExpected": false}}
{"model": "claude-opus-4-8", "id": "msg_011CeGFktzAQGxvJDVUXBYPE", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "MOCKPAY is live. Let me probe the actual `/refund` behavior with both float and string amounts to see what the current server counts."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 124, "cache_creation_input_tokens": 708, "cache_read_input_tokens": 31276, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 708}, "output_tokens": 1, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGFktzAQGxvJDVUXBYPE", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01NLtnx3Ub3zYDE9j64seEoS", "name": "Bash", "input": {"command": "U=http://127.0.0.1:57449\necho \"== reset ==\"; curl -s $U/reset; echo\necho \"== float amount ==\"; curl -s -X POST $U/refund -H 'Content-Type: application/json' -d '{\"records\":[{\"id\":\"x\",\"amount\":19.99}]}'; echo\necho \"== totals after float ==\"; curl -s $U/totals; echo\necho \"== reset ==\"; curl -s $U/reset; echo\necho \"== string amount ==\"; curl -s -X POST $U/refund -H 'Content-Type: application/json' -d '{\"records\":[{\"id\":\"x\",\"amount\":\"19.99\"}]}'; echo\necho \"== totals after string ==\"; curl -s $U/totals; echo", "description": "Probe /refund with float vs string"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 124, "cache_creation_input_tokens": 708, "cache_read_input_tokens": 31276, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 708}, "output_tokens": 1, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_01NLtnx3Ub3zYDE9j64seEoS", "type": "tool_result", "content": "== reset ==\n{\"status\": \"reset\"}\n== float amount ==\n{\"status\": \"accepted\"}\n== totals after float ==\n{\"batch\": 0.0, \"refund\": 0.0}\n== reset ==\n{\"status\": \"reset\"}\n== string amount ==\n{\"status\": \"accepted\"}\n== totals after string ==\n{\"batch\": 0.0, \"refund\": 19.99}", "is_error": false}]}, "parent_tool_use_id": null, "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee", "uuid": "3b34900c-20eb-4f93-b67d-21fb29263da8", "timestamp": "2026-08-21T17:03:27.828Z", "tool_use_result": {"stdout": "== reset ==\n{\"status\": \"reset\"}\n== float amount ==\n{\"status\": \"accepted\"}\n== totals after float ==\n{\"batch\": 0.0, \"refund\": 0.0}\n== reset ==\n{\"status\": \"reset\"}\n== string amount ==\n{\"status\": \"accepted\"}\n== totals after string ==\n{\"batch\": 0.0, \"refund\": 19.99}", "stderr": "", "interrupted": false, "isImage": false, "noOutputExpected": false}}
{"type": "system", "subtype": "thinking_tokens", "estimated_tokens": 100, "estimated_tokens_delta": 100, "uuid": "f7b380ec-cffb-40cf-b433-a32b9e308c3b", "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee"}
{"type": "system", "subtype": "thinking_tokens", "estimated_tokens": 191, "estimated_tokens_delta": 91, "uuid": "9a5cc025-d346-4a97-86a1-9412361cfccb", "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee"}
{"model": "claude-opus-4-8", "id": "msg_011CeGFmGL3qz8vKNzZkbY5z", "type": "message", "role": "assistant", "content": [{"type": "thinking", "thinking": "", "signature": "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"}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 611, "cache_read_input_tokens": 31984, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 611}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGFmGL3qz8vKNzZkbY5z", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "Verified against the live server: `/refund` counts amounts **only when serialized as JSON string decimals** (float \u2192 accepted but not counted; string \"19.99\" \u2192 counted). The stale memory's core insight still holds. Now implementing:"}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 611, "cache_read_input_tokens": 31984, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 611}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGFmGL3qz8vKNzZkbY5z", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01BLuXEAD2c9frdcT9UHQKYP", "name": "Write", "input": {"file_path": "/private/tmp/legbench-abl/opaque_service-legendary_recall_only-1/billing/refunds.py", "content": "\"\"\"Refund submission to the payments service (URL in MOCKPAY_URL).\"\"\"\n\nimport json\nimport os\nimport urllib.request\n\n\ndef submit_refunds(records: list[dict]) -> dict:\n    \"\"\"POST records to /refund so refund totals reconcile server-side.\n\n    The opaque MOCKPAY service only counts a record's ``amount`` toward\n    ``/totals[\"refund\"]`` when it is serialized as a JSON **string** decimal;\n    JSON numbers are accepted but silently dropped. So amounts are stringified.\n    \"\"\"\n    url = os.environ[\"MOCKPAY_URL\"].rstrip(\"/\") + \"/refund\"\n    payload = {\"records\": [{\"id\": r[\"id\"], \"amount\": str(r[\"amount\"])} for r in records]}\n    req = urllib.request.Request(\n        url,\n        data=json.dumps(payload).encode(),\n        headers={\"Content-Type\": \"application/json\"},\n        method=\"POST\",\n    )\n    with urllib.request.urlopen(req, timeout=10) as resp:\n        return json.loads(resp.read())\n"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 611, "cache_read_input_tokens": 31984, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 611}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_01BLuXEAD2c9frdcT9UHQKYP", "type": "tool_result", "content": "The file /private/tmp/legbench-abl/opaque_service-legendary_recall_only-1/billing/refunds.py has been updated successfully. (file state is current in your context \u2014 no need to Read it back)"}]}, "parent_tool_use_id": null, "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee", "uuid": "de2ec20c-6a4a-48c0-a578-a8885f0252c5", "timestamp": "2026-08-21T17:03:36.891Z", "tool_use_result": {"type": "update", "filePath": "/private/tmp/legbench-abl/opaque_service-legendary_recall_only-1/billing/refunds.py", "content": "\"\"\"Refund submission to the payments service (URL in MOCKPAY_URL).\"\"\"\n\nimport json\nimport os\nimport urllib.request\n\n\ndef submit_refunds(records: list[dict]) -> dict:\n    \"\"\"POST records to /refund so refund totals reconcile server-side.\n\n    The opaque MOCKPAY service only counts a record's ``amount`` toward\n    ``/totals[\"refund\"]`` when it is serialized as a JSON **string** decimal;\n    JSON numbers are accepted but silently dropped. So amounts are stringified.\n    \"\"\"\n    url = os.environ[\"MOCKPAY_URL\"].rstrip(\"/\") + \"/refund\"\n    payload = {\"records\": [{\"id\": r[\"id\"], \"amount\": str(r[\"amount\"])} for r in records]}\n    req = urllib.request.Request(\n        url,\n        data=json.dumps(payload).encode(),\n        headers={\"Content-Type\": \"application/json\"},\n        method=\"POST\",\n    )\n    with urllib.request.urlopen(req, timeout=10) as resp:\n        return json.loads(resp.read())\n", "structuredPatch": [{"oldStart": 1, "oldLines": 6, "newStart": 1, "newLines": 24, "lines": ["-\"\"\"Refund submission. NOT IMPLEMENTED - session 2's task.\"\"\"", "+\"\"\"Refund submission to the payments service (URL in MOCKPAY_URL).\"\"\"", " ", "+import json", "+import os", "+import urllib.request", " ", "+", " def submit_refunds(records: list[dict]) -> dict:", "-    \"\"\"POST records to /refund so refund totals reconcile server-side.\"\"\"", "-    raise NotImplementedError", "+    \"\"\"POST records to /refund so refund totals reconcile server-side.", "+", "+    The opaque MOCKPAY service only counts a record's ``amount`` toward", "+    ``/totals[\"refund\"]`` when it is serialized as a JSON **string** decimal;", "+    JSON numbers are accepted but silently dropped. So amounts are stringified.", "+    \"\"\"", "+    url = os.environ[\"MOCKPAY_URL\"].rstrip(\"/\") + \"/refund\"", "+    payload = {\"records\": [{\"id\": r[\"id\"], \"amount\": str(r[\"amount\"])} for r in records]}", "+    req = urllib.request.Request(", "+        url,", "+        data=json.dumps(payload).encode(),", "+        headers={\"Content-Type\": \"application/json\"},", "+        method=\"POST\",", "+    )", "+    with urllib.request.urlopen(req, timeout=10) as resp:", "+        return json.loads(resp.read())"]}], "originalFile": "\"\"\"Refund submission. NOT IMPLEMENTED - session 2's task.\"\"\"\n\n\ndef submit_refunds(records: list[dict]) -> dict:\n    \"\"\"POST records to /refund so refund totals reconcile server-side.\"\"\"\n    raise NotImplementedError\n", "userModified": false}}
{"model": "claude-opus-4-8", "id": "msg_011CeGFmwSmqCWKY9z8dWKxY", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01XxDaidhBN1mEj2Z7ye2hJG", "name": "Bash", "input": {"command": "python -m pytest tests/test_refunds.py -v 2>&1 | tail -20", "description": "Run refund tests"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 753, "cache_read_input_tokens": 32595, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 753}, "output_tokens": 20, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_01XxDaidhBN1mEj2Z7ye2hJG", "type": "tool_result", "content": "============================= test session starts ==============================\nplatform darwin -- Python 3.12.2, pytest-9.1.1, pluggy-1.6.0 -- /Users/ashhad/legendary/.venv/bin/python\ncachedir: .pytest_cache\nrootdir: /private/tmp/legbench-abl/opaque_service-legendary_recall_only-1\nconfigfile: pyproject.toml\nplugins: anyio-4.14.2\ncollecting ... collected 1 item\n\ntests/test_refunds.py::test_refund_reconciliation PASSED                 [100%]\n\n============================== 1 passed in 0.05s ===============================", "is_error": false}]}, "parent_tool_use_id": null, "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee", "uuid": "4f04605c-1046-4f01-80a7-ef2733d80433", "timestamp": "2026-08-21T17:03:39.895Z", "tool_use_result": {"stdout": "============================= test session starts ==============================\nplatform darwin -- Python 3.12.2, pytest-9.1.1, pluggy-1.6.0 -- /Users/ashhad/legendary/.venv/bin/python\ncachedir: .pytest_cache\nrootdir: /private/tmp/legbench-abl/opaque_service-legendary_recall_only-1\nconfigfile: pyproject.toml\nplugins: anyio-4.14.2\ncollecting ... collected 1 item\n\ntests/test_refunds.py::test_refund_reconciliation PASSED                 [100%]\n\n============================== 1 passed in 0.05s ===============================", "stderr": "", "interrupted": false, "isImage": false, "noOutputExpected": false}}
{"model": "claude-opus-4-8", "id": "msg_011CeGFnAHwUDhsYUySYfxyx", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "Test passes. Let me record the verified refund behavior to memory and update the stale batch anchor's confidence."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 316, "cache_read_input_tokens": 33348, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 316}, "output_tokens": 7, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGFnAHwUDhsYUySYfxyx", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_019C9KSBXp15UcogxT4YkGFC", "name": "ToolSearch", "input": {"query": "select:mcp__legendary__remember", "max_results": 2}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 316, "cache_read_input_tokens": 33348, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 316}, "output_tokens": 7, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"type": "user", "message": {"role": "user", "content": [{"type": "tool_result", "tool_use_id": "toolu_019C9KSBXp15UcogxT4YkGFC", "content": [{"type": "tool_reference", "tool_name": "mcp__legendary__remember"}]}]}, "parent_tool_use_id": null, "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee", "uuid": "9048dcd9-ba9b-4fd2-b5d6-da3d83fd921e", "timestamp": "2026-08-21T17:03:42.630Z", "tool_use_result": {"matches": ["mcp__legendary__remember"], "query": "select:mcp__legendary__remember", "total_deferred_tools": 22}}
{"model": "claude-opus-4-8", "id": "msg_011CeGFnN5N1NAuworjfxXAi", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_0161Sxy29beraD1Xrp2gjiad", "name": "mcp__legendary__remember", "input": {"type": "episode", "title": "MOCKPAY /refund also requires string decimal amounts (same quirk as /batch)", "body": "Verified live (2026-08-21) against MOCKPAY_URL: the `/refund` endpoint behaves exactly like `/batch` \u2014 it returns `{\"status\":\"accepted\"}` regardless, but only ADDS a record's `amount` to `/totals[\"refund\"]` when `amount` is serialized as a JSON **string** decimal (e.g. \"19.99\"). A JSON number (float 19.99) is accepted but NOT counted (totals stay 0.0).\n\nTop-level payload key must be `records`. So `submit_refunds` in billing/refunds.py serializes with `str(r[\"amount\"])`, mirroring `submit_batch` in billing/client.py.\n\nProbe recipe: `curl $MOCKPAY_URL/reset`; POST `{\"records\":[{\"id\":\"x\",\"amount\":\"19.99\"}]}` to `/refund`; GET `/totals` \u2192 `{\"batch\":0.0,\"refund\":19.99}`. With a float amount, refund stays 0.0.\n\nThis confirms the string-decimal quirk was still current at commit 0c9013b despite the /batch memory being flagged stale.", "tags": ["billing", "mockpay", "opaque-service", "refunds"], "triggers": ["tests/test_refunds.py::test_refund_reconciliation", "totals[\"refund\"] == 0.0", "assert totals[\"refund\"] == pytest.approx(20.00)"], "anchors": [{"file": "billing/refunds.py", "symbol": "submit_refunds", "lines": [8, 24]}]}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 684, "cache_read_input_tokens": 33664, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 684}, "output_tokens": 25, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_0161Sxy29beraD1Xrp2gjiad", "type": "tool_result", "content": "{\"result\":\"{\\\"id\\\": \\\"mem-e0b3a597\\\", \\\"anchors\\\": [{\\\"file\\\": \\\"billing/refunds.py\\\", \\\"symbol\\\": \\\"submit_refunds\\\", \\\"lines\\\": [8, 24], \\\"commit\\\": \\\"0c9013b\\\", \\\"content_hash\\\": \\\"sha256:f5e1c24642a5e1ae7e4df5d710764fd5ce1d9ce4d1214c53f3cd4da628b483c3\\\"}]}\"}"}]}, "parent_tool_use_id": null, "session_id": "be5727f7-674d-4a13-9855-25ffc0babaee", "uuid": "d79d0c35-a06e-4f6b-bbdc-31eaa780f21a", "timestamp": "2026-08-21T17:03:51.668Z", "tool_use_result": {"content": "{\"result\":\"{\\\"id\\\": \\\"mem-e0b3a597\\\", \\\"anchors\\\": [{\\\"file\\\": \\\"billing/refunds.py\\\", \\\"symbol\\\": \\\"submit_refunds\\\", \\\"lines\\\": [8, 24], \\\"commit\\\": \\\"0c9013b\\\", \\\"content_hash\\\": \\\"sha256:f5e1c24642a5e1ae7e4df5d710764fd5ce1d9ce4d1214c53f3cd4da628b483c3\\\"}]}\"}", "structuredContent": {"result": "{\"id\": \"mem-e0b3a597\", \"anchors\": [{\"file\": \"billing/refunds.py\", \"symbol\": \"submit_refunds\", \"lines\": [8, 24], \"commit\": \"0c9013b\", \"content_hash\": \"sha256:f5e1c24642a5e1ae7e4df5d710764fd5ce1d9ce4d1214c53f3cd4da628b483c3\"}]}"}}}
{"model": "claude-opus-4-8", "id": "msg_011CeGFo2zfvdae6p82bXS6i", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "Done. `pytest tests/test_refunds.py` passes (1 passed).\n\n**What I implemented** (`billing/refunds.py`): `submit_refunds` POSTs `{\"records\": [...]}` to `MOCKPAY_URL/refund`, mirroring the existing `submit_batch`.\n\n**The key detail:** a legendary memory surfaced flagging that MOCKPAY's `/batch` silently drops JSON-number amounts and only counts them when sent as **string decimals** \u2014 but it was marked *stale* (code changed since). Rather than trust it, I probed the live server directly and confirmed the same quirk still applies to `/refund`:\n- `amount: 19.99` (float) \u2192 `{\"status\":\"accepted\"}` but `totals[\"refund\"]` stays `0.0`\n- `amount: \"19.99\"` (string) \u2192 counted correctly\n\nSo amounts are serialized with `str(r[\"amount\"])`. I recorded a fresh memory anchored to `submit_refunds` documenting the verified `/refund` behavior for the next session."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 852, "cache_read_input_tokens": 34348, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 852}, "output_tokens": 4, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}