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{"type": "system", "subtype": "hook_response", "hook_id": "0b436c2f-85cc-4eea-ab2f-5738de4f0cb6", "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": "b68a36f8-4ee4-4c63-a590-2039e2d95724", "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814"}
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{"model": "claude-opus-4-8", "id": "msg_011CeGJWErvtuGHZGeao4vma", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "I'll start by loading the debugging skill, then investigate the failure."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 7577, "cache_creation_input_tokens": 2825, "cache_read_input_tokens": 16283, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 2825}, "output_tokens": 7, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
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{"type": "user", "message": {"role": "user", "content": [{"type": "tool_result", "tool_use_id": "toolu_01GnT7T6Cgz6ocaYFvnNrRnW", "content": "Launching skill: superpowers:systematic-debugging"}]}, "parent_tool_use_id": null, "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814", "uuid": "74dde6ae-e13b-42f2-a840-6e79820ffe2c", "timestamp": "2026-08-21T17:39:28.038Z", "tool_use_result": {"success": true, "commandName": "superpowers:systematic-debugging"}}
{"type": "user", "message": {"role": "user", "content": [{"type": "text", "text": "Base directory for this skill: /Users/ashhad/.claude/plugins/cache/superpowers-dev/superpowers/5.1.0/skills/systematic-debugging\n\n# Systematic Debugging\n\n## Overview\n\nRandom fixes waste time and create new bugs. Quick patches mask underlying issues.\n\n**Core principle:** ALWAYS find root cause before attempting fixes. Symptom fixes are failure.\n\n**Violating the letter of this process is violating the spirit of debugging.**\n\n## The Iron Law\n\n```\nNO FIXES WITHOUT ROOT CAUSE INVESTIGATION FIRST\n```\n\nIf you haven't completed Phase 1, you cannot propose fixes.\n\n## When to Use\n\nUse for ANY technical issue:\n- Test failures\n- Bugs in production\n- Unexpected behavior\n- Performance problems\n- Build failures\n- Integration issues\n\n**Use this ESPECIALLY when:**\n- Under time pressure (emergencies make guessing tempting)\n- \"Just one quick fix\" seems obvious\n- You've already tried multiple fixes\n- Previous fix didn't work\n- You don't fully understand the issue\n\n**Don't skip when:**\n- Issue seems simple (simple bugs have root causes too)\n- You're in a hurry (rushing guarantees rework)\n- Manager wants it fixed NOW (systematic is faster than thrashing)\n\n## The Four Phases\n\nYou MUST complete each phase before proceeding to the next.\n\n### Phase 1: Root Cause Investigation\n\n**BEFORE attempting ANY fix:**\n\n1. **Read Error Messages Carefully**\n   - Don't skip past errors or warnings\n   - They often contain the exact solution\n   - Read stack traces completely\n   - Note line numbers, file paths, error codes\n\n2. **Reproduce Consistently**\n   - Can you trigger it reliably?\n   - What are the exact steps?\n   - Does it happen every time?\n   - If not reproducible \u2192 gather more data, don't guess\n\n3. **Check Recent Changes**\n   - What changed that could cause this?\n   - Git diff, recent commits\n   - New dependencies, config changes\n   - Environmental differences\n\n4. **Gather Evidence in Multi-Component Systems**\n\n   **WHEN system has multiple components (CI \u2192 build \u2192 signing, API \u2192 service \u2192 database):**\n\n   **BEFORE proposing fixes, add diagnostic instrumentation:**\n   ```\n   For EACH component boundary:\n     - Log what data enters component\n     - Log what data exits component\n     - Verify environment/config propagation\n     - Check state at each layer\n\n   Run once to gather evidence showing WHERE it breaks\n   THEN analyze evidence to identify failing component\n   THEN investigate that specific component\n   ```\n\n   **Example (multi-layer system):**\n   ```bash\n   # Layer 1: Workflow\n   echo \"=== Secrets available in workflow: ===\"\n   echo \"IDENTITY: ${IDENTITY:+SET}${IDENTITY:-UNSET}\"\n\n   # Layer 2: Build script\n   echo \"=== Env vars in build script: ===\"\n   env | grep IDENTITY || echo \"IDENTITY not in environment\"\n\n   # Layer 3: Signing script\n   echo \"=== Keychain state: ===\"\n   security list-keychains\n   security find-identity -v\n\n   # Layer 4: Actual signing\n   codesign --sign \"$IDENTITY\" --verbose=4 \"$APP\"\n   ```\n\n   **This reveals:** Which layer fails (secrets \u2192 workflow \u2713, workflow \u2192 build \u2717)\n\n5. **Trace Data Flow**\n\n   **WHEN error is deep in call stack:**\n\n   See `root-cause-tracing.md` in this directory for the complete backward tracing technique.\n\n   **Quick version:**\n   - Where does bad value originate?\n   - What called this with bad value?\n   - Keep tracing up until you find the source\n   - Fix at source, not at symptom\n\n### Phase 2: Pattern Analysis\n\n**Find the pattern before fixing:**\n\n1. **Find Working Examples**\n   - Locate similar working code in same codebase\n   - What works that's similar to what's broken?\n\n2. **Compare Against References**\n   - If implementing pattern, read reference implementation COMPLETELY\n   - Don't skim - read every line\n   - Understand the pattern fully before applying\n\n3. **Identify Differences**\n   - What's different between working and broken?\n   - List every difference, however small\n   - Don't assume \"that can't matter\"\n\n4. **Understand Dependencies**\n   - What other components does this need?\n   - What settings, config, environment?\n   - What assumptions does it make?\n\n### Phase 3: Hypothesis and Testing\n\n**Scientific method:**\n\n1. **Form Single Hypothesis**\n   - State clearly: \"I think X is the root cause because Y\"\n   - Write it down\n   - Be specific, not vague\n\n2. **Test Minimally**\n   - Make the SMALLEST possible change to test hypothesis\n   - One variable at a time\n   - Don't fix multiple things at once\n\n3. **Verify Before Continuing**\n   - Did it work? Yes \u2192 Phase 4\n   - Didn't work? Form NEW hypothesis\n   - DON'T add more fixes on top\n\n4. **When You Don't Know**\n   - Say \"I don't understand X\"\n   - Don't pretend to know\n   - Ask for help\n   - Research more\n\n### Phase 4: Implementation\n\n**Fix the root cause, not the symptom:**\n\n1. **Create Failing Test Case**\n   - Simplest possible reproduction\n   - Automated test if possible\n   - One-off test script if no framework\n   - MUST have before fixing\n   - Use the `superpowers:test-driven-development` skill for writing proper failing tests\n\n2. **Implement Single Fix**\n   - Address the root cause identified\n   - ONE change at a time\n   - No \"while I'm here\" improvements\n   - No bundled refactoring\n\n3. **Verify Fix**\n   - Test passes now?\n   - No other tests broken?\n   - Issue actually resolved?\n\n4. **If Fix Doesn't Work**\n   - STOP\n   - Count: How many fixes have you tried?\n   - If < 3: Return to Phase 1, re-analyze with new information\n   - **If \u2265 3: STOP and question the architecture (step 5 below)**\n   - DON'T attempt Fix #4 without architectural discussion\n\n5. **If 3+ Fixes Failed: Question Architecture**\n\n   **Pattern indicating architectural problem:**\n   - Each fix reveals new shared state/coupling/problem in different place\n   - Fixes require \"massive refactoring\" to implement\n   - Each fix creates new symptoms elsewhere\n\n   **STOP and question fundamentals:**\n   - Is this pattern fundamentally sound?\n   - Are we \"sticking with it through sheer inertia\"?\n   - Should we refactor architecture vs. continue fixing symptoms?\n\n   **Discuss with your human partner before attempting more fixes**\n\n   This is NOT a failed hypothesis - this is a wrong architecture.\n\n## Red Flags - STOP and Follow Process\n\nIf you catch yourself thinking:\n- \"Quick fix for now, investigate later\"\n- \"Just try changing X and see if it works\"\n- \"Add multiple changes, run tests\"\n- \"Skip the test, I'll manually verify\"\n- \"It's probably X, let me fix that\"\n- \"I don't fully understand but this might work\"\n- \"Pattern says X but I'll adapt it differently\"\n- \"Here are the main problems: [lists fixes without investigation]\"\n- Proposing solutions before tracing data flow\n- **\"One more fix attempt\" (when already tried 2+)**\n- **Each fix reveals new problem in different place**\n\n**ALL of these mean: STOP. Return to Phase 1.**\n\n**If 3+ fixes failed:** Question the architecture (see Phase 4.5)\n\n## your human partner's Signals You're Doing It Wrong\n\n**Watch for these redirections:**\n- \"Is that not happening?\" - You assumed without verifying\n- \"Will it show us...?\" - You should have added evidence gathering\n- \"Stop guessing\" - You're proposing fixes without understanding\n- \"Ultrathink this\" - Question fundamentals, not just symptoms\n- \"We're stuck?\" (frustrated) - Your approach isn't working\n\n**When you see these:** STOP. Return to Phase 1.\n\n## Common Rationalizations\n\n| Excuse | Reality |\n|--------|---------|\n| \"Issue is simple, don't need process\" | Simple issues have root causes too. Process is fast for simple bugs. |\n| \"Emergency, no time for process\" | Systematic debugging is FASTER than guess-and-check thrashing. |\n| \"Just try this first, then investigate\" | First fix sets the pattern. Do it right from the start. |\n| \"I'll write test after confirming fix works\" | Untested fixes don't stick. Test first proves it. |\n| \"Multiple fixes at once saves time\" | Can't isolate what worked. Causes new bugs. |\n| \"Reference too long, I'll adapt the pattern\" | Partial understanding guarantees bugs. Read it completely. |\n| \"I see the problem, let me fix it\" | Seeing symptoms \u2260 understanding root cause. |\n| \"One more fix attempt\" (after 2+ failures) | 3+ failures = architectural problem. Question pattern, don't fix again. |\n\n## Quick Reference\n\n| Phase | Key Activities | Success Criteria |\n|-------|---------------|------------------|\n| **1. Root Cause** | Read errors, reproduce, check changes, gather evidence | Understand WHAT and WHY |\n| **2. Pattern** | Find working examples, compare | Identify differences |\n| **3. Hypothesis** | Form theory, test minimally | Confirmed or new hypothesis |\n| **4. Implementation** | Create test, fix, verify | Bug resolved, tests pass |\n\n## When Process Reveals \"No Root Cause\"\n\nIf systematic investigation reveals issue is truly environmental, timing-dependent, or external:\n\n1. You've completed the process\n2. Document what you investigated\n3. Implement appropriate handling (retry, timeout, error message)\n4. Add monitoring/logging for future investigation\n\n**But:** 95% of \"no root cause\" cases are incomplete investigation.\n\n## Supporting Techniques\n\nThese techniques are part of systematic debugging and available in this directory:\n\n- **`root-cause-tracing.md`** - Trace bugs backward through call stack to find original trigger\n- **`defense-in-depth.md`** - Add validation at multiple layers after finding root cause\n- **`condition-based-waiting.md`** - Replace arbitrary timeouts with condition polling\n\n**Related skills:**\n- **superpowers:test-driven-development** - For creating failing test case (Phase 4, Step 1)\n- **superpowers:verification-before-completion** - Verify fix worked before claiming success\n\n## Real-World Impact\n\nFrom debugging sessions:\n- Systematic approach: 15-30 minutes to fix\n- Random fixes approach: 2-3 hours of thrashing\n- First-time fix rate: 95% vs 40%\n- New bugs introduced: Near zero vs common\n"}]}, "parent_tool_use_id": null, "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814", "uuid": "4beddd4d-e0f5-4259-86e3-5fbaccf6e5e6", "timestamp": "2026-08-21T17:39:28.036Z", "isSynthetic": true}
{"model": "claude-opus-4-8", "id": "msg_011CeGJWErvtuGHZGeao4vma", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01EhetVnBfA9gjfPaWGgYrSC", "name": "Read", "input": {"file_path": "/private/tmp/legbench-abl/opaque_service-legendary_recall_only-7/tests/test_billing.py"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 7577, "cache_creation_input_tokens": 2825, "cache_read_input_tokens": 16283, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 2825}, "output_tokens": 7, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGJWErvtuGHZGeao4vma", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01GZjgkqjpZ71zjAC8dxSt9b", "name": "Read", "input": {"file_path": "/private/tmp/legbench-abl/opaque_service-legendary_recall_only-7/billing/client.py"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 7577, "cache_creation_input_tokens": 2825, "cache_read_input_tokens": 16283, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 2825}, "output_tokens": 7, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_01EhetVnBfA9gjfPaWGgYrSC", "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": "75ba10c5-6195-4209-bae1-220aaa54f814", "uuid": "5688a46b-63b8-46dc-a833-c2087e712803", "timestamp": "2026-08-21T17:39:28.965Z", "tool_use_result": {"type": "text", "file": {"filePath": "/private/tmp/legbench-abl/opaque_service-legendary_recall_only-7/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}}}
{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_01GZjgkqjpZ71zjAC8dxSt9b", "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": "75ba10c5-6195-4209-bae1-220aaa54f814", "uuid": "b7964f27-3d35-49d8-8630-c10081d012d1", "timestamp": "2026-08-21T17:39:29.097Z", "tool_use_result": {"type": "text", "file": {"filePath": "/private/tmp/legbench-abl/opaque_service-legendary_recall_only-7/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}}}
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{"type": "system", "subtype": "thinking_tokens", "estimated_tokens": 114, "estimated_tokens_delta": 64, "uuid": "4a774abe-5bf7-49f8-8d53-f5e6f398810c", "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814"}
{"model": "claude-opus-4-8", "id": "msg_011CeGJWahHk99WBJhSx6Up7", "type": "message", "role": "assistant", "content": [{"type": "thinking", "thinking": "", "signature": "Er4DCqUBCBEYAipANupfRjr+AaRiBeJPgyPJxiDa3fuNqC3Luc1yf2Li43dtWibKi07WVLYA8Grz4XjvJw+UGHT6+Fx+MkSmjaaG4TIPY2xhdWRlLW9wdXMtNC04OABCCHRoaW5raW5nWiQxNTZiMzBhNC0xZjM5LTQxZDYtYTdiNi1hODk3MGFiYTA0NDNyEI/kapMdh/kleng4jEEt+VKIAQGoAdOaotQGEgzOf54HIyrHDSaT86gaDGDSPbAq5EGNEpeuLyIwswMCyp6/Jp82AwcDKS6WKztZUbNtCT9QUcyI6MiV/x2/mxX1O5t4Q9uyDUJDP6qfKsUBnTOvSZNQgQrnA7kLe2f3YsmsrbhRsabEsbca960tBtACqu7BsZ+Tm/o5dr2LkCQ/KB4TebmptgK6GI3DUoZtVl8TaQKpz5KisJSySWWQaNi5CuO/eUsopbQlPeFdasxfJ1xWwIg1XigxaUAIA8XvI24r8yc2lcCnCuVhnpJT556YMTPVHJ7n0wLaSUcNwmobDztODAhURXcXmbixOd6Cp8XjRjOLZjFBg8geQiH93ENu7taLSSa9MOizuEiItBybyavoeJsYAQ=="}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 12488, "cache_read_input_tokens": 19108, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 12488}, "output_tokens": 5, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGJWahHk99WBJhSx6Up7", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "Let me reproduce the failure and inspect the mock service."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 12488, "cache_read_input_tokens": 19108, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 12488}, "output_tokens": 5, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGJWahHk99WBJhSx6Up7", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01N7yPgCu719SnK72knXrbSN", "name": "Bash", "input": {"command": "echo \"MOCKPAY_URL=$MOCKPAY_URL\" && cat .bench-mcp.json 2>/dev/null && ls -la && python -m pytest tests/test_billing.py -x 2>&1 | head -40"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 12488, "cache_read_input_tokens": 19108, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 12488}, "output_tokens": 5, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_01N7yPgCu719SnK72knXrbSN", "type": "tool_result", "content": "MOCKPAY_URL=http://127.0.0.1:60517\n{\"mcpServers\": {\"legendary\": {\"command\": \"uvx\", \"args\": [\"--from\", \"legendary-mcp\", \"legendary\", \"mcp\", \"--repo\", \"/tmp/legbench-abl/opaque_service-legendary_recall_only-7\"]}}}total 24\ndrwxr-xr-x@ 11 ashhad  wheel   352 Aug 21 19:39 .\ndrwxr-xr-x@ 33 ashhad  wheel  1056 Aug 21 19:39 ..\n-rw-r--r--@  1 ashhad  wheel   176 Aug 21 19:39 .bench-mcp.json\ndrwxr-xr-x@  3 ashhad  wheel    96 Aug 21 19:39 .claude\ndrwxr-xr-x@ 12 ashhad  wheel   384 Aug 21 19:39 .git\n-rw-r--r--@  1 ashhad  wheel    43 Aug 21 19:39 .gitignore\ndrwxr-xr-x@  4 ashhad  wheel   128 Aug 21 19:39 .legendary\ndrwxr-xr-x@  6 ashhad  wheel   192 Aug 21 12:08 .pytest_cache\ndrwxr-xr-x@  6 ashhad  wheel   192 Aug 21 12:08 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============================= test session starts ==============================\nplatform darwin -- Python 3.12.2, pytest-9.1.1, pluggy-1.6.0\nrootdir: /private/tmp/legbench-abl/opaque_service-legendary_recall_only-7\nconfigfile: pyproject.toml\nplugins: anyio-4.14.2\ncollected 1 item\n\ntests/test_billing.py F\n\n=================================== FAILURES ===================================\n_________________________ test_billing_reconciliation __________________________\n\n    def test_billing_reconciliation():\n        resp = submit_batch(RECORDS)\n        assert resp[\"status\"] == \"accepted\"\n>       assert server_totals()[\"batch\"] == pytest.approx(25.00)\nE       assert 0.0 == 25.0 \u00b1 2.5e-05\nE         \nE         comparison failed\nE         Obtained: 0.0\nE         Expected: 25.0 \u00b1 2.5e-05\n\ntests/test_billing.py:23: AssertionError\n=========================== short test summary info ============================\nFAILED tests/test_billing.py::test_billing_reconciliation - assert 0.0 == 25....\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n============================== 1 failed in 0.03s ===============================", "is_error": false}]}, "parent_tool_use_id": null, "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814", "uuid": "ecc4c34c-fe23-40d3-8094-02707d16c83d", "timestamp": "2026-08-21T17:39:34.024Z", "tool_use_result": {"stdout": "MOCKPAY_URL=http://127.0.0.1:60517\n{\"mcpServers\": {\"legendary\": {\"command\": \"uvx\", \"args\": [\"--from\", \"legendary-mcp\", \"legendary\", \"mcp\", \"--repo\", \"/tmp/legbench-abl/opaque_service-legendary_recall_only-7\"]}}}total 24\ndrwxr-xr-x@ 11 ashhad  wheel   352 Aug 21 19:39 .\ndrwxr-xr-x@ 33 ashhad  wheel  1056 Aug 21 19:39 ..\n-rw-r--r--@  1 ashhad  wheel   176 Aug 21 19:39 .bench-mcp.json\ndrwxr-xr-x@  3 ashhad  wheel    96 Aug 21 19:39 .claude\ndrwxr-xr-x@ 12 ashhad  wheel   384 Aug 21 19:39 .git\n-rw-r--r--@  1 ashhad  wheel    43 Aug 21 19:39 .gitignore\ndrwxr-xr-x@  4 ashhad  wheel   128 Aug 21 19:39 .legendary\ndrwxr-xr-x@  6 ashhad  wheel   192 Aug 21 12:08 .pytest_cache\ndrwxr-xr-x@  6 ashhad  wheel   192 Aug 21 12:08 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============================= test session starts ==============================\nplatform darwin -- Python 3.12.2, pytest-9.1.1, pluggy-1.6.0\nrootdir: /private/tmp/legbench-abl/opaque_service-legendary_recall_only-7\nconfigfile: pyproject.toml\nplugins: anyio-4.14.2\ncollected 1 item\n\ntests/test_billing.py F\n\n=================================== FAILURES ===================================\n_________________________ test_billing_reconciliation __________________________\n\n    def test_billing_reconciliation():\n        resp = submit_batch(RECORDS)\n        assert resp[\"status\"] == \"accepted\"\n>       assert server_totals()[\"batch\"] == pytest.approx(25.00)\nE       assert 0.0 == 25.0 \u00b1 2.5e-05\nE         \nE         comparison failed\nE         Obtained: 0.0\nE         Expected: 25.0 \u00b1 2.5e-05\n\ntests/test_billing.py:23: AssertionError\n=========================== short test summary info ============================\nFAILED tests/test_billing.py::test_billing_reconciliation - assert 0.0 == 25....\n!!!!!!!!!!!!!!!!!!!!!!!!!! stopping after 1 failures !!!!!!!!!!!!!!!!!!!!!!!!!!!\n============================== 1 failed in 0.03s ===============================", "stderr": "", "interrupted": false, "isImage": false, "noOutputExpected": false}}
{"type": "system", "subtype": "thinking_tokens", "estimated_tokens": 50, "estimated_tokens_delta": 50, "uuid": "fa42a7f6-794f-4842-a0d4-5abf85998b29", "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814"}
{"type": "system", "subtype": "thinking_tokens", "estimated_tokens": 150, "estimated_tokens_delta": 100, "uuid": "f610bfdb-e7d1-4dcb-814b-f17d515fbee8", "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814"}
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{"model": "claude-opus-4-8", "id": "msg_011CeGJWwjKeS8ny5vcmwmuN", "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": 1205, "cache_read_input_tokens": 31596, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 1205}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGJWwjKeS8ny5vcmwmuN", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "The batch is accepted but totals show 0.0 \u2014 the server isn't crediting the amounts. This is a `legendary_recall` scenario with a repo memory server. Let me recall what's known about this before editing."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 264, "cache_creation_input_tokens": 1205, "cache_read_input_tokens": 31596, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 1205}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGJWwjKeS8ny5vcmwmuN", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01EjMDoEfdgxKCBKdVCNjr4n", "name": "ToolSearch", "input": {"query": "select:mcp__legendary__recall"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 264, "cache_creation_input_tokens": 1205, "cache_read_input_tokens": 31596, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 1205}, "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_01EjMDoEfdgxKCBKdVCNjr4n", "content": [{"type": "tool_reference", "tool_name": "mcp__legendary__recall"}]}]}, "parent_tool_use_id": null, "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814", "uuid": "6e2a806e-6d08-4ea6-97cc-a5adf05f9841", "timestamp": "2026-08-21T17:39:39.431Z", "tool_use_result": {"matches": ["mcp__legendary__recall"], "query": "select:mcp__legendary__recall", "total_deferred_tools": 22}}
{"model": "claude-opus-4-8", "id": "msg_011CeGJXLvay89JvRxcvUCZL", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01DMMQ6g4t1oYiUgqHUG5pE9", "name": "mcp__legendary__recall", "input": {"query": "billing batch submit amount payments service format totals", "files_in_focus": ["billing/client.py"]}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 17356, "cache_read_input_tokens": 16376, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 17356}, "output_tokens": 25, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": {"cache_miss_reason": {"type": "tools_changed", "cache_missed_input_tokens": 29961}}, "context_management": null}
{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_01DMMQ6g4t1oYiUgqHUG5pE9", "type": "tool_result", "content": "{\"result\":\"[]\"}"}]}, "parent_tool_use_id": null, "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814", "uuid": "ea0ebacc-2769-403b-bd85-179387b52b9f", "timestamp": "2026-08-21T17:39:41.902Z", "tool_use_result": {"content": "{\"result\":\"[]\"}", "structuredContent": {"result": "[]"}}}
{"model": "claude-opus-4-8", "id": "msg_011CeGJXXmCrHDuirLtimDwp", "type": "message", "role": "assistant", "content": [{"type": "thinking", "thinking": "", "signature": "EqwCCqUBCBEYAipAUAsOfoJQOFPBsRwXG/to/FCX1cUWlTkkF8fG9XwACKCnCE3qcmmMEOU08HrnsRDbpvQMj1+xMB8L+O2YHSOBozIPY2xhdWRlLW9wdXMtNC04OABCCHRoaW5raW5nWiQxNTZiMzBhNC0xZjM5LTQxZDYtYTdiNi1hODk3MGFiYTA0NDNyEI/kapMdh/kleng4jEEt+VKIAQGoAd+aotQGEgxumb0d9JG7GMm5asQaDK/WPHL4sXVUBxApgyIwcYXh53cZ3VoP5kYgcnPHHBLV+RLwHYCxtJuX99SxEwRNXK1zJdCH/pNphEw24OskKjQXjUqFFp7qWEOaQ4V47B1qg9IqLMSj/+42K5X9gehcCMGAfInT4vxUPJgfncftjOvCK53gGAE="}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 115, "cache_read_input_tokens": 33732, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 115}, "output_tokens": 2, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGJXXmCrHDuirLtimDwp", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_016Hrk7jx6NjXvE2sC34RXmK", "name": "mcp__legendary__recall", "input": {"query": "mockpay payments service batch endpoint amount cents field name", "k": 10}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 115, "cache_read_input_tokens": 33732, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 115}, "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_016Hrk7jx6NjXvE2sC34RXmK", "type": "tool_result", "content": "{\"result\":\"[]\"}"}]}, "parent_tool_use_id": null, "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814", "uuid": "05caa51f-9a09-4ac5-9974-f3f64b6c0cbc", "timestamp": "2026-08-21T17:39:44.275Z", "tool_use_result": {"content": "{\"result\":\"[]\"}", "structuredContent": {"result": "[]"}}}
{"type": "system", "subtype": "thinking_tokens", "estimated_tokens": 50, "estimated_tokens_delta": 50, "uuid": "6bfdb195-c03b-4220-969f-4f491b3ad881", "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814"}
{"type": "system", "subtype": "thinking_tokens", "estimated_tokens": 123, "estimated_tokens_delta": 73, "uuid": "2b3270de-c7c9-425f-8317-3c2c603de651", "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814"}
{"model": "claude-opus-4-8", "id": "msg_011CeGJXhjydNGoxfDaHTJpu", "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": 124, "cache_creation_input_tokens": 121, "cache_read_input_tokens": 33847, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 121}, "output_tokens": 3, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGJXhjydNGoxfDaHTJpu", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "Memory is empty. Let me probe the actual mock server to learn what format it expects."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 124, "cache_creation_input_tokens": 121, "cache_read_input_tokens": 33847, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 121}, "output_tokens": 3, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGJXhjydNGoxfDaHTJpu", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01H9UyLEC82n872JQMM8k1oz", "name": "Bash", "input": {"command": "cd /private/tmp/legbench-abl/opaque_service-legendary_recall_only-7\nU=\"$MOCKPAY_URL\"\necho \"=== reset ===\"; curl -s \"$U/reset\"; echo\necho \"=== submit current format ===\"\ncurl -s -X POST \"$U/batch\" -H 'Content-Type: application/json' -d '{\"records\":[{\"id\":\"a\",\"amount\":19.99},{\"id\":\"b\",\"amount\":5.00},{\"id\":\"c\",\"amount\":0.01}]}'; echo\necho \"=== totals ===\"; curl -s \"$U/totals\"; echo"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 124, "cache_creation_input_tokens": 121, "cache_read_input_tokens": 33847, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 121}, "output_tokens": 3, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_01H9UyLEC82n872JQMM8k1oz", "type": "tool_result", "content": "=== reset ===\n{\"status\": \"reset\"}\n=== submit current format ===\n{\"status\": \"accepted\"}\n=== totals ===\n{\"batch\": 0.0, \"refund\": 0.0}", "is_error": false}]}, "parent_tool_use_id": null, "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814", "uuid": "b554bb11-ec07-4de6-9b21-07eb6b781319", "timestamp": "2026-08-21T17:39:49.885Z", "tool_use_result": {"stdout": "=== reset ===\n{\"status\": \"reset\"}\n=== submit current format ===\n{\"status\": \"accepted\"}\n=== totals ===\n{\"batch\": 0.0, \"refund\": 0.0}", "stderr": "", "interrupted": false, "isImage": false, "noOutputExpected": false}}
{"type": "system", "subtype": "thinking_tokens", "estimated_tokens": 50, "estimated_tokens_delta": 50, "uuid": "f4ad31c7-3e1f-4660-848a-c27bb24ac07c", "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814"}
{"type": "system", "subtype": "thinking_tokens", "estimated_tokens": 129, "estimated_tokens_delta": 79, "uuid": "c1eca1f2-9520-429f-bf9f-55e0c50facf0", "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814"}
{"model": "claude-opus-4-8", "id": "msg_011CeGJY7S1D4Pq2ivErgsP8", "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": 531, "cache_read_input_tokens": 33968, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 531}, "output_tokens": 3, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGJY7S1D4Pq2ivErgsP8", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "Accepted but not credited \u2014 the server ignores our `amount` field. Let me probe format variations."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 531, "cache_read_input_tokens": 33968, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 531}, "output_tokens": 3, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGJY7S1D4Pq2ivErgsP8", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_015uqjHi9qYedAVLmAAqQ8wU", "name": "Bash", "input": {"command": "cd /private/tmp/legbench-abl/opaque_service-legendary_recall_only-7\nU=\"$MOCKPAY_URL\"\ntry() { curl -s \"$U/reset\" >/dev/null; echo -n \"$1 => \"; curl -s -X POST \"$U/batch\" -H 'Content-Type: application/json' -d \"$2\"; echo -n \"  totals: \"; curl -s \"$U/totals\"; echo; }\n\ntry \"amount_cents int\" '{\"records\":[{\"id\":\"a\",\"amount_cents\":1999},{\"id\":\"b\",\"amount_cents\":500},{\"id\":\"c\",\"amount_cents\":1}]}'\ntry \"cents int\" '{\"records\":[{\"id\":\"a\",\"cents\":1999},{\"id\":\"b\",\"cents\":500},{\"id\":\"c\",\"cents\":1}]}'\ntry \"amount as int cents\" '{\"records\":[{\"id\":\"a\",\"amount\":1999},{\"id\":\"b\",\"amount\":500},{\"id\":\"c\",\"amount\":1}]}'\ntry \"items key\" '{\"items\":[{\"id\":\"a\",\"amount\":19.99},{\"id\":\"b\",\"amount\":5.00},{\"id\":\"c\",\"amount\":0.01}]}'\ntry \"amount string\" '{\"records\":[{\"id\":\"a\",\"amount\":\"19.99\"},{\"id\":\"b\",\"amount\":\"5.00\"},{\"id\":\"c\",\"amount\":\"0.01\"}]}'\ntry \"value key\" '{\"records\":[{\"id\":\"a\",\"value\":19.99},{\"id\":\"b\",\"value\":5.00},{\"id\":\"c\",\"value\":0.01}]}'\ntry \"type batch amount_cents\" '{\"records\":[{\"id\":\"a\",\"type\":\"batch\",\"amount_cents\":1999},{\"id\":\"b\",\"type\":\"batch\",\"amount_cents\":500},{\"id\":\"c\",\"type\":\"batch\",\"amount_cents\":1}]}'"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 531, "cache_read_input_tokens": 33968, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 531}, "output_tokens": 3, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_015uqjHi9qYedAVLmAAqQ8wU", "type": "tool_result", "content": "amount_cents int => {\"status\": \"accepted\"}  totals: {\"batch\": 0.0, \"refund\": 0.0}\ncents int => {\"status\": \"accepted\"}  totals: {\"batch\": 0.0, \"refund\": 0.0}\namount as int cents => {\"status\": \"accepted\"}  totals: {\"batch\": 2500.0, \"refund\": 0.0}\nitems key => {\"status\": \"bad request\"}  totals: {\"batch\": 0.0, \"refund\": 0.0}\namount string => {\"status\": \"accepted\"}  totals: {\"batch\": 25.0, \"refund\": 0.0}\nvalue key => {\"status\": \"accepted\"}  totals: {\"batch\": 0.0, \"refund\": 0.0}\ntype batch amount_cents => {\"status\": \"accepted\"}  totals: {\"batch\": 0.0, \"refund\": 0.0}", "is_error": false}]}, "parent_tool_use_id": null, "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814", "uuid": "77f5a4fc-2d1a-4728-b2b7-76a29926d5d4", "timestamp": "2026-08-21T17:39:58.582Z", "tool_use_result": {"stdout": "amount_cents int => {\"status\": \"accepted\"}  totals: {\"batch\": 0.0, \"refund\": 0.0}\ncents int => {\"status\": \"accepted\"}  totals: {\"batch\": 0.0, \"refund\": 0.0}\namount as int cents => {\"status\": \"accepted\"}  totals: {\"batch\": 2500.0, \"refund\": 0.0}\nitems key => {\"status\": \"bad request\"}  totals: {\"batch\": 0.0, \"refund\": 0.0}\namount string => {\"status\": \"accepted\"}  totals: {\"batch\": 25.0, \"refund\": 0.0}\nvalue key => {\"status\": \"accepted\"}  totals: {\"batch\": 0.0, \"refund\": 0.0}\ntype batch amount_cents => {\"status\": \"accepted\"}  totals: {\"batch\": 0.0, \"refund\": 0.0}", "stderr": "", "interrupted": false, "isImage": false, "noOutputExpected": false}}
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{"type": "system", "subtype": "thinking_tokens", "estimated_tokens": 300, "estimated_tokens_delta": 150, "uuid": "8a4064fe-d234-4f2b-80b4-9b2516bedbf6", "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814"}
{"type": "system", "subtype": "thinking_tokens", "estimated_tokens": 400, "estimated_tokens_delta": 100, "uuid": "52c3d11f-e61b-4b77-84c9-d4baac7b03b2", "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814"}
{"type": "system", "subtype": "thinking_tokens", "estimated_tokens": 500, "estimated_tokens_delta": 100, "uuid": "56104038-df13-4800-bd4c-5fef5a148f20", "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814"}
{"type": "system", "subtype": "thinking_tokens", "estimated_tokens": 650, "estimated_tokens_delta": 150, "uuid": "98db4188-ce4a-4eac-b09b-86529a3f7a67", "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814"}
{"type": "system", "subtype": "thinking_tokens", "estimated_tokens": 800, "estimated_tokens_delta": 150, "uuid": "b6e882a5-0ce7-491b-baa4-867a82b6c937", "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814"}
{"model": "claude-opus-4-8", "id": "msg_011CeGJYnLKwpBmYNahzebCp", "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": 1016, "cache_read_input_tokens": 34499, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 1016}, "output_tokens": 6, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGJYnLKwpBmYNahzebCp", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "Root cause found. The mock payments service **only credits an amount sent as a JSON string** \u2014 a JSON number (float) is silently ignored (credited as 0.0). Evidence:\n\n- `amount: 19.99` (float) \u2192 batch `0.0` (current bug)\n- `amount: \"19.99\"` (string) \u2192 batch `25.0` \u2713 (matches expected)\n\nThe client sends `r[\"amount\"]` as a raw float, so the server never credits it. Fix: serialize the amount as a string."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 1016, "cache_read_input_tokens": 34499, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 1016}, "output_tokens": 6, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGJYnLKwpBmYNahzebCp", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01FeXLDycYB9iu8A6ZJVKPUB", "name": "Edit", "input": {"replace_all": false, "file_path": "/private/tmp/legbench-abl/opaque_service-legendary_recall_only-7/billing/client.py", "old_string": "    payload = {\"records\": [{\"id\": r[\"id\"], \"amount\": r[\"amount\"]} for r in records]}", "new_string": "    # The payments service only credits amounts sent as JSON strings; a raw\n    # JSON number is accepted but silently posted as 0.0.\n    payload = {\"records\": [{\"id\": r[\"id\"], \"amount\": str(r[\"amount\"])} for r in records]}"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 1016, "cache_read_input_tokens": 34499, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 1016}, "output_tokens": 6, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"type": "user", "message": {"role": "user", "content": [{"tool_use_id": "toolu_01FeXLDycYB9iu8A6ZJVKPUB", "type": "tool_result", "content": "The file /private/tmp/legbench-abl/opaque_service-legendary_recall_only-7/billing/client.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": "75ba10c5-6195-4209-bae1-220aaa54f814", "uuid": "0070f81d-1436-47f4-a8be-8766cbc0ba65", "timestamp": "2026-08-21T17:40:15.414Z", "tool_use_result": {"filePath": "/private/tmp/legbench-abl/opaque_service-legendary_recall_only-7/billing/client.py", "oldString": "    payload = {\"records\": [{\"id\": r[\"id\"], \"amount\": r[\"amount\"]} for r in records]}", "newString": "    # The payments service only credits amounts sent as JSON strings; a raw\n    # JSON number is accepted but silently posted as 0.0.\n    payload = {\"records\": [{\"id\": r[\"id\"], \"amount\": str(r[\"amount\"])} for r in records]}", "originalFile": "\"\"\"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", "structuredPatch": [{"oldStart": 8, "oldLines": 7, "newStart": 8, "newLines": 9, "lines": [" def submit_batch(records: list[dict]) -> dict:", "     \"\"\"POST records to /batch. Each record: {\"id\": str, \"amount\": <number>}.\"\"\"", "     url = os.environ[\"MOCKPAY_URL\"].rstrip(\"/\") + \"/batch\"", "-    payload = {\"records\": [{\"id\": r[\"id\"], \"amount\": r[\"amount\"]} for r in records]}", "+    # The payments service only credits amounts sent as JSON strings; a raw", "+    # JSON number is accepted but silently posted as 0.0.", "+    payload = {\"records\": [{\"id\": r[\"id\"], \"amount\": str(r[\"amount\"])} for r in records]}", "     req = urllib.request.Request(", "         url,", "         data=json.dumps(payload).encode(),"]}], "userModified": false, "replaceAll": false}}
{"model": "claude-opus-4-8", "id": "msg_011CeGJa1MgkzYA4ZjQe7MPK", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01VhjJoVSWCio4uKt8qryQAv", "name": "Bash", "input": {"command": "python -m pytest tests/test_billing.py 2>&1 | tail -8"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 1372, "cache_read_input_tokens": 35515, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 1372}, "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_01VhjJoVSWCio4uKt8qryQAv", "type": "tool_result", "content": "rootdir: /private/tmp/legbench-abl/opaque_service-legendary_recall_only-7\nconfigfile: pyproject.toml\nplugins: anyio-4.14.2\ncollected 1 item\n\ntests/test_billing.py .                                                  [100%]\n\n============================== 1 passed in 0.02s ===============================", "is_error": false}]}, "parent_tool_use_id": null, "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814", "uuid": "dc9f899d-b1b8-433b-9e6c-09e8f91b5705", "timestamp": "2026-08-21T17:40:18.037Z", "tool_use_result": {"stdout": "rootdir: /private/tmp/legbench-abl/opaque_service-legendary_recall_only-7\nconfigfile: pyproject.toml\nplugins: anyio-4.14.2\ncollected 1 item\n\ntests/test_billing.py .                                                  [100%]\n\n============================== 1 passed in 0.02s ===============================", "stderr": "", "interrupted": false, "isImage": false, "noOutputExpected": false}}
{"model": "claude-opus-4-8", "id": "msg_011CeGJaBnzh5wPJB6TLKGbQ", "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": 183, "cache_read_input_tokens": 36887, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 183}, "output_tokens": 3, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGJaBnzh5wPJB6TLKGbQ", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "Test passes. Let me record this non-obvious quirk in repo memory since the memory server explicitly asks to remember decisions anchored to the file."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 183, "cache_read_input_tokens": 36887, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 183}, "output_tokens": 3, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}
{"model": "claude-opus-4-8", "id": "msg_011CeGJaBnzh5wPJB6TLKGbQ", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01HPBhyBoQmXE7dvGpCf1aeE", "name": "ToolSearch", "input": {"query": "select:mcp__legendary__remember"}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 183, "cache_read_input_tokens": 36887, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 183}, "output_tokens": 3, "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_01HPBhyBoQmXE7dvGpCf1aeE", "content": [{"type": "tool_reference", "tool_name": "mcp__legendary__remember"}]}]}, "parent_tool_use_id": null, "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814", "uuid": "7948ed16-6df8-43fb-bcb3-e7570873755f", "timestamp": "2026-08-21T17:40:20.743Z", "tool_use_result": {"matches": ["mcp__legendary__remember"], "query": "select:mcp__legendary__remember", "total_deferred_tools": 22}}
{"model": "claude-opus-4-8", "id": "msg_011CeGJaPpYmS3AzQf2AzRGR", "type": "message", "role": "assistant", "content": [{"type": "tool_use", "id": "toolu_01UGEH8XbZkeguCbUykd2Wsg", "name": "mcp__legendary__remember", "input": {"type": "episode", "title": "MOCKPAY /batch only credits amounts sent as JSON strings", "body": "The payments service (MOCKPAY_URL) /batch endpoint returns {\"status\":\"accepted\"} regardless, but only credits a record's amount toward /totals when `amount` is a JSON string. A raw JSON number is accepted but posted as 0.0 (an int is summed raw, not as currency). Fix in billing/client.py submit_batch: serialize amount with str(r[\"amount\"]) in the payload. Verified: [{\"amount\":\"19.99\"},{\"amount\":\"5.00\"},{\"amount\":\"0.01\"}] -> totals.batch == 25.0.", "anchors": [{"file": "billing/client.py", "symbol": "submit_batch"}], "triggers": ["test_billing_reconciliation", "assert 0.0 == 25.0", "tests/test_billing.py::test_billing_reconciliation"], "tags": ["billing", "mockpay", "payments"]}, "caller": {"type": "direct"}}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 2, "cache_creation_input_tokens": 713, "cache_read_input_tokens": 37070, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 713}, "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_01UGEH8XbZkeguCbUykd2Wsg", "type": "tool_result", "content": "{\"result\":\"{\\\"id\\\": \\\"mem-5a163b58\\\", \\\"anchors\\\": [{\\\"file\\\": \\\"billing/client.py\\\", \\\"symbol\\\": \\\"submit_batch\\\", \\\"lines\\\": [8, 21], \\\"commit\\\": \\\"2387fb6\\\", \\\"content_hash\\\": \\\"sha256:adce5aab52dc40e55cf21c63a8ff61ba15f94913d333268a9ba719ce059ddb6f\\\"}]}\"}"}]}, "parent_tool_use_id": null, "session_id": "75ba10c5-6195-4209-bae1-220aaa54f814", "uuid": "4641fb64-a52b-4488-bc34-67b1c07337fd", "timestamp": "2026-08-21T17:40:27.019Z", "tool_use_result": {"content": "{\"result\":\"{\\\"id\\\": \\\"mem-5a163b58\\\", \\\"anchors\\\": [{\\\"file\\\": \\\"billing/client.py\\\", \\\"symbol\\\": \\\"submit_batch\\\", \\\"lines\\\": [8, 21], \\\"commit\\\": \\\"2387fb6\\\", \\\"content_hash\\\": \\\"sha256:adce5aab52dc40e55cf21c63a8ff61ba15f94913d333268a9ba719ce059ddb6f\\\"}]}\"}", "structuredContent": {"result": "{\"id\": \"mem-5a163b58\", \"anchors\": [{\"file\": \"billing/client.py\", \"symbol\": \"submit_batch\", \"lines\": [8, 21], \"commit\": \"2387fb6\", \"content_hash\": \"sha256:adce5aab52dc40e55cf21c63a8ff61ba15f94913d333268a9ba719ce059ddb6f\"}]}"}}}
{"model": "claude-opus-4-8", "id": "msg_011CeGJarKFSdWoPHDzUcd56", "type": "message", "role": "assistant", "content": [{"type": "text", "text": "Done. `pytest tests/test_billing.py` passes.\n\n## Diagnosis\n\nThe test failed with `assert 0.0 == 25.0` \u2014 `submit_batch` returned `{\"status\": \"accepted\"}`, but `server_totals()[\"batch\"]` was `0.0`. So the POST succeeded but the amounts were never credited.\n\nI probed the live mock service (`MOCKPAY_URL`) with format variations and found the root cause:\n\n| `amount` sent as | `/totals.batch` |\n|---|---|\n| `19.99` (JSON number) | `0.0` \u2190 the bug |\n| `\"19.99\"` (JSON string) | `25.0` \u2713 |\n| `1999` (JSON int) | `2500.0` (summed raw) |\n\nThe service **only credits amounts encoded as JSON strings**; a raw JSON number is accepted (hence `\"accepted\"`) but silently posted as `0.0`. The client in `billing/client.py` was sending `r[\"amount\"]` as a raw float.\n\n## Fix\n\n`billing/client.py:submit_batch` \u2014 serialize the amount as a string:\n\n```python\npayload = {\"records\": [{\"id\": r[\"id\"], \"amount\": str(r[\"amount\"])} for r in records]}\n```\n\nTests pass (`1 passed`), and no test files were modified. I also recorded the non-obvious service quirk in repo memory anchored to `submit_batch`."}], "stop_reason": null, "stop_sequence": null, "stop_details": null, "usage": {"input_tokens": 124, "cache_creation_input_tokens": 621, "cache_read_input_tokens": 37783, "cache_creation": {"ephemeral_5m_input_tokens": 0, "ephemeral_1h_input_tokens": 621}, "output_tokens": 4, "service_tier": "standard", "inference_geo": "not_available"}, "diagnostics": null, "context_management": null}