cursor(rules[avoid-debug-loops]) Prevent AI digging us a hole

Add a new cursor rule 'avoid-debug-loops' that helps identify when
debugging efforts are becoming circular and counterproductive.

The rule provides:
- Clear indicators for detecting debug loops
- A 4-step action plan to break the cycle
- A structured format for documenting issues completely
- A portable template for sharing problems in a fresh context

This will help reduce time spent in frustrating debugging loops and
facilitate more efficient problem-solving approaches.

Author: tony

.cursor/rules/avoid-debug-loops.mdc

@@ -0,0 +1,57 @@
+---
+description: When stuck in debugging loops, break the cycle by minimizing to an MVP, removing debugging cruft, and documenting the issue completely for a fresh approach
+globs: *.py
+alwaysApply: false
+---
+# Avoid Debug Loops
+
+When debugging becomes circular and unproductive, follow these steps:
+
+## Detection
+- You have made multiple unsuccessful attempts to fix the same issue
+- You are adding increasingly complex code to address errors
+- Each fix creates new errors in a cascading pattern
+- You are uncertain about the root cause after 2-3 iterations
+
+## Action Plan
+
+1. **Pause and acknowledge the loop**
+   - Explicitly state that you are in a potential debug loop
+   - Review what approaches have been tried and failed
+
+2. **Minimize to MVP**
+   - Remove all debugging cruft and experimental code
+   - Revert to the simplest version that demonstrates the issue
+   - Focus on isolating the core problem without added complexity
+
+3. **Comprehensive Documentation**
+   - Provide a clear summary of the issue
+   - Include minimal but complete code examples that reproduce the problem
+   - Document exact error messages and unexpected behaviors
+   - Explain your current understanding of potential causes
+
+4. **Format for Portability**
+   - Present the problem in quadruple backticks for easy copying:
+
+````
+# Problem Summary
+[Concise explanation of the issue]
+
+## Minimal Reproduction Code
+```python
+# Minimal code example that reproduces the issue
+```
+
+## Error/Unexpected Output
+```
+[Exact error messages or unexpected output]
+```
+
+## Failed Approaches
+[Brief summary of approaches already tried]
+
+## Suspected Cause
+[Your current hypothesis about what might be causing the issue]
+````
+
+This format enables the user to easily copy the entire problem statement into a fresh conversation for a clean-slate approach.