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cursor,windsurf(rules[dev-loop]) Sync with latest python loop
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‎.cursor/rules/avoid-debug-loops.mdc

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

‎.cursor/rules/dev-loop.mdc

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---
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description: QA every edit
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globs: *.py
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alwaysApply: true
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---
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# Development Process
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## Project Stack
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The project uses the following tools and technologies:
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- **uv** - Python package management and virtual environments
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- **ruff** - Fast Python linter and formatter
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- **py.test** - Testing framework
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- **pytest-watcher** - Continuous test runner
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- **mypy** - Static type checking
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- **doctest** - Testing code examples in documentation
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## 1. Start with Formatting
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Format your code first:
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```
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uv run ruff format .
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```
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## 2. Run Tests
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Verify that your changes pass the tests:
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```
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uv run py.test
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```
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For continuous testing during development, use pytest-watcher:
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```
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# Watch all tests
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uv run ptw .
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# Watch and run tests immediately, including doctests
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uv run ptw . --now --doctest-modules
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# Watch specific files or directories
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uv run ptw . --now --doctest-modules src/libtmux/_internal/
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```
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## 3. Commit Initial Changes
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Make an atomic commit for your changes using conventional commits.
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Use `@git-commits.mdc` for assistance with commit message standards.
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## 4. Run Linting and Type Checking
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Check and fix linting issues:
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```
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uv run ruff check . --fix --show-fixes
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```
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Check typings:
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```
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uv run mypy
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```
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## 5. Verify Tests Again
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Ensure tests still pass after linting and type fixes:
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```
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uv run py.test
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```
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## 6. Final Commit
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Make a final commit with any linting/typing fixes.
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Use `@git-commits.mdc` for assistance with commit message standards.
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## Development Loop Guidelines
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If there are any failures at any step due to your edits, fix them before proceeding to the next step.
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## Python Code Standards
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### Docstring Guidelines
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For `src/**/*.py` files, follow these docstring guidelines:
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1. **Use reStructuredText format** for all docstrings.
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```python
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"""Short description of the function or class.
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Detailed description using reStructuredText format.
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Parameters
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----------
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param1 : type
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Description of param1
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param2 : type
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Description of param2
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Returns
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-------
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type
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Description of return value
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"""
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```
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2. **Keep the main description on the first line** after the opening `"""`.
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3. **Use NumPy docstyle** for parameter and return value documentation.
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### Doctest Guidelines
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For doctests in `src/**/*.py` files:
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1. **Use narrative descriptions** for test sections rather than inline comments:
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```python
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"""Example function.
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Examples
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--------
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Create an instance:
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>>> obj = ExampleClass()
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Verify a property:
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>>> obj.property
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'expected value'
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"""
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```
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2. **Move complex examples** to dedicated test files at `tests/examples/<path_to_module>/test_<example>.py` if they require elaborate setup or multiple steps.
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3. **Utilize pytest fixtures** via `doctest_namespace` for more complex test scenarios:
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```python
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"""Example with fixture.
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Examples
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--------
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>>> # doctest_namespace contains all pytest fixtures from conftest.py
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>>> example_fixture = getfixture('example_fixture')
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>>> example_fixture.method()
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'expected result'
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"""
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```
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4. **Keep doctests simple and focused** on demonstrating usage rather than comprehensive testing.
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5. **Add blank lines between test sections** for improved readability.
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6. **Test your doctests continuously** using pytest-watcher during development:
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```
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# Watch specific modules for doctest changes
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uv run ptw . --now --doctest-modules src/path/to/module.py
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```
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### Pytest Testing Guidelines
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1. **Use existing fixtures over mocks**:
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- Use fixtures from conftest.py instead of `monkeypatch` and `MagicMock` when available
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- For instance, if using libtmux, use provided fixtures: `server`, `session`, `window`, and `pane`
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- Document in test docstrings why standard fixtures weren't used for exceptional cases
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2. **Preferred pytest patterns**:
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- Use `tmp_path` (pathlib.Path) fixture over Python's `tempfile`
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- Use `monkeypatch` fixture over `unittest.mock`
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### Import Guidelines
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1. **Prefer namespace imports**:
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- Import modules and access attributes through the namespace instead of importing specific symbols
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- Example: Use `import enum` and access `enum.Enum` instead of `from enum import Enum`
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- This applies to standard library modules like `pathlib`, `os`, and similar cases
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2. **Standard aliases**:
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- For `typing` module, use `import typing as t`
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- Access typing elements via the namespace: `t.NamedTuple`, `t.TypedDict`, etc.
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- Note primitive types like unions can be done via `|` pipes and primitive types like list and dict can be done via `list` and `dict` directly.
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3. **Benefits of namespace imports**:
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- Improves code readability by making the source of symbols clear
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- Reduces potential naming conflicts
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- Makes import statements more maintainable

‎.cursor/rules/git-commits.mdc

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---
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description: git-commits: Git commit message standards and AI assistance
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globs: git-commits: Git commit message standards and AI assistance | *.git/* .gitignore .github/* CHANGELOG.md CHANGES.md
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alwaysApply: true
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---
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# Optimized Git Commit Standards
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## Commit Message Format
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```
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Component/File(commit-type[Subcomponent/method]): Concise description
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why: Explanation of necessity or impact.
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what:
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- Specific technical changes made
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- Focused on a single topic
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refs: #issue-number, breaking changes, or relevant links
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```
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## Component Patterns
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### General Code Changes
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```
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Component/File(feat[method]): Add feature
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Component/File(fix[method]): Fix bug
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Component/File(refactor[method]): Code restructure
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```
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### Packages and Dependencies
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| Language | Standard Packages | Dev Packages | Extras / Sub-packages |
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|------------|------------------------------------|-------------------------------|-----------------------------------------------|
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| General | `lang(deps):` | `lang(deps[dev]):` | |
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| Python | `py(deps):` | `py(deps[dev]):` | `py(deps[extra]):` |
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| JavaScript | `js(deps):` | `js(deps[dev]):` | `js(deps[subpackage]):`, `js(deps[dev{subpackage}]):` |
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#### Examples
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- `py(deps[dev]): Update pytest to v8.1`
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- `js(deps[ui-components]): Upgrade Button component package`
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- `js(deps[dev{linting}]): Add ESLint plugin`
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### Documentation Changes
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Prefix with `docs:`
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```
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docs(Component/File[Subcomponent/method]): Update API usage guide
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```
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### Test Changes
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Prefix with `tests:`
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```
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tests(Component/File[Subcomponent/method]): Add edge case tests
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```
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## Commit Types Summary
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- **feat**: New features or enhancements
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- **fix**: Bug fixes
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- **refactor**: Code restructuring without functional change
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- **docs**: Documentation updates
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- **chore**: Maintenance (dependencies, tooling, config)
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- **test**: Test-related updates
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- **style**: Code style and formatting
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## General Guidelines
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- Subject line: Maximum 50 characters
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- Body lines: Maximum 72 characters
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- Use imperative mood (e.g., "Add", "Fix", not "Added", "Fixed")
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- Limit to one topic per commit
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- Separate subject from body with a blank line
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- Mark breaking changes clearly: `BREAKING:`
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- Use `See also:` to provide external references
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## AI Assistance Workflow in Cursor
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- Stage changes with `git add`
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- Use `@commit` to generate initial commit message
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- Review and refine generated message
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- Ensure adherence to these standards
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## Good Commit Example
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```
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Pane(feat[capture_pane]): Add screenshot capture support
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why: Provide visual debugging capability
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what:
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- Implement capturePane method with image export
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- Integrate with existing Pane component logic
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- Document usage in Pane README
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refs: #485
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See also: https://example.com/docs/pane-capture
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```
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## Bad Commit Example
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```
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fixed stuff and improved some functions
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```
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These guidelines ensure clear, consistent commit histories, facilitating easier code review and maintenance.

‎.cursor/rules/notes-llms-txt.mdc

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---
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description: LLM-friendly markdown format for notes directories
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globs: notes/**/*.md,**/notes/**/*.md
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alwaysApply: true
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---
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# Instructions for Generating LLM-Optimized Markdown Content
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When creating or editing markdown files within the specified directories, adhere to the following guidelines to ensure the content is optimized for LLM understanding and efficient token usage:
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1. **Conciseness and Clarity**:
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- **Be Brief**: Present information succinctly, avoiding unnecessary elaboration.
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- **Use Clear Language**: Employ straightforward language to convey ideas effectively.
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2. **Structured Formatting**:
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- **Headings**: Utilize markdown headings (`#`, `##`, `###`, etc.) to organize content hierarchically.
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- **Lists**: Use bullet points (`-`) or numbered lists (`1.`, `2.`, etc.) to enumerate items clearly.
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- **Code Blocks**: Enclose code snippets within triple backticks (```) to distinguish them from regular text.
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3. **Semantic Elements**:
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- **Emphasis**: Use asterisks (`*`) or underscores (`_`) for italicizing text to denote emphasis.
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- **Strong Emphasis**: Use double asterisks (`**`) or double underscores (`__`) for bold text to highlight critical points.
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- **Inline Code**: Use single backticks (`) for inline code references.
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4. **Linking and References**:
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- **Hyperlinks**: Format links using `[Link Text](mdc:URL)` to provide direct access to external resources.
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- **References**: When citing sources, use footnotes or inline citations to maintain readability.
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5. **Avoid Redundancy**:
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- **Eliminate Repetition**: Ensure that information is not unnecessarily repeated within the document.
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- **Use Summaries**: Provide brief summaries where detailed explanations are not essential.
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6. **Standard Compliance**:
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- **llms.txt Conformance**: Structure the document in alignment with the `llms.txt` standard, which includes:
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- An H1 heading with the project or site name.
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- A blockquote summarizing the project's purpose.
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- Additional markdown sections providing detailed information.
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- H2-delimited sections containing lists of URLs for further details.
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By following these guidelines, the markdown files will be tailored for optimal LLM processing, ensuring that the content is both accessible and efficiently tokenized for AI applications.
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For more information on the `llms.txt` standard, refer to the official documentation: https://llmstxt.org/

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