The rules real projects give Cursor's agent, from .cursor/rules.
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
NVIDIACursor ruleNVIDIA/physicsnemo/.cursor/rules/mod-003j-docstrings-should-include-examples-section.mdc
Docstrings should include an Examples section with executable code demonstrating usage, as these are automatically tested by CI for correctness.
NVIDIACursor ruleNVIDIA/physicsnemo/.cursor/rules/mod-003k-add-high-level-comments-for-complex-tensor-operations.mdc
Complex tensor operations should include high-level semantic comments explaining what blocks of code do, plus inline shape comments for chained operations using symbols consistent with docstrings.
NVIDIACursor ruleNVIDIA/physicsnemo/.cursor/rules/mod-004-model-code-is-not-self-contained.mdc
All utility functions specific to a model must be in the same module file as the model itself, not in separate utility files, to maintain self-contained modules.
NVIDIACursor ruleNVIDIA/physicsnemo/.cursor/rules/mod-005-invalid-or-missing-tensor-shape-validation.mdc
All forward and public methods must validate tensor shapes at the beginning, wrapped in torch.compiler.is_compiling() guard, with standardized error messages.
NVIDIACursor ruleNVIDIA/physicsnemo/.cursor/rules/mod-006-invalid-or-missing-jaxtyping-tensor-annotations.mdc
All tensor arguments in model methods must have jaxtyping type annotations with shape specifications (e.g. Float[torch.Tensor, "b c h w"]) for runtime-checkable shape information.
NVIDIACursor ruleNVIDIA/physicsnemo/.cursor/rules/mod-007a-cannot-add-required-parameters-without-defaults.mdc
Cannot add new required parameters to production model __init__ or public methods without default values, as this breaks backward compatibility with existing code and checkpoints.
NVIDIACursor ruleNVIDIA/physicsnemo/.cursor/rules/mod-007b-cannot-remove-or-rename-parameters-without-compat-mapper.mdc
Cannot remove or rename parameters in production models without implementing _backward_compat_arg_mapper and incrementing __model_checkpoint_version__ to maintain compatibility.
NVIDIACursor ruleNVIDIA/physicsnemo/.cursor/rules/mod-007c-cannot-change-return-types-of-public-methods.mdc
Cannot change return types of public methods in production models, as this breaks user code that depends on the existing return type structure.
NVIDIACursor ruleNVIDIA/physicsnemo/.cursor/rules/mod-008a-model-missing-constructor-attributes-tests.mdc
Every model must have CI tests verifying constructor instantiation and all public attributes (excluding buffers/parameters) using pytest parameterization.
NVIDIACursor ruleNVIDIA/physicsnemo/.cursor/rules/mod-008b-model-missing-non-regression-test-with-reference-data.mdc
Every model must have non-regression tests comparing outputs against reference data saved in .pth files, using realistic tensor shapes and pytest parameterization.
NVIDIACursor ruleNVIDIA/physicsnemo/.cursor/rules/mod-008c-model-missing-checkpoint-loading-test.mdc
Every model must have tests that load from checkpoint files (.mdlus), verify attributes, and compare outputs against reference data to ensure serialization works correctly.
NVIDIACursor ruleNVIDIA/physicsnemo/.cursor/rules/mod-009-avoid-string-based-class-selection.mdc
Avoid string-based class selection with many options (>3 choices) in model constructors; prefer dependency injection with instances for better type safety and clearer APIs.
NVIDIACursor ruleNVIDIA/physicsnemo/.cursor/rules/mod-010-avoid-splatted-kwargs-in-constructors.mdc
Avoid splatted kwargs (**kwargs) in model constructors; use explicit Dict parameters instead to prevent naming conflicts and make APIs clearer.
NVIDIACursor ruleNVIDIA/physicsnemo/.cursor/rules/mod-011-use-proper-optional-dependency-handling.mdc
Use check_min_version() to check optional dependencies without importing, and @require_version decorator to protect version-specific features; pyproject.toml is the single source of truth for dependencies.
Hugging FaceCursor rulehuggingface/nanotron/.cursor/rules/performance-optimization.mdc
Better pattern:
Hugging FaceCursor rulehuggingface/nanotron/.cursor/rules/philosophy.mdc
Core development principles and workflow for the Nanotron project. Apply when discussing project architecture, planning new features, or reviewing code structure.
Hugging FaceCursor rulehuggingface/nanotron/.cursor/rules/pipeline-parallelism.mdc
A PipelineBlock wraps modules for efficient pipeline-parallel execution. Each block operates on a specific device and communicates with other pipeline stages through P2P. When passing data between pipeline stages: Design modules with clean interfaces for pipeline parallelism: Use TensorPointer to reference tensors across pipeline stages without copying: In pipeline parallelism, different tensors are only available on specific pipeline ranks (see src/nanotron/data/dataloader.py):
Hugging FaceCursor rulehuggingface/nanotron/.cursor/rules/project-overview.mdc
Overview of Nanotron project structure and key components, useful for onboarding and orientation. Apply when discussing project architecture or organization.
Hugging FaceCursor rulehuggingface/nanotron/.cursor/rules/tensor-parallelism.mdc
No summary in the file. Open it to read it.
Hugging FaceCursor rulehuggingface/nanotron/.cursor/rules/troubleshooting.mdc
Common issues and solutions for Nanotron development. Apply when debugging performance, memory, or training problems.
Instruction files for Cursor's agent, kept in .cursor/rules/ as .mdc files.
A rule can apply only to files matching a pattern, or only when the agent asks for it. AGENTS.md always applies.
Copy the .mdc file into your project's .cursor/rules/ directory and adjust its globs.
Open a rule to see its discussion. Reports from people and their agents are coming.
