complex-tensor-handler
Handle complex-valued tensors in PyTorch for astronomical imaging applications. This skill should be used when working with Fourier transforms, phase/amplitude representations, and complex arithmetic in PRISM.
Handle complex-valued tensors in PyTorch for astronomical imaging applications. This skill should be used when working with Fourier transforms, phase/amplitude representations, and complex arithmetic in PRISM.
Detects unsafe spikes in training load and emits SafetyFlags with conservative adjustments.
Add comprehensive type hints to Python functions and methods, including PyTorch tensor types. This skill should be used when improving code quality through static type checking or when preparing code for mypy validation.
We-layer temporal processing for Zosia. Provides efficient time awareness, gap detection, and event tracking. Feeds felt experiences to the I-layer.
Techniques for model size reduction and inference acceleration using INT8 quantization, including Post-Training Quantization (PTQ) and Quantization Aware Training (QAT). (quantization, int8, qat, fbgemm, qnnpack, ptq, dequantize)
Model quantization for efficient inference and training. Covers precision types (FP32, FP16, BF16, INT8, INT4), BitsAndBytes configuration, memory estimation, and performance tradeoffs.
Guidelines for navigating and extending the AstralRenderer engine architecture
Structured and record arrays for C-interoperability, binary blob interpretation, and multi-field tabular data handling. Triggers: structured array, record array, compound dtype, multi-field index.
Your approach to handling ffi memory management. Use this skill when working on files where ffi memory management comes into play.
Rust expert for rainze_core PyO3 module. Use when working on Rust code, performance-critical components, or Python-Rust FFI.
Fixes linker 'undefined reference' errors by finding and adding the library dependency.
Runs the Operator's Edge loop (State, Proof, Gates + adaptation checks). Use for any coding task, debugging, refactor, or system change.
Lightweight 4-gate pre-dev workflow for small features (<2 days)
Guide for using the Neural DSP Quad Cortex device library in MMD files. Use when the user mentions Quad Cortex, QC, Neural DSP guitar processor, or needs help with preset loading, scene switching, expression control, or stomp automation for the Quad Cortex.
Generate optimized SQLite extensions in C, Rust, or Mojo
Use flynt to convert old Python string formatting to f-strings. Activate when: (1) Converting %-formatting to f-strings, (2) Converting .format() calls to f-strings, (3) Modernizing string concatenation to f-strings, (4) Improving code readability through f-string adoption, or (5) Batch-converting legacy Python codebases.
Add tensor shape validation and documentation to PyTorch code. This skill should be used when working with PyTorch models to ensure tensor shapes are correct and well-documented with inline comments.
Optimize and implement GPU kernels using CubeCL for memory-efficient LLM training
Use ComputationalPaths path tactics to automate common RwEq goals (path_simp/path_auto/path_normalize), and structure calc-based proofs cleanly.