rust-tooling
Rust development tools including PyO3 bindings, sqlx database access, AGiXT SDK, and Rust-Python interop
Find the perfect capability for your agent.
Rust development tools including PyO3 bindings, sqlx database access, AGiXT SDK, and Rust-Python interop
Build or modify the Rust↔Python FFI using PyO3+maturin. Use for binding builds, smoke tests, and boundary validation workflow.
Low-risk Python performance optimization patterns with verified speedups
Parsing binary files with mixed endianness and variable-length records in Python.
Implement or modify a Rust function exposed to Python via PyO3 in eo-processor. Use when adding new compute kernels, fixing numerical/shape bugs in the Rust core, or wiring Rust functions into the Python module safely and consistently.
Эксперт Python разработки. Используй для Python best practices, async, typing и ecosystem.
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.
Rust expert for rainze_core PyO3 module. Use when working on Rust code, performance-critical components, or Python-Rust FFI.
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.
Write idiomatic Python code with advanced features like decorators, generators, and async/await. Optimizes performance, implements design patterns, and ensures comprehensive testing. Use for ML training, analytics tools, performance profiling, or any Python heavy lifting.
Convert Python loops to vectorized PyTorch tensor operations for performance. This skill should be used when optimizing computational bottlenecks in PyTorch code during Phase 4 performance optimization.
High-performance C development for data-intensive systems, with explicit emphasis on time-indexed / log-structured in-memory engines (e.g., Timelog-class designs). Use when building advanced data structures, algorithms, or libraries in C with focus on: memory efficiency, cache locality, immutable segment layouts, atomic publication, snapshot reads, SIMD/bit operations, and (future) Python bindings. Applies to: custom allocators, paged/segment storage, compression and bitmaps, index structures, single-writer/multi-reader concurrency patterns, background maintenance (flush/compaction), and performance-critical library development.
Astral社製ツール(uv, Ruff, ty)でPython開発環境を構築。プロジェクト作成、依存関係管理、コード品質改善、CI/CD設定時に使用。
Use when improving data loading, validation, and IO boundaries in Python research code.
Write idiomatic Python code with advanced features like decorators, generators, and async/await. Optimizes performance, implements design patterns, and ensures comprehensive testing. Use for ML training, analytics tools, performance profiling, or any Python heavy lifting.
Universal functions (ufuncs) for vectorization, including reductions, in-place operations, and custom Python-function wrapping. Triggers: ufunc, vectorize, reduce, accumulate, frompyfunc, in-place.
Diagnose and fix maturin build issues for PyO3 Python bindings. Use when encountering problems with maturin develop, missing Python exports, module registration errors, or type stub generation issues. Particularly useful when new PyO3 methods compile but don't appear in Python.
Implements concise, streamlined Python code matching exact architect specifications. Use when writing Python code, creating modules, or when the user asks to implement features in Python.