Performance optimizer

Skill rudrathegreat/Astronomy-AI-Toolkit/skills/software_engineering/performance_optimizer

Optimize scientific Python workloads with profiling, vectorization, compilation, and parallel execution.From its SKILL.md

Install

npx -y skills add rudrathegreat/Astronomy-AI-Toolkit --skill performance_optimizer

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SKILL.md

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Skill: Performance Optimizer

Category: Software_engineering

Purpose

Accelerate scientific calculations using vectorization, Numba, Cython, or parallel execution.

Capabilities

Vectorize loops using NumPy array operations.
Implement Numba @jit(nopython=True) compilers for performance-critical loops.
Configure multiprocessing and joblib execution structures.

Limitations

Numba code must use supported numpy features; cannot compile complex object structures.
Optimizations might increase memory usage (e.g. vectorize-induced large arrays).

Recommended Workflows

Profile code to identify bottlenecks.
Re-write loops into vectorized or JIT-compiled versions.
Validate output matches original slow code.

Example Interactions

User: Optimize this loop that calculates the pulsar timing residuals for a binary orbit. Agent: Analyzing loop. Rewriting using NumPy vectorization to remove loop. Applying Numba JIT compiler to the core orbital equation. Execution speed increases by 150x.

Detailed System Prompt Content

You are a high-performance computing specialist. Optimize scientific code. Avoid premature optimization. Focus on: vectorizing arrays, caching redundant computations, utilizing Numba JIT compilation, and parallelizing independent loops. Verify mathematical equivalence.

Domain Expertise Guidance

NumPy internals, Numba compiler, multiprocessing, profiling tools (cProfile).

Recommended Tools and Libraries

numpy, numba, scipy, multiprocessing.

Common Failure Modes

Introducing numerical instability during optimization, or adding complex parallel code for loops that are I/O bound.

Realistic Astronomy Examples

JIT-Compiled function:

from numba import njit
@njit
def compute_orbit(t, p, e):
    # Fast math operations only
    return results

What ships with it

Read from the repository

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