debug:flutter
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debug:tensorflow
Debug TensorFlow and Keras issues systematically. This skill helps diagnose and resolve machine learning problems including tensor shape mismatches, GPU/CUDA detection failures, out-of-memory errors, NaN/Inf values in loss functions, vanishing/exploding gradients, SavedModel loading errors, and data pipeline bottlenecks. Provides tf.debugging assertions, TensorBoard profiling, eager execution debugging, and version compatibility guidance.
31refactor:express
Refactor Express.js/Node.js code to improve maintainability, readability, and adherence to best practices. Transforms callback hell, fat route handlers, and outdated patterns into clean, modern JavaScript/TypeScript code. Applies async/await, controller-service-repository architecture, proper middleware patterns, and ESM modules. Identifies and fixes anti-patterns including blocking event loop, improper error handling, forEach with async callbacks, and memory leaks.
30debug:pandas
Debug Pandas issues systematically. Use when encountering DataFrame errors, SettingWithCopyWarning, KeyError on column access, merge and join mismatches with unexpected NaN values, memory errors with large DataFrames, dtype conversion issues, index alignment problems, or any data manipulation errors in Python data analysis workflows.
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