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[REQUIRED] Comprehensive description of what this skill does and when to use it. Include: (1) Primary functionality, (2) Specific use cases, (3) Security operations context. Must include specific "Use when:" clause for skill discovery. Example: "SAST vulnerability analysis and remediation guidance using Semgrep and industry security standards. Use when: (1) Analyzing static code for security vulnerabilities, (2) Prioritizing security findings by severity, (3) Providing secure coding remediation, (4) Integrating security checks into CI/CD pipelines." Maximum 1024 characters.
Use when pricing options, calculating Greeks, implementing exotic derivatives, or building pricing engines - covers Black-Scholes, binomial trees, Monte Carlo, and QuantLib integrationUse when ", " mentioned.
A meta skill that teaches AI agents how to discover, install, and use skills from the findskill.md ecosystem. Use when you need to extend capabilities by finding specialized skills, when a user asks to perform tasks that would benefit from specialized skills, or when explicitly asked to find or install skills.
Refactor React and TypeScript code to improve maintainability, readability, and performance. This skill transforms complex React components into clean, well-structured code following modern React 19 patterns. It addresses component bloat, prop drilling, unnecessary re-renders, and improper hook usage. Leverages React 19 features including the React Compiler for automatic memoization, Actions for form handling, useOptimistic for immediate UI feedback, the use() hook for async data, and Server Components for optimal performance.
Refactor Pandas code to improve maintainability, readability, and performance. Identifies and fixes loops/.iterrows() that should be vectorized, overuse of .apply() where vectorized alternatives exist, chained indexing patterns, inplace=True usage, inefficient dtypes, missing method chaining opportunities, complex filters, merge operations without validation, and SettingWithCopyWarning patterns. Applies Pandas 2.0+ features including PyArrow backend, Copy-on-Write, vectorized operations, method chaining, .query()/.eval(), optimized dtypes, and pipeline patterns.
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.
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.
Expert guidance for building smart contracts on Stellar using the Soroban Rust SDK. Use this skill when working with Soroban smart contracts for tasks including (1) creating new contracts with [contract] and [contractimpl] attributes, (2) implementing storage with Persistent, Temporary, or Instance storage types, (3) working with auth contexts and authorization, (4) handling tokens and Stellar Asset Contracts, (5) writing tests with testutils, (6) deploying contracts, (7) working with events and logging, (8) using crypto functions, (9) debugging contract errors, (10) security best practices and vulnerability prevention, (11) avoiding common security pitfalls like missing authorization, integer overflow, or reinitialization attacks.
Refactor Nuxt.js/Vue code to improve maintainability, readability, and adherence to best practices. Identifies and fixes DRY violations, oversized components, deep nesting, SRP violations, data fetching anti-patterns with useFetch/useAsyncData/$fetch, poor composable organization, and mixed business/presentation logic. Applies Nuxt 3 patterns including auto-imports, proper data fetching, single-responsibility composables, TypeScript integration, runtime config, Nitro server routes, Nuxt Layers, middleware patterns, Pinia state management, and performance optimizations.
Refactor Scikit-learn and machine learning code to improve maintainability, reproducibility, and adherence to best practices. This skill transforms working ML code into production-ready pipelines that prevent data leakage and ensure reproducible results. It addresses preprocessing outside pipelines, missing random_state parameters, improper cross-validation, and custom transformers not following sklearn API conventions. Implements proper Pipeline and ColumnTransformer patterns, systematic hyperparameter tuning, and appropriate evaluation metrics.
Expert backend development covering API design, database architecture, microservices, message queues, caching, and system scalability.
Refactor Angular code to improve maintainability, readability, and adherence to best practices. Transforms large components, nested subscriptions, and outdated patterns into clean, modern Angular code. Applies signals, standalone components, OnPush change detection, proper RxJS patterns, and Angular Style Guide conventions. Identifies and fixes memory leaks, function calls in templates, fat components, and missing lazy loading.