Loading...
Loading...
Found 118 Skills
Expertise in architecting, implementing, reviewing, and debugging hierarchical matching systems. Use when working with: (1) Two-sided matching (Gale-Shapley, hospital-resident, student-school), (2) Assignment/optimization problems (Hungarian algorithm, bipartite matching), (3) Multi-level hierarchy matching (org charts, taxonomies, nested categories), (4) Entity resolution and record linkage across hierarchies. Triggers: debugging match quality issues, reviewing matching algorithms, translating business requirements into constraints, validating match correctness, architecting new matching systems, fixing unstable matches, resolving constraint violations, diagnosing preference misalignment.
Development guide for @rytass/storages base package (儲存基底套件開發指南). Use when creating new storage adapters (新增儲存 adapter), understanding base interfaces, or extending storage functionality. Covers StorageInterface, Storage class, file converters (檔案轉換器), hash algorithms (雜湊演算法), and implementation patterns.
Provides guidance for PyTorch-native agentic RL using torchforge, Meta's library separating infra from algorithms. Use when you want clean RL abstractions, easy algorithm experimentation, or scalable training with Monarch and TorchTitan.
Implement API rate limiting strategies using token bucket, sliding window, and fixed window algorithms. Use when protecting APIs from abuse, managing traffic, or implementing tiered rate limits.
Comprehensive guide for Qiskit - IBM's quantum computing framework. Use for quantum circuit design, quantum algorithms (VQE, QAOA, Grover, Shor), quantum simulation, noise modeling, quantum machine learning, and quantum chemistry calculations. Essential for quantum computing research and applications.
Vector database selection, embedding storage, approximate nearest neighbor (ANN) algorithms, and vector search optimization. Use when choosing vector stores, designing semantic search, or optimizing similarity search performance.
Implements API rate limiting using token bucket, sliding window, and Redis-based algorithms to protect against abuse. Use when securing public APIs, implementing tiered access, or preventing denial-of-service attacks.
Comprehensive quantum computing toolkit for building, optimizing, and executing quantum circuits. Use when working with quantum algorithms, simulations, or quantum hardware including (1) Building quantum circuits with gates and measurements, (2) Running quantum algorithms (VQE, QAOA, Grover), (3) Transpiling/optimizing circuits for hardware, (4) Executing on IBM Quantum or other providers, (5) Quantum chemistry and materials science, (6) Quantum machine learning, (7) Visualizing circuits and results, or (8) Any quantum computing development task.
Guidance for implementing Adaptive Rejection Sampling (ARS) algorithms. This skill should be used when implementing rejection sampling methods, log-concave distribution samplers, or statistical sampling algorithms that require envelope construction and adaptive updates. It provides procedural approaches, performance considerations, and verification strategies specific to ARS implementations.
Byzantine consensus voting for multi-agent decision making. Implements voting protocols, conflict resolution, and agreement algorithms for reaching consensus among multiple agents.
Best practices for implementing efficient business logic on mobile using appropriate algorithms and data structures.
Combining IoT sensor data using algorithms like Kalman filters for improved accuracy and reliability