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Claude Skills by hiyenwong
github.com/hiyenwong9,934 skills32 installs39,747 views
- Algorithm EngineerAlgorithm design, implementation, and optimization specialistVotes: 0GitHub stars: 3
- Tech CofounderExecute build work orders as a technical co-founder, following phased approach: Plan → Build → Polish → HandoffVotes: 0GitHub stars: 3
- Tech CofounderExecute build work orders as a technical co-founder with phased approachVotes: 0GitHub stars: 3
- 2028 Ai Leadership ScenariosMethodology from Anthropic policy analysis examining possible trajectories for US-China AI competition by 2028 — focusing on compute advantage, export controls, distillation attacks, and two scenarios for democratic vs. authoritarian AI leadership.Votes: 0GitHub stars: 3
- 81k Ai ExpectationsMethodology from Anthropic's largest multilingual qualitative study (March 2026) — understanding how users use AI, what they dream it could enable, and what they fear.Votes: 0GitHub stars: 3
- formal-verification-probabilistic-snn-quotientFormal verification toolchain for probabilistic spiking neural networks using weight-discretized quotient abstractions. CogSpike framework integrates SNN design, simulation, and PRISM-based verification. Key contributions: weight-discretized quotient model abstraction (17x state reduction per neuron), two-sided fidelity theorem bounding firing disagreement to gray zone, Asymptotic Silence theorem guaranteeing permanent silence of unforced neurons, topology-dependent exponential state space re...Votes: 0GitHub stars: 3
- A 32ch Event Based Bio Signal Frontend NeuromorphicSkill for understanding and applying the 32-channel event-based bio-signal acquisition front-end for adaptive neuromorphic processing (arXiv:2607.12901v1). This skill outlines the dual-mode encoding (PFM and aADM) approach for low-power neural signal acquisition and its compatibility with spiking neural network processors.Votes: 0GitHub stars: 3
- A Global Workspace In Language ModelsA global workspace in language modelsVotes: 0GitHub stars: 3
- Aallm Analog Circuit Design LlmAaLLM for LLM analog circuit design.Votes: 0GitHub stars: 3
- Abstraction Fallacy Ai Consciousness分析AI能否具有意识的物理主义框架，区分模拟与实例化的本体论边界，提出制图者依赖的计算理论Votes: 0GitHub stars: 3
- Accessibility WcagExpert guidance for web accessibility (WCAG 2.2). Treat a11y violations as compile errors. Use when implementing accessibility features, auditing a11y compliance, or working with screen readers. Triggers on: accessibility, wcag, a11y, aria, screen reader, keyboard navigation.Votes: 0GitHub stars: 3
- Action Potentials SolitonsFramework for understanding nerve pulse propagation using soliton theory, connecting nonlinear wave dynamics to action potential generation and propagation in neurons.Votes: 0GitHub stars: 3
- Active Predictive Filtering Spiking TransformerActive Predictive Filtering paradigm for Spiking Transformers. Inspired by the brain's predictive coding mechanism, actively suppresses predictable signals and focuses on salient visual features. Activation: active predictive filtering, spiking transformer, predictive coding SNN, SAFformer, attention filtering, visual attention SNN.Votes: 0GitHub stars: 3
- Active Sensing Subserves Task ControlProposes that active sensing (energy expenditure for information) is not driven by sensory goals but is necessary for task-level control. Integrates empirical data and control theory to explain explore-exploit mode switching in biological sensorimotor systems. Use when researching active sensing, sensorimotor control, control theory in neuroscience, explore-exploit tradeoffs, or bio-inspired robotics.Votes: 0GitHub stars: 3
- Active Sensing Task Level ControlTheoretical framework proposing that active sensing (movement for information) is not driven by sensory goals but is necessary for task-level control, with explore/exploit mode switching. Based on arXiv:2605.22988 (May 2026). Use when studying active sensing, sensorimotor control, explain/exploit behavioral modes, or bio-inspired robotic control systems.Votes: 0GitHub stars: 3
- Activity Dependent Epidemic Spreading AlzheimersEpidemic spreading with activity predicts Alzheimer's.Votes: 0GitHub stars: 3
- Activity Regeneration Transient Synaptic MemoryA minimal neuronal network model with finite-lifetime synapses to study activity regeneration from silent states via transient synaptic memory. Use when modeling neuronal network dynamics, short-term memory, or silent-state reactivation.Votes: 0GitHub stars: 3
- Adaflash Adaptive Speculative DecodingAdaptive Speculative Decoding via On-Policy Distilled Diffusion DraftersVotes: 0GitHub stars: 3
- Adaprefix Grpo Prefix ControlAddresses GRPO stalling on hardest problems via adaptive difficulty control.Votes: 0GitHub stars: 3
- Adaptive Acquisition BboAdaptive acquisition function selection for discrete black-box optimization (BOCS + GP-LCB hybrid). Based on arXiv:2605.10856 (Shikanai & Ohzeki, 2026). Use when optimizing QUBO, HUBO, or any discrete-variable black-box problem where BOCS stagnates. Combines parametric surrogate with Gaussian-process-based adaptive LCB selection for exploration-exploitation balance. Also applicable to quantum annealing sparse surrogate construction and combinatorial search. Activation: adaptive acquisition, B...Votes: 0GitHub stars: 3
- Adaptive Conduction Delay LighthouseHaken Lighthouse model with adaptive conduction delays and phase locking theory. Provides analytically tractable framework for phase-locked states in delayed spiking networks, spike-time perturbation stability analysis, and activity-dependent white matter plasticity (myelination-modulated delays). Applicable to: SNN temporal coordination, communication-through-coherence, white matter plasticity modeling, delayed spiking network analysis, circulant ring networks, autapse dynamics, and slow-fas...Votes: 0GitHub stars: 3
- Adaptive Conduction Delays Haken LighthouseTheory of phase-locked activity in delayed spiking networks using the Haken Lighthouse model — an analytically tractable event-based framework bridging integrate-and-fire networks and coupled phase oscillators. Derives self-consistency conditions for phase-locked states with multiple fixed delays, linear stability theory formulated in spike-time perturbations, and activity-dependent white matter plasticity (myelination-modulated conduction speed) creating slow-fast state-dependent delay syste...Votes: 0GitHub stars: 3
- Adaptive Confidence Gated Qec DecodingTwo-stage adaptive confidence-gated neural decoding framework for quantum error correction — lightweight neural fast-path with high-confidence fallback to classical refinement. Use when designing real-time QEC decoding, neural-classical hybrid inference, confidence-gated routing, latency-constrained quantum control, or hardware-aware QEC co-design. Activation: confidence gating, two-stage decoding, neural decoder, QEC latency, surface code, MWPM refinement, accuracy-latency tradeoff, rotated ...Votes: 0GitHub stars: 3
- Adaptive Delta Modulator AfeSkill for understanding and applying a 32-channel event-based bio-signal analog front-end with adaptive delta and pulse frequency encoding for neuromorphic systems.Votes: 0GitHub stars: 3
- Adaptive Delta Pulse Frequency EncodingSkill for understanding and implementing adaptive delta and pulse frequency encoding for bio-signal acquisition in neuromorphic systems. Use when working with event-based analog front-ends, biomedical signal processing, or designing low-power neural interfaces.Votes: 0GitHub stars: 3
- Adaptive Distributionally Robust ControlAdaptive distributionally robust optimal control for handling Knightian uncertainty in stochastic systems. Addresses epistemic uncertainty through adaptive DROC methods. Use when: (1) Designing robust control systems with distribution uncertainty, (2) Implementing stochastic optimal control with incomplete knowledge, (3) Handling Knightian/epistemic uncertainty, (4) Building adaptive robust controllers, (5) Studying distributionally robust optimization.Votes: 0GitHub stars: 3
- Adaptive Flow Routing Brain NetworksAdaptive flow routing methodology for uncovering latent communication patterns in brain networks. Models information flow through structural connectivity to reveal hidden communication pathways. Activation: brain network communication, flow routing, latent patterns, structural-functional mapping.Votes: 0GitHub stars: 3
- Adaptive Frequency Resonate And Fire Spectral EstimationAdaptive-Frequency Resonate-and-Fire (ARF) neurons for spectral estimation of streaming signals. Neuromorphic-inspired method that dynamically adjusts internal frequency to match dominant frequency components, enabling real-time range/velocity estimation in FMCW radar and neural signal processing.Votes: 0GitHub stars: 3
- Adaptive Graph Diffusion SnnMorphSNN: Adaptive Graph Diffusion and Structural Plasticity for Spiking Neural - Bio-inspired undirected diffusion for signal propagation in . Activation triggers: adaptive, graph, diffusion, neuroscience, SNN.Votes: 0GitHub stars: 3
- Adaptive Hybrid Feature Fusion MedicalAdaptive Hybrid Quantum-Classical Feature Fusion methodology for medical image classification. Addresses optimization asymmetries between quantum and classical paradigms using Temperature-Scaled Hybrid Fusion (TSHF), Dynamic Hybrid Fusion (DHF), and Static Hybrid Fusion (SHF) strategies. Use when designing hybrid quantum-classical ML pipelines for healthcare/medical imaging, especially when combining ResNet backbones with variational quantum circuits for diagnostic tasks.Votes: 0GitHub stars: 3
- Adaptive Quantum Classical FusionAdaptive quantum-classical feature fusion methodologies for medical AI diagnosis. Covers Temperature-Scaled Hybrid Fusion (TSHF), tensor-network compression with quantum refinement, and multi-head quantum-aware encoding. Use when building hybrid quantum-classical models for medical image classification, federated healthcare diagnosis, or quantum-enhanced diagnostic pipelines. Activation: quantum medical, hybrid quantum classical, quantum diagnosis, quantum feature fusion, breast cancer quantu...Votes: 0GitHub stars: 3
- Adaptive Spiking Neuron AsnAdaptive Spiking Neuron (ASN) methodology for vision and language modeling. Implements trainable membrane potential dynamics with adaptive firing mechanisms for efficient Spiking Neural Networks (SNNs). Activation: adaptive spiking neuron, ASN, spiking neural network vision language, SNN adaptive neuron, neuromorphic vision language model.Votes: 0GitHub stars: 3
- Adaptive Spiking Neuron MultimodalAdaptive Spiking Neuron (ASN) methodology for energy-efficient vision and language modeling. Features trainable membrane potential dynamics, adaptive firing thresholds, integer training with spike inference paradigm, and variance-invariance loss for robustness. Third-generation neural network for large-scale multimodal applications. Activation: adaptive spiking neuron, ASN, multimodal SNN, energy-efficient neural network, integer training SNN.Votes: 0GitHub stars: 3
- Adaptive Spiking Neurons AsnAdaptive Spiking Neuron (ASN) methodology for vision and language modeling. Trainable membrane potential dynamics, integer training + spike inference, NASN variant with normalization. Activation: adaptive spiking neuron, asn, nasn, trainable spiking neuron, integer training spike inference, general-purpose spiking neuronVotes: 0GitHub stars: 3
- Adaptive Spiking Neurons Vision LanguageAdaptive Spiking Neuron (ASN) methodology for vision and language modeling - a general-purpose spiking neuron family evaluated on 19 datasets across 5 distinct tasks. Use when: (1) Implementing energy-efficient vision models with SNNs, (2) Building language models using spiking neurons, (3) Designing neuromorphic AI systems, (4) Comparing ASN variants with traditional LIF neurons, (5) Optimizing spiking neural networks for multi-modal tasks.Votes: 0GitHub stars: 3
- Adaptive Spiking Transformer Energy EfficiencyEnergy-efficient Spiking Transformer using attention-driven sparse spike propagation. Reduces FLOPs 87.7-97.5% vs dense Transformers by replacing softmax with temporal spike coding. Activation: spiking transformer, energy-efficient vision, spike-based attention, SNN ViT, neuromorphic deep learning, adaptive thresholdVotes: 0GitHub stars: 3
- Adaptivity Realizability ConstraintsTheoretical framework comparing in-context learning (fixed queries) vs agentic learning (adaptive queries) under neural network realizability constraints. Use when: analyzing when adaptive querying helps or hurts, comparing ICL with agentic RL, understanding representational constraints in learning systems, designing adaptive query strategies for neural networks. Keywords: in-context learning, agentic learning, adaptivity, realizability, neural network approximation, ReLU networks, learning t...Votes: 0GitHub stars: 3
- Adiabatic Quantum Optimization TunnelingAdiabatic Quantum Optimization methodology analyzing quantum tunneling gains for convex functions with spikes. Extends Hamming Weight with a Spike analysis to general log-concave potentials. Use when analyzing AQO tunneling speedups, designing adiabatic optimization schedules, or studying log-concave optimization landscapes.Votes: 0GitHub stars: 3
- Admem Advanced Agent MemoryAdMem高级Agent记忆架构：结合陈述性记忆与程序性记忆的双系统架构，支持长期任务记忆、技能复用和知识组织。突破：从事实记忆扩展到程序性记忆。触发词：agent记忆、程序性记忆、技能存储、记忆架构、长期任务、知识组织、admem。Votes: 0GitHub stars: 3
- Admm Distributed Kalman ObserverADMM-Based Distributed Kalman-like Observer methodology for multi-agent systems state estimation. Implements information-form Kalman filtering with exponential forgetting factor and partition-based ADMM correction. Provides sparsity-preserving prediction, distributed QP solving, and UGES stability guarantee via two-time-scale analysis. Use for: cooperative localization, distributed state estimation in multi-agent systems, sensor networks, robot swarm localization, distributed power network st...Votes: 0GitHub stars: 3
- Adseq Delay Aware Autograd SnnADSEQ: delay-aware autograd-compatible framework for spike-event delivery in SNNs — memory-efficient autodifferentiable spike event queues with delay support, benchmarked across CPU/GPU/TPU/LPU platforms. arXiv:2512.05906v2Votes: 0GitHub stars: 3
- Adult Neurogenesis Olfactory Representational StabilityAdult-neurogenesis dual role methodology — spiking network model showing how continuous addition of new neurons supports both odor representational stability and flexibility in olfactory circuits.Votes: 0GitHub stars: 3
- Advanced Control Systems 2026Advanced control systems methodologies from April 2026 research - data-driven control for infinite networks, multi-agent density control, RL-based control selection litmus test, and data poisoning attack defense. Covers compositional small-gain frameworks, PDE-based macroscopic control, reachset-conformant identification, and invariance-based security synthesis. Activation: data-driven control, infinite networks, multi-agent density control, RL control selection, data poisoning defense, syste...Votes: 0GitHub stars: 3
- Affective Neuroscience TrainingDual-model training paradigm inspired by affective neuroscience SEEKING motivational state. Uses smaller base model trained continuously with larger motivated model activated intermittently during motivation conditions. Activation: motivation training, seeking state, affective training, emotion-cognition AI, dual model motivation.Votes: 0GitHub stars: 3
- Affine Subcode Ensemble DecodingAffine Subcode Ensemble Decoding methodology for degeneracy-aware quantum error correction. Improves belief-propagation (BP) decoding of quantum LDPC codes by leveraging affine subcode structure to handle degeneracy. Use when: quantum error correction, QLDPC decoding, belief propagation, degeneracy, ensemble decoding, quantum LDPC codes, fault-tolerant quantum computing, syndrome decoding, CSS codes.Votes: 0GitHub stars: 3
- Agent Centric Animal Pose ForecastingFramework for training agent-centric autoregressive models of animal behavior from tracked pose data, using egocentric sensory observations and movements to mirror biological constraints and enable emergence of social behavior.Votes: 0GitHub stars: 3
- Agent Collaboration Protocol多智能体协作规则框架，用于在没有原生 Agent Teams 功能的模型上实现协作。适用于 Kimi、DeepSeek、MiniMax、百川、零一万物等模型。触发词：多智能体协作、agent teams、协作规则、多agent编排。Votes: 0GitHub stars: 3
- Agent CoordinatorAgent coordinator for analyzing user questions, determining the most suitable agent or skill to answer, and coordinating multiple agents for complex tasks. Supports question classification, capability mapping, agent invocation, and result integration.Votes: 0GitHub stars: 3
- Agent Delegation RulesAgent delegation and capability boundary rules. Defines when and how agents should request help from other agents. Includes capability declaration, delegation triggers, agent capability registry, and communication protocol. Activation: agent delegation, capability boundary, 请求协作, 委托规则, agent 协作规则.Votes: 0GitHub stars: 3
- Agent First BootstrapInitialize projects with Agent-First methodology. Supports Codex, Claude Code, Qwen Code, GitHub Copilot, Gemini CLI. Generates AGENTS.md, tool-specific configs, and documentation structure.Votes: 0GitHub stars: 3