Claude Skills by majiayu000

Cohesive Linear HoTT patterns for interaction entropy with diagram generation. Implements Schreiber's cohesive modalities (♯,♭,ʃ) and Riley's linear modality (♮) for quantum-classical bridging.

Task management and workflow patterns using liaison. Use when managing tasks, creating workflows, or working with task-driven automation.

LibAFL is a modular fuzzing library for building custom fuzzers. Use for advanced fuzzing needs, custom mutators, or non-standard fuzzing targets.

LibAFL is a modular fuzzing library for building custom fuzzers. Use for advanced fuzzing needs, custom mutators, or non-standard fuzzing targets.

libagent - Agent orchestration library for conversational AI. AgentMind class coordinates LLM completions, memory management, tool execution, and multi-turn conversations. AgentAction handles tool calls and action processing. Use for building chat agents, RAG pipelines, and AI assistants. Integrates with libmemory, librpc, and libllm

Upgrades .NET NuGet packages with breaking change handling

Coordinates project structure migration to Clean Architecture

Restructures React frontend from monolith to component-based architecture

Generates .NET Clean Architecture backend structure from entity definitions

Coordinates Docker, CI/CD, and environment configuration setup via auto-detection

Coordinates linters, pre-commit hooks, and test infrastructure setup

Configures ESLint, Prettier, Ruff, and .NET analyzers

Configures Husky, lint-staged, commitlint, and Python pre-commit

Creates test infrastructure with Vitest, xUnit, and pytest

Generates project-specific .claude/commands for Claude Code

Coordinates logging, error handling, CORS, health checks, and API docs

Configures structured logging (Serilog/.NET, structlog/Python)

Configures health check endpoints for Kubernetes readiness/liveness/startup

Orchestrates final verification - build, test, and container health checks

Builds all detected projects and verifies successful compilation

Executes all test suites and reports results with coverage

Run and interact with lnd Lightning Network daemon in Docker. Use for Lightning development, testing payment channels on regtest, managing lnd containers, and calling lnd RPC endpoints (getinfo, connect, open/close channels, pay/receive). Supports bitcoind, btcd, and neutrino backends.

Detects unsafe training load spikes (>20-30% week-over-week) and emits safety flags. Use in nightly background jobs or when reviewing weekly training volume with conservative adjustment recommendations.

Load architecture principles and core conventions for grounding work against project standards - simple context loading for all workflow stages

Configure and deploy load balancers (HAProxy, AWS ELB/ALB/NLB) for distributing traffic, session management, and high availability.

负载均衡配置

Comprehensive guide to load balancing algorithms, health checks, and high-availability patterns.

도메인/기능의 컨텍스트 빠른 파악. Use when: (1) 특정 도메인 이해 필요, (2) 기존 기능 수정 전 파악, (3) 세션 시작 시 컨텍스트 로드.

Load the full content of a previous Claude Code conversation into current context. Use when user asks to "load conversation <uuid>" or "show me conversation <uuid>" or references loading/viewing a past conversation by its ID.

Ultra-fast data discovery and loading skill for industrial finance datasets. Handles CSV, JSON, DuckDB, Parquet, and Feather with memory-efficient 2-step discovery and loading.

Reload memory context from files

Load, activate, and optionally install an AI skill from a .skill file. Use this skill when the user wants to load, activate, or use a skill file. The user can invoke this skill with slash command `/load-skill [ --install | -i ] SKILLFILE`, where SKILLFILE is the path to a .skill file.

Bootstrap skill loader for instance startup. Pulls fresh skills from plurigrid/asi and loads GF(3)-balanced startup triads. MUST run at beginning of every new instance.

Creates comprehensive load test plans with realistic scenarios, traffic models, k6 scripts, and success criteria. Use for "load testing", "performance testing", "capacity validation", or "stress testing".

Performance and load testing for API endpoints, payment pipeline, and concurrent user scenarios

| Atributo | Valor | |----------|-------| | **ID** | `sre-load-testing-performance` | | **Nivel** | 🔴 Avanzado | | **Versión** | 1.0.0 | | **Keywords** | `load-testing`, `performance`, `k6`, `jmeter`, `stress-testing`, `capacity-planning`, `benchmarking`, `rust` | | **Referencia** | [k6 Documentation](https://k6.io/docs/), [JMeter](https://jmeter.apache.org/) |

Create and manage K6 load tests for REST and GraphQL APIs. Use when creating load tests, writing K6 scripts, testing API performance, debugging load test failures, or setting up performance monitoring. Covers REST endpoints, GraphQL operations, data generation, IRI handling, configuration patterns, and performance troubleshooting.

Auto-activates when user mentions load test, performance test, stress test, k6, Artillery, benchmark, or scalability testing. Expert in designing and executing performance tests.

Imported skill load from langchain

Use when creating loading indicators, spinners, progress bars, or skeleton screens to communicate system status

Loads internal CausalPy example datasets. Use when the user needs example data or asks about available demos.

加载并预处理保险保单周度数据，支持智能周期检测、多周数据加载、数据验证和清洗。在开始任何保险数据分析任务时使用。

Design effective loading states, skeleton screens, and empty states that maintain user confidence. Use when content takes time to load, when showing progress, or handling empty data scenarios. Triggers on "loading state", "skeleton screen", "empty state", "spinner", "progress bar", "loading animation", "zero state".

Imported skill loading from langchain

Load pre-existing Seurat objects into the immunopipe pipeline instead of starting from raw count matrices via SampleInfo. This enables analysis on already processed single-cell RNA-seq data stored in Seurat R objects.

LobeHub CLI Toolbox - AI-powered command-line tools including lobe-commit (ChatGPT Git commits with Gitmoji), lobe-i18n (automated internationalization), and lobe-label (GitHub label management)

LobeTTS - High-quality TypeScript TTS/STT toolkit with EdgeSpeech, Microsoft, OpenAI engines, React hooks, audio visualization components, and both server and browser support

LobeVidol - Virtual idol creation platform with MMD dance support, VRM character customization, multi-provider LLM integration, and interactive 3D conversations

Access LobeChat for AI chat, knowledge base queries, and multi-model routing.

Delegate complex, multi-step codebase exploration to local Ollama models. Best for analysis, review, and understanding tasks that require reasoning across multiple files.