majiayu000/claude-skill-registry - 22페이지

llm-evaluation

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.

원문 언어: 영어

llm-evaluation

Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.

원문 언어: 영어

llm-function-calling

Implementing function calling (tool use) with LLMs for structured outputs and external integrations.

원문 언어: 영어

llm-gateway-routing

LLM gateway and routing configuration using OpenRouter and LiteLLM. Invoke when: - Setting up multi-model access (OpenRouter, LiteLLM) - Configuring model fallbacks and reliability - Implementing cost-based or latency-based routing - A/B testing different…

원문 언어: 영어

llmintegration

LLM integration patterns for Claude, GPT, Gemini, and Ollama. Activate for AI API integration, prompt engineering, token management, extended thinking, and multi-model orchestration.

원문 언어: 영어

llm-integration

Guide for using LLM utilities in speedy_utils, including memoized OpenAI clients and chat format transformations.

원문 언어: 영어

llm-judge-patterns

Comprehensive guide to using LLMs as judges for automated evaluation including prompt patterns, calibration, bias reduction, and multi-judge ensembles

원문 언어: 영어

llm-local-deployment

Comprehensive guide for deploying LLMs locally using Ollama, vLLM, and llama.cpp. Local deployment offers privacy, cost control, and reduced latency compared to cloud APIs. This skill covers everythin

원문 언어: 영어

llm-ops

Local LLM health checks and cache management. Probe Ollama/vLLM/SGLang endpoints, clean model caches.

원문 언어: 영어

llm-pipeline

Pydantic-AI agents, RAG, embeddings for Pulse Radar knowledge extraction.

원문 언어: 영어

llm-streaming-response-handler

Build production LLM streaming UIs with Server-Sent Events, real-time token display, cancellation, error recovery. Handles OpenAI/Anthropic/Claude streaming APIs. Use for chatbots, AI assistants, real-time text generation. Activate on "LLM streaming", "SSE",…

원문 언어: 영어

llm-streaming

LLM streaming response patterns. Use when implementing real-time token streaming, Server-Sent Events for AI responses, or streaming with tool calls.

원문 언어: 영어

llm-token-optimization

See the main LLM Cost Optimization skill for comprehensive coverage of token economics and optimization strategies.

원문 언어: 영어

llm-txt-protocol

LLM Text Protocol provides standardized patterns for text-based interactions with language models. It encompasses prompt engineering, response formatting, and text processing patterns that ensure cons

원문 언어: 영어

llms-txt-support

Detect and use llms.txt files for LLM-optimized documentation. Use when checking if a site has LLM-ready docs before scraping.

원문 언어: 영어

local-llm-fine-tuning

Guides users through the process of preparing datasets and fine-tuning local Large Language Models (LLMs) using techniques like LoRA and QLoRA.

원문 언어: 영어

local-rag-search

Local Retrieval-Augmented Generation with vector search.

원문 언어: 영어

logfire

Use for Pydantic Logfire observability, tracing, and debugging. Query exceptions, spans, logs with SQL. View traces in Logfire UI. 4 tools for application monitoring and error analysis.

원문 언어: 영어

long-document-llm-pipeline

Use when processing documents over 50K characters through LLM APIs with section splitting and batch cost reduction.

원문 언어: 영어

longitudinal-drift-detector

Detect behavioral drift and alignment degradation over time.

원문 언어: 영어

looking-up-docs

Library documentation via Context7. Use for API references, code examples, framework docs.

원문 언어: 영어

lora

Parameter-efficient fine-tuning with Low-Rank Adaptation (LoRA). Use when fine-tuning large language models with limited GPU memory, creating task-specific adapters, or when you need to train multiple specialized models from a single base.

원문 언어: 영어

lora-ofl

Imported skill lora_ofl from anthropic

원문 언어: 영어

lumen-ai

Master AI-powered natural language data exploration with Lumen AI. Use this skill when building conversational data analysis interfaces, enabling natural language queries to databases, creating custom AI agents for domain-specific analytics, implementing RAG…

원문 언어: 영어

lyra

Transform vague inputs into precision-optimized AI prompts for Claude, ChatGPT, Gemini, or other LLMs. Use when user mentions "optimize prompt", "improve prompt", "lyra", "prompt engineering", or needs help crafting effective AI prompts.

원문 언어: 영어

mcp-local-rag

Provides score interpretation (< 0.3 good, > 0.5 skip), query optimization, and source naming for query_documents, ingest_file, ingest_data tools. Use this skill when working with RAG, searching documents, ingesting files, saving web content, or handling PDF,…

원문 언어: 영어

meta-analyst-agent

AI self-improvement analyst. Tracks AI agent mistakes, analyzes failure patterns, and proposes system improvements. Implements continuous learning loop for trading system enhancement.

metacognitive-self-mod

Analyze and improve the improvement process. Use for detecting regressions and meta-optimization.

원문 언어: 영어

minimax-mcp-usage

Optimal patterns for MiniMax MCP tools (web_search + understand_image)

원문 언어: 영어

moai-ai-nano-banana

Nano-Banana AI service integration for content generation, image creation, and AI-powered workflows. Use when integrating AI services for content creation.

원문 언어: 영어

model

Inspect or change Babysitter model-routing policy by phase.

원문 언어: 영어

model-ab-test

Use when validating model downgrades for skills or agents. Runs A/B comparison between current and proposed model, scores outputs against test criteria, produces verdict.

원문 언어: 영어

model-fallback

模型自动降级与故障切换。当主模型请求失败、超时、达到速率限制或配额耗尽时，自动切换到备用模型，确保服务连续性。支持多供应商、多优先级的智能模型选择，提供健康监控、自动重试和错误恢复机制。

원문 언어: 중국어

model-management

CLI commands to add, update, list, and deprecate AI models in the database. Triggers on "add model", "new model", "update model", "deprecate model", "model pricing", "model cli".

원문 언어: 영어

model-manager

Test, validate, and add new AI models to the eval suite. Use when user asks to add new models, test model access, check pricing, or update models.yml.

원문 언어: 영어

model-router

Route work to the cheapest model tier that can reliably complete it.

원문 언어: 영어

model-routing

Model selection strategy for subagents — haiku for exploration, sonnet for implementation, opus for architecture/security

원문 언어: 영어

model-switch

Switch the agent's model at runtime and restart. Use when the user asks to change models (e.g., "switch to kimi", "use opus", "go cheaper"), or when the agent decides a different model is better for the current workload.

원문 언어: 영어

model-usage

Step-by-step guidance for model usage.

원문 언어: 영어

model-usage

Use CodexBar CLI local cost usage to summarize per-model usage for Codex or Claude, including the current (most recent) model or a full model breakdown. Trigger when asked for model-level usage/cost data from codexbar, or when you need a scriptable per-model…

원문 언어: 영어