Build LLM applications with LlamaIndex. Create indexes, query engines, and data connectors. Use for RAG applications, document search, and knowledge base systems.
Build LLM applications with LlamaIndex. Create indexes, query engines, and data connectors. Use for RAG applications, document search, and knowledge base systems.
Build LLM applications with LlamaIndex. Create indexes, query engines, and data connectors. Use for RAG applications, document search, and knowledge base systems.
LlamaIndex implementation patterns with templates, scripts, and examples for building RAG applications.
LlamaIndex Wolfram Alpha tool for computational knowledge queries, math solving, scientific calculations, and agent integration.
Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models.
Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP vision encoder with Vicuna/LLaMA language models.
Describe images, read text, analyze charts, and answer questions about images using a compact vision-language model.
Expert LLC operations management for ID8Labs LLC (Florida single-member LLC). 9 specialized agents providing PhD-level expertise in compliance, tax strategy, asset protection, and…
Company formation and LLC setup by country — costs, timelines, requirements, and tax notes. Use when the user asks about forming an LLC, company incorporation, offshore company,…
用 Playwright 从深知晓、深知晓（深度溯源）、豆包、腾讯元宝、DeepSeek 和通义千问网页端无损采集完整回答、原始引用、引用标记和现场存证。用于 Fact-Check-X 的原始答案采集阶段，或任何需要比较多个 AI 网页回答与参考来源的任务。
LLMService API contract — the correct signatures for complete(), stream(), embed(), and response types.
Code calling LLM APIs — model output is untrusted input: defensive parsing, server-side schema validation, authorization never from model output, approval-gated writes, injection…
Production-ready patterns for building LLM applications, inspired by [Dify](https://github.com/langgenius/dify) and industry best practices.
Production-ready patterns for building LLM applications, inspired by [Dify](https://github.com/langgenius/dify) and industry best practices. — from majiayu000/claude-skill-registry
Building applications with Large Language Models - prompt engineering, RAG patterns, and LLM integration. Use for AI-powered features, chatbots, or LLM-based automation.
You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and AI-powered applications.
You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and AI-powered applications.
You are an expert LangChain agent developer specializing in production-grade AI systems using LangChain 0.1+ and LangGraph. — from Bhomesh/agent-harness
You are an expert LangChain agent developer specializing in production-grade AI systems using LangChain 0.1+ and LangGraph. — from majiayu000/claude-skill-registry
Building applications with Large Language Models - prompt engineering, RAG patterns, and LLM integration. Use for AI-powered features, chatbots, or LLM-based automation.
You are an expert prompt engineer specializing in crafting effective prompts for LLMs through advanced techniques including constitutional AI, chain-of-thought reasoning — from…
You are an expert prompt engineer specializing in crafting effective prompts for LLMs through advanced techniques including constitutional AI, chain-of-thought reasoning — from…
Detects common LLM coding agent artifacts in codebases. Identifies test quality issues, dead code, over-abstraction, and verbose LLM style patterns.
Execute programs on a compiled transformer stack machine where every instruction fetch and memory read is a parabolic attention head.
Design a reliable LLM-as-judge metric — a calibrated rubric, a clear scoring scale, and bias controls — and validate it against human labels before trusting it.
Using LLMs as automated evaluators for comparing chatbot responses with Chatbot Arena methodology
针对商业、法律等高风险长文档的长上下文推理优化器，提供五大核心能力. 分层分析策略（L0快速扫描→L1深度分析→L2聚焦深挖）按文档长度自动选择层级组合，控制token成本. 文档分块处理超长文档（超过50000字），按章节逻辑边界分割，逐块独立分析后全局检查跨块矛盾，解决上下文衰减问题.
本地 LLM Benchmark 工具。當使用者想測試、比較或選擇本地 Ollama 模型時觸發。流程：檢查 Ollama 安裝 → 依 VRAM 推薦模型大小 → 下載模型 → 跑 benchmark → 與現有模型比較 → 輸出 markdown 報告。
External LLM invocation. Triggered ONLY by @council,@probe,@crossref,@gpt,@gemini,@grok,@qwen.
Use when the user wants to chat with a non-Claude model (GPT-4o, Claude via Copilot, Kimi, GLM, MiniMax), get a second opinion from another LLM, compare model responses, or when…
Process textual and multimedia files with various LLM providers using the llm CLI. Supports both non-interactive and interactive modes with model selection, config persistence,…
Centralized AI-readable documentation repository with 245+ frameworks and tools. Use to find documentation, add new sources, or update existing docs.
Write effective LLM prompts, commands, and agent instructions. Goal-oriented over step-prescriptive. Role + Objective + Latitude pattern.
Configure RuVLLM local inference with model selection, MicroLoRA fine-tuning, and SONA adaptation
USE FOR RAG/LLM grounding. Returns pre-extracted web content (text, tables, code) optimized for LLMs. GET + POST. Adjust max_tokens/count based on complexity.
Audyt i optymalizacja treści pod AI/LLM (Answer Engine Optimization, GEO). Użyj gdy użytkownik pyta "czy strona jest widoczna w AI", "LLM-friendly", "optymalizacja pod AI", "czy…
Weekly LLM spend + unit-economics report — cost by stage (Haiku classifier vs Sonnet reply), by product (Solo 1:1 vs Family group), and per household, plotted against the price.
Orchestrate a configurable, multi-member CLI planning council (Codex, Claude Code, Gemini, OpenCode, or custom) to produce independent implementation plans, anonymize and…
Multi-LLM collaborative brainstorming and planning. Use when user explicitly requests consultation with multiple AI models (ChatGPT, Gemini, other LLMs) before presenting an…
Orchestrate multiple LLMs as a council, generating collective intelligence through peer review and chairman synthesis
Fetch LLM-optimized documentation from llms.txt endpoints for up-to-date API references
Optimize documentation for AI coding assistants and LLMs. Improves docs for Claude, Copilot, and other AI tools through c7score optimization, llms.txt generation, question-driven…
Extract structured data from construction documents using LLMs. Process RFIs, submittals, contracts, specifications. Convert unstructured PDFs to structured JSON/Excel.
Design LLM evaluation harnesses — benchmark design, model comparison, automated evals — with reproducible scoring, confidence intervals, and regression detection.
트리거: "LLM 평가", "eval 만들어줘", "모델 테스트", "프롬프트 평가", "LLM 품질 테스트" 수행: 태스크 분석 → 평가 기준 정의 → 테스트 케이스 생성 → 평가 코드 작성 → 리포트 형식 설계 출력: 평가 케이스 JSON + 평가 실행 코드 + 채점 기준 문서
Builds an evaluation harness for LLM/agent outputs using golden datasets, code-based scorers, and LLM-as-judge, run as a regression gate when prompts, models, or RAG configs…
Use when validating, benchmarking, or monitoring LLM application performance. Keywords: RAG evaluation, LLM-as-a-judge, CI/CD gating, trajectory scoring, test suites, prompt…
LLM-as-a-Judge evaluator via Langfuse. Scores traces on relevance, accuracy, hallucination, and helpfulness using GPT-5-nano as judge.
Use when adapting large language models to specific tasks, domains, or behaviors - covers LoRA, QLoRA, PEFT, instruction tuning, and full fine-tuning strategiesUse when ", "…
Fine-tune large language models efficiently using LoRA, QLoRA, and PEFT methods. Use for domain adaptation, instruction tuning, task-specific optimization, and parameter-efficient…
LLM fine-tuning expert for LoRA, QLoRA, dataset preparation, and training optimization
Recommend the right LLM agent framework for a given use case. Covers framework comparison (LangChain, LangGraph, CrewAI, AutoGen, Agno, Dify, n8n, Semantic Kernel, Haystack,…
Clarifies inputs, outputs, success criteria, decisions, and unresolved conditions so downstream agents can execute without guessing.
Implementing function calling (tool use) with LLMs for structured outputs and external integrations.
LLM-powered quality verification using prompt hooks. Validates commit messages, code patterns, and conventions using AI before allowing operations.
Layer input filtering, output validation, injection defense, and human escalation around LLM features.
Generates a structured handoff document so another LLM can pick up the current work with full context.
Finding and accessing AI/LLM model brand icons from lobe-icons library. Use when users need icon URLs, want to download brand logos for AI models/providers/applications ( — from…
Finding and accessing AI/LLM model brand icons from lobe-icons library. Use when users need icon URLs, want to download brand logos for AI models/providers/applications ( — from…