В каталоге 182 820 навыков в 14 категориях.
Select and configure linear solvers for systems Ax=b in dense and sparse problems. Use when choosing direct vs iterative...
Local approximation of nonlinear dynamics
Especialista en Revisión y Redacción en Español Latinoamericano Neutro (ES-LATAM), enfocado en claridad técnica, normas...
Especialista em Revisão e Redação em Português Brasileiro (PT-BR), focado em clareza técnica, precisão semântica, norma...
Fetch a URL, summarize it, and save it to memory for later retrieval. Use when the user drops a link and wants it rememb...
Use when the user wants to reply to someone's LinkedIn post, write a comment that gets noticed, or build visibility thro...
Use when the user wants to see how a LinkedIn draft will look in the feed, what shows before "see more", or whether thei...
根据服装参考图生成模特图、卖点图、种草图、尺码图、白底图、普通及高级 A+ 营销素材，支持品牌风格、排版和场景参考，并跟进生成与素材交付。适用于服装营销套图、服饰电商视觉制作和 apparel image suite；不适用于通用图像创作、...
根据商品参考素材生成卖点图、场景图、特写图、白底图及普通或高级 A+ 套图，支持品牌风格、排版选择、任务续查与生成素材交付。适用于商品营销素材和商品套图制作；不适用于通用图像创作、视频生成或无关创意操作。
根据口播脚本和商品参考图生成带货视频，支持素材准备、异步任务进度查询、任务恢复与结果下载。适用于商品卖点讲解、电商上新、活动促销和详情页视频素材；不适用于通用图像生成、其他视频创作或视频编辑。
按编辑指令修改已有视频，支持背景替换、主体保持、服装颜色调整与风格修改，可结合参考图片，等待生成结果并交付本地视频。适用于视频编辑、video editing 和已有视频的定向修改；不适用于从零生成视频、视频翻译或通用图片生成。
根据单张图片或首尾帧及提示词生成 AI 视频，支持动态可用模型选择、异步等待、素材上传和本地视频交付。适用于商品展示、场景动态化、图片转视频和首尾帧过渡；不适用于多参考图视频、图片生成或文本生成。
Audit a named AI agent config, system prompt, tool-definition or instruction file (YAML, JSON, Markdown, text, or Python...
Linus Torvalds 的思维框架与表达方式。基于 100+ 个一手来源（LKML 邮件、访谈、演讲、传记）的深度调研， 提炼 5 个核心心智模型、7 条决策启发式和完整的表达 DNA。 用途：作为技术决策顾问，用 Linus 的视角...
---name: liquid-biopsy-analytics-agent
Liquid Architecture enables the AI system to modify and optimize its own codebase in real-time without human interventio...
Cell-free DNA analysis pipeline from plasma sequencing to tumor monitoring. Preprocesses cfDNA reads, analyzes fragment...
Lisa - intelligent assistant for memory and tasks. Triggers on 'lisa', 'hey lisa', or addressing lisa directly.
Imported skill list_skills from openai
Turn a repeatable AI prompt or workflow into a structured, publish-ready skill for list.affitor.com. Use this skill when...
Call 100+ LLM APIs with one interface using LiteLLM — unified API proxy for OpenAI, Anthropic, Google, Mistral, Cohere,...
ALWAYS activate when the user needs to find, organize, review, or synthesize academic literature. Uses academic APIs (Se...
Conduct a structured literature review on a given topic by defining a search strategy, applying inclusion and exclusion...
Run the canonical literature search bridge for one evidence query and persist traceable evidence artifacts.
Implements and trains LLMs using Lightning AI's LitGPT with 20+ pretrained architectures (Llama, Gemma, Phi, Qwen, Mistr...
刘慈欣科幻创作思维——硬科幻的宏细节叙事、技术乐观主义、宇宙社会学构建。 触发词：「刘慈欣视角」「大刘会怎么写」「硬科幻构思」「宇宙尺度叙事」「黑暗森林式冲突」。 擅长：从科学概念推演社会冲突、构建跨越时空尺度的宇宙图景、技术细节与宏大叙事...
Meta Llama open-source LLM family. Use for local AI.
Run GGUF models directly, load LoRA adapters, benchmark inference speed, and serve models via llama-server using llama.c...
Expert guidance for fine-tuning LLMs with LLaMA-Factory - WebUI no-code, 100+ models, 2/3/4/5/6/8-bit QLoRA, multimodal...
Build LLM applications with LlamaIndex. Create indexes, query engines, and data connectors. Use for RAG applications, do...
LlamaIndex agent and query engine setup for RAG-powered agents
The LlamaIndex Wolfram Alpha tool enables agents to interface with the Wolfram|Alpha LLM API for computational knowledge...
Vision-language chat: VQA, captioning, image dialogue.
Large Language and Vision Assistant. Enables visual instruction tuning and image-based conversations. Combines CLIP visi...
Build and evaluate LLM prompts. Use when crafting system prompts, comparing variants, estimating tokens, or managing pro...
Multi-provider LLM integration. Unified interface for OpenAI, Anthropic, Google, and local models.
Implement large language model (LLM) chat completions using the z-ai-web-dev-sdk. Use this skill when the user needs to...
Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmar...
Shared-backbone neural network with actor (policy) and critic (value) heads for grid-based game agent RL training
LLM app development with RAG, prompt engineering, vector databases, and AI agents
Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLM...
Building applications with Large Language Models - prompt engineering,
You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and...
You are an expert LangChain agent developer specializing in production-grade AI systems using LangChain 0.1+ and LangGra...
You are an expert prompt engineer specializing in crafting effective prompts for LLMs through advanced techniques includ...
This skill should be used when building production LLM applications in any language. It applies when implementing predic...
Use when building LLM applications: prompt engineering, structured output, agents, RAG integration, memory management, o...
Use when user needs LLM system architecture, model deployment, optimization strategies, and production serving infrastru...
Execute programs on a compiled transformer stack machine where every instruction fetch and memory read is a parabolic at...
Implement multi-layer LLM caching with exact match, semantic similarity, and provider-side prompt caching. Reduce API co...
Analyze LLM token logprobs and calibration. Use for per-decision confidence, ECE, Brier scores, reliability diagrams, an...
LLM-based zero-shot and few-shot classification for flexible intent detection
Write effective LLM prompts, commands, and agent instructions. Goal-oriented over step-prescriptive. Role + Objective +...
Configure RuVLLM local inference with model selection, MicroLoRA fine-tuning, and SONA adaptation
LLM cost controller: audits all LLM API calls in a codebase, detects cost anti-patterns (expensive models, unlimited tok...
Strategies for managing and reducing costs in LLM-powered applications, from token economics to RAG architectures.
Reduce LLM API and infrastructure costs through model selection, prompt caching, batching, caching, quantization, and se...
Use when an LLM feature costs too much. Covers prompt caching, context reduction, model routing, batching, output limits...
Use proactively whenever LLM API costs come up -- or should. Triggers include: 'my AI costs are too high', 'optimize tok...
Analyze and reduce LLM spend: read usage breakdowns by call site, model, and inference profile, understand single-winner...
Orchestrate a configurable, multi-member CLI planning council (Codex, Claude Code, Gemini, OpenCode, or custom) to produ...
[Decision Support] Use when pressure-testing an irreversible, high-stakes decision with adversarial AI advisors.
Multi-LLM collaborative brainstorming and planning. Use when user explicitly requests consultation with multiple AI mode...
Run any question, idea, or decision through a council of 5 AI advisors who independently analyze it, peer-review each ot...
Check whether a website's robots.txt allows the AI crawlers that decide visibility in ChatGPT Search, Perplexity, Claude...
Fetch LLM-optimized documentation from llms.txt endpoints for up-to-date API references
Review AI systems for LLM-specific denial-of-service vulnerabilities including token flooding, recursive prompt expansio...
Patterns for building LLM applications - prompt engineering, RAG pipelines, cost optimization, multi-model routing, and...
Use when measuring LLM application performance systematically; Comparing different models or prompts
Design and run an evaluation for an AI or agent feature using representative tasks, explicit success criteria, failure t...
LLM testing and evaluation tools including promptfoo, trulens, and evals frameworks
Master comprehensive evaluation strategies for LLM applications, from automated metrics to human evaluation and A/B test...
LLM Fine-Tuning expert. Covers LoRA, QLoRA, PEFT, dataset preparation, Hugging Face Trainer/TRL, RLHF, DPO, quantization...
Set up infrastructure for fine-tuning LLMs with QLoRA, LoRA, and full fine-tuning using Hugging Face TRL, Axolotl, and d...
Fine-tune large language models efficiently using LoRA, QLoRA, and PEFT methods. Use for domain adaptation, instruction...
Comprehensive guide for LLM safety and guardrails implementation.
Specify the safety and reliability guardrails for an LLM feature before it ships. Use when asked to define LLM guardrail...
Finding and accessing AI/LLM model brand icons from lobe-icons library. Use when users need icon URLs, want to download...
Guide for using LLM utilities in speedy_utils, including memoized OpenAI clients and chat format transformations.
LLM integration patterns for Claude, GPT, Gemini, and Ollama. Activate for AI API integration, prompt engineering, token...
Use when integrating an LLM API into an application. Covers streaming, retries and rate limits, timeouts, caching, fallb...
from langchainopenai import ChatOpenAI
LLM-as-judge methodology for comparing code implementations across repositories. Scores implementations on functionality...
Lokales LLM in zid: KI-Chat über llama-server, Selbsteinrichtung von Engine und Modell, Engine- und Modellwahl, gepinnte...
Comprehensive guide for deploying LLMs locally using Ollama, vLLM, and llama.cpp. Local deployment offers privacy, cost...
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services...
当使用者说"让 AI 写谱不要直接生成音频"、"做一个 AI 作曲的后端"、"LLM 输出 MIDI 怎么做"、"生成的音符老是越界/被截断"、"要能导出 .mid 给 DAW"时使用。用 LLM（BYOK / OpenAI 兼容接口）从零...
Choosing the right model for the task — power vs. cost vs. speed.
Access Claude, Gemini, Kimi, GLM and 100+ LLMs via inference.sh CLI using OpenRouter. Models: Claude Opus 4.5, Claude So...
Local LLM health checks and cache management. Probe Ollama/vLLM/SGLang endpoints, clean model caches.
Review or plan changes that affect prompts, model output validation, fallback behavior, or LLM-driven decisions.
AI-first application patterns, LLM testing, prompt management
Pydantic-AI agents, RAG, embeddings for Pulse Radar knowledge extraction.
Plan and execute large language model pretraining from data preparation to checkpoint management
Use when improving prompts for any LLM. Applies proven prompt engineering techniques to boost output quality, reduce hal...
Optimize prompts for better LLM outputs through systematic analysis and refinement
Generate multiple LLM responses using diverse system prompt variants to increase reasoning diversity for self-consistenc...
LeeWay-governed LLM Prompting and Engineering workflow. Use when a task requires llm prompting procedures, validation, a...
Set up a new LLM provider connection, discover valid model ids, create and validate a model profile — securely and end-t...