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LLM & AI

Large Language Models and AI agents.

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llm-ai
0

context-pack-format

รูปแบบการจัดเตรียม context ให้กระชับ มีโครงสร้าง และใช้ token อย่างมีประสิทธิภาพ

AmnadTaowsoam
AmnadTaowsoam
data-ai
open
llm-ai
0

motion-planning

Generate production-quality Python code for robot motion planning algorithms that run in Pyodide (browser). Creates educational code for teaching path planning (A*, RRT), trajectory optimization, PID control, model predictive control (MPC), and whole-body control. Focuses on algorithm implementation, visualization, and educational clarity.

khanaleema
khanaleema
data-ai
open
llm-ai
0

context-initializer

Automatically invokes init-explorer agent when project context is empty or unknown.

leonj1
leonj1
data-ai
open
llm-ai
0

mcp-server

Model Context Protocol server exposing AI Factory tools to Claude Desktop

alexanderjamesmcleod
alexanderjamesmcleod
data-ai
open
llm-ai
0

langchain-agents

Building LLM agents with LangChain and LangGraph, covering tool-calling model initialization, state management, and observability with LangSmith. Triggers: langchain, langgraph, langsmith, agent-executor, chat-model-tools.

cuba6112
cuba6112
data-ai
open
llm-ai
0

daily-log

Daily log conventions for agent memory between sessions. Use when: "daily log", "today's note", "what happened today", "session start", "check context".

joint-hubs
joint-hubs
data-ai
open
llm-ai
0

whisper-lolo-transcription-jobs

Implement or adjust background transcription jobs for whisper-lolo. Use when wiring Inngest events, handling long-running jobs, chunking before transcription, persisting transcripts, or maintaining the TranscriptionProvider abstraction.

Lofp34
Lofp34
data-ai
open
llm-ai
0

ai-auditability

Implementing comprehensive logging, tracking, and audit trails for AI systems to ensure compliance and enable debugging.

AmnadTaowsoam
AmnadTaowsoam
data-ai
open
llm-ai
0

creating-meta-prompts

Claude間のパイプライン用に最適化されたメタプロンプトを作成します。リサーチ、計画、実行の各段階を含む多段階ワークフローを設計します。複雑なタスクの段階的処理、Claude間の連携、構造化されたワークフローが必要な場合に使用してください。

sekka
sekka
data-ai
open
llm-ai
0

synonyms

Generate synonyms for words or phrases. Use this skill when the user needs alternative words with similar meanings, wants to expand vocabulary, or seeks varied expressions for writing.

LaZzyMan
LaZzyMan
data-ai
open
llm-ai
0

embedding-pipeline

Implement reusable embedding functions using Gemini embedding models via LangChain with proper error handling and batching for sitemap-crawled content.

nadeemsangrasi
nadeemsangrasi
data-ai
open
llm-ai
0

rag-chatbot-enhancement

Improves the RAG (Retrieval-Augmented Generation) chatbot for the Physical AI & Humanoid Robotics textbook with strict grounding, citation requirements, and performance optimization.

Fatima367
Fatima367
data-ai
open
llm-ai
0

moai-foundation-core

MoAI-ADK's foundational principles - TRUST 5, SPEC-First TDD, delegation patterns, token optimization, progressive disclosure, modular architecture, agent catalog, command reference, and execution rules for building AI-powered development workflows

rdmptv
rdmptv
data-ai
open
llm-ai
0

strands-agent-architect

Design, build, deploy, and troubleshoot AI agents using AWS Strands Agents Framework (PRIMARY), Google ADK v1.0, A2A (Agent-to-Agent) protocols, and AWS Bedrock AgentCore. Use when creating new agents, implementing agent communication patterns, configuring AgentCore runtime, setting up RAG pipelines, integrating with Gemini 3.0, debugging deployment issues, or optimizing agent performance.

LPDigital-Agent
LPDigital-Agent
data-ai
open
llm-ai
0

memory

Unified four-tier memory system for AI agents. Tier 1 Semantic (Brain+Forgetful search), Tier 2 Episodic (session replay), Tier 3 Causal (decision patterns). Enables memory-first architecture per ADR-007.

loriensleafs
loriensleafs
data-ai
open
llm-ai
0

fabric-improve-prompt

Improve LLM prompts using prompt engineering best practices. Invoke when user wants to optimize prompts, improve slash commands, or apply prompt engineering.

theaj42
theaj42
data-ai
open
llm-ai
0

using-ltk

Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions

eyadsibai
eyadsibai
data-ai
open
llm-ai
0

using-claude-code-cli

Invoke Claude Code CLI from Python orchestrators and shell scripts. Use when asked to "spawn claude as subprocess", "automate claude cli", "run claude headless", "configure --allowedTools", "set up claude hooks", or "parallel claude invocation". Covers permissions, directory access (--add-dir), hooks, sandbox mode, and async patterns.

SpillwaveSolutions
SpillwaveSolutions
data-ai
open
llm-ai
0

phase-intent

Phase 1 of assist workflow - Classify intent as CREATE, REFACTOR, or VERIFY

chkim-su
chkim-su
data-ai
open
llm-ai
0

gemini-3-pro-api

Gemini 3 Pro API/SDK integration for text generation, reasoning, and chat. Covers setup, authentication, thinking levels, streaming, and production deployment. Use when working with Gemini 3 Pro API, Python SDK, Node.js SDK, text generation, chat applications, or advanced reasoning tasks.

adaptationio
adaptationio
data-ai
open
llm-ai
0

validating-openai-api-implementations

Use when reviewing OpenAI API usage, answering questions about OpenAI endpoints, or validating implementations against the official API specification. Provides expert knowledge on chat completions, embeddings, models, audio, assistants, batch processing, and moderations endpoints. Essential for code reviews involving OpenAI integrations and determining if features/parameters are part of the official API.

bbrowning
bbrowning
data-ai
open
llm-ai
0

skill-creator

효과적인 SKILL을 제작하기 위한 가이드입니다. 특화된 지식, 워크플로우 또는 도구 통합을 통해 Claude의 기능을 확장하는 새로운 SKILL을 생성하거나 기존 SKILL을 업데이트하려는 경우 이 SKILL을 사용하세요.

icartsh
icartsh
data-ai
open
llm-ai
0

rag-implementation

RAG (Retrieval Augmented Generation) implementation patterns including document chunking, embedding generation, vector database integration, semantic search, and RAG pipelines. Use when building RAG systems, implementing semantic search, creating knowledge bases, or when user mentions RAG, embeddings, vector database, retrieval, document chunking, or knowledge retrieval.

vanman2024
vanman2024
data-ai
open
llm-ai
0

ultrawork

Activate maximum performance mode with parallel agent orchestration for high-throughput task completion

mikev10
mikev10
data-ai
open
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