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LLM & AI

Large Language Models and AI agents.

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llm-ai
1

multi-agent-orchestration

Comprehensive guide to building multi-agent systems, agent collaboration patterns, and orchestration strategies (2025-2026 standards)

mdaashir
mdaashir
data-ai
open
llm-ai
1

few-shot-prompting

Example-based prompting techniques for in-context learning

pluginagentmarketplace
pluginagentmarketplace
data-ai
open
llm-ai
1

rag-expert

Expert in Retrieval-Augmented Generation systems - knowledge bases, chunking strategies, embedding optimization, and production RAG architectures

frankxai
frankxai
data-ai
open
llm-ai
1

jules

Scripts to communicate with Jules AI - An Autonomous Coding Agent

dappvibe
dappvibe
data-ai
open
llm-ai
1

doc-review

Review a single file or all files in a folder for data inconsistencies, reference errors, typos, and unclear terminology using parallel sub-agents

vladm3105
vladm3105
data-ai
open
llm-ai
1

remembering-conversations

ALWAYS USE THIS SKILL WHEN STARTING ANY KIND OF WORK, NO MATTER HOW TRIVIAL. You have no memory between sessions and will reinvent solutions or repeat past mistakes UNLESS YOU USE THIS SKILL. Gives you perfect recall of all your past conversations and projects.

Krosebrook
Krosebrook
data-ai
open
llm-ai
1

consulting-agents

Use when you need information you don't have, expertise outside your comfort zone, or fresh eyes on code - dispatches agents to research, advise, or review. NOT for implementation delegation (see subagent-driven-development).

snits
snits
data-ai
open
llm-ai
1

rag-exploitation

Attack techniques for Retrieval-Augmented Generation systems including knowledge base poisoning

pluginagentmarketplace
pluginagentmarketplace
data-ai
open
llm-ai
1

context-optimization

Apply optimization techniques to extend effective context capacity. Use when context limits constrain agent performance, when optimizing for cost or latency, or when implementing long-running agent systems.

SyntaxAsSpiral
SyntaxAsSpiral
data-ai
open
llm-ai
1

outsourcing-core

로컬 AI CLI에 작업을 아웃소싱할 때 자동 활성화. Use when the task is complex, requires specialized AI capabilities, or benefits from distributing work to different AI models

inchan
inchan
data-ai
open
llm-ai
1

rlm-process

Process large contexts using RLM (Recursive Language Model) patterns - chunking, filtering, recursive sub-calls

namesreallyblank
namesreallyblank
data-ai
open
llm-ai
1

writing-claude-skills

Create effective Agent Skills following the agentskills.io specification. Use when creating new skills, reviewing existing skills, or improving skill descriptions.

stephendolan
stephendolan
data-ai
open
llm-ai
1

fal-ai-image

Generate images using fal.ai nano-banana-pro model

artwist-polyakov
artwist-polyakov
data-ai
open
llm-ai
1

prompting

Prompt engineering standards and context engineering principles for AI agents based on Anthropic best practices. Covers clarity, structure, progressive discovery, and optimization for signal-to-noise ratio.

rafaelcalleja
rafaelcalleja
data-ai
open
llm-ai
1

claude4-prompt-engineer

Expert prompt engineering for Claude 4.x models (Sonnet 4.5, Opus 4.5, Haiku 4.5). Use when creating system prompts, optimizing existing prompts, designing agentic workflows, or improving prompt effectiveness. Triggers on requests like "optimize this prompt", "write a system prompt", "improve these instructions", "create an agent prompt", or any task involving prompt design for Claude.

pkarpovich
pkarpovich
data-ai
open
llm-ai
1

hf-jobs

This skill should be used when users want to run any workload on Hugging Face Jobs infrastructure. Covers UV scripts, Docker-based jobs, hardware selection, cost estimation, authentication with tokens, secrets management, timeout configuration, and result persistence. Designed for general-purpose compute workloads including data processing, inference, experiments, batch jobs, and any Python-based tasks. Should be invoked for tasks involving cloud compute, GPU workloads, or when users mention running jobs on Hugging Face infrastructure without local setup.

Nymbo
Nymbo
data-ai
open
llm-ai
1

architecting-memory

Implements progression from Vector RAG → GraphRAG → Temporal Knowledge Graphs. Use when designing persistent memory architectures for AI agent systems.

Git-Fg
Git-Fg
data-ai
open
llm-ai
1

lima-sandbox-testing

Run Claude Code integration tests in isolated Lima VM sandboxes. Use for E2E testing, hook validation, session survival tests, and any scenario requiring isolated Claude execution.

hgeldenhuys
hgeldenhuys
data-ai
open
llm-ai
1

maternal-chat-helper

Auxilia desenvolvimento do chat NathIA no projeto Nossa Maternidade. Conhece a arquitetura de agentes IA (MaternalChatAgent, EmotionAnalysisAgent), MCP servers (Supabase, GoogleAI, OpenAI, Anthropic), e prompts. Use ao trabalhar com chat, agentes IA, ou integracao Gemini.

LionGab
LionGab
data-ai
open
llm-ai
1

using-superpowers

Core skill activation protocol - establishes mandatory workflows for finding and applying skills before any task

a-ariff
a-ariff
data-ai
open
llm-ai
1

agent-memory

Implement agent memory - short-term, long-term, semantic storage, and retrieval

pluginagentmarketplace
pluginagentmarketplace
data-ai
open
llm-ai
1

memory-systems

Agent memory architecture including working, short-term, long-term, and temporal knowledge graphs.

5dlabs
5dlabs
data-ai
open
llm-ai
1

adhering-execution-standard

Defines behavioral standards for autonomous agents and enforces Uninterrupted Flow, Self-Verification, Auth-Gates, and Handoff protocols. PROACTIVELY Use when defining behavioral standards for autonomous agents or enforcing protocols. Internal-only reference for agent behavior.

Git-Fg
Git-Fg
data-ai
open
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