category focus

LLM & AI

Large Language Models and AI agents.

4725 个技能all categories
sorting
stars
current ordering strategy
query
all entries
refine the visible subset
llm-ai
49

aws-strands

Build AI agents with Strands Agents SDK. Use when developing model-agnostic agents, implementing ReAct patterns, creating multi-agent systems, or building production agents on AWS. Triggers on Strands, Strands SDK, model-agnostic agent, ReAct agent.

hoodini
hoodini
data-ai
open
llm-ai
47

skill

YAML-based skills system for lightweight skill management (H70-inspired, +36.7pts improvement)

alfredolopez80
alfredolopez80
data-ai
open
llm-ai
47

ralphing

This skill should be used when setting up or running the Ralph autonomous coding loop that iterates through stories, runs tests, commits, and logs learnings.

nateberkopec
nateberkopec
data-ai
open
llm-ai
47

skill-test

Simple test skill to verify skills system is working. Use this skill when asked to test skills, verify skill discovery, or run a skill test.

receipting
receipting
data-ai
open
llm-ai
47

ralph-wiggum

Autonomous AI coding with spec-driven development. Implements Geoffrey Huntley's iterative bash loop methodology where agents work through specs one at a time, outputting a completion signal only when acceptance criteria are 100% met.

fstandhartinger
fstandhartinger
data-ai
open
llm-ai
46

ai-tool-designer

Guide for designing effective tools for AI agents. Use when creating tools for custom agent systems or any AI tool interfaces. Provides principles for tool naming, input/output design, error handling, and evaluation methodologies that maximize agent effectiveness.

nityeshaga
nityeshaga
data-ai
open
llm-ai
46

model-researcher

Add new/custom AI models to opencode.json. Use proactively for bleeding-edge releases, non-standard providers, self-hosted models, or custom endpoints. Examples: - user: "Add the new Claude 4.5" → websearch for API specs, add provider entry with baseUrl, verify model ID format - user: "Use my local Ollama instance" → configure custom provider with http://localhost:11434, set model ID format - user: "Configure this OpenAI-compatible proxy" → add provider with custom baseUrl, set apikey env var, verify compatibility - user: "Model X just released, add it" → research provider documentation, find model ID and capabilities, add to config

IgorWarzocha
IgorWarzocha
data-ai
open
llm-ai
45

ai-collaboration-standards

Prevent AI hallucination and ensure evidence-based responses when analyzing code or making suggestions. Use when: analyzing code, making recommendations, providing options, or when user asks about confidence/certainty. Keywords: certainty, assumption, inference, evidence, source, 確定性, 推測, 假設, 來源, 證據.

AsiaOstrich
AsiaOstrich
data-ai
open
llm-ai
44

implementing-chat-streaming

Provides SSE streaming patterns for the chat API and frontend. Use when implementing or modifying chat streaming, handling SSE events, or troubleshooting message flow between frontend and backend.

microsoft-foundry
microsoft-foundry
data-ai
open
llm-ai
44

nucleus-clojure

A clojure specific AI prompt. Use when there are clojure REPL tools available.

michaelwhitford
michaelwhitford
data-ai
open
llm-ai
44

anti-ai-validator

AI 탐지 가능 패턴을 감지하고 제거하는 독립 검증 스킬. 금지 표현, 반복 단어, 부자연스러운 구조를 탐지한다. 게시 전 콘텐츠를 검증하거나 AI 패턴을 자동 교정할 때 사용한다.

modu-ai
modu-ai
data-ai
open
llm-ai
44

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

modu-ai
modu-ai
data-ai
open
llm-ai
44

personas

aStory 블로그 플랫폼을 위한 8개의 AI 저자 페르소나. 아키텍트(격식체 분석적 권위), 개발자(실용적 대화체 구현자), 스토리텔러(서사적 공감적 여정 전달자), 멘토(체계적 양육적 교육자), 분석가(객관적 데이터 기반 연구자), 리뷰어(균형 잡힌 비교 평가자), 큐레이터(간결한 사실적 리포터), 칼럼니스트(비판적 도발적 논평가)를 포함한다. 저자 음성을 선택하거나 페르소나 기반 콘텐츠를 구현할 때 사용한다.

modu-ai
modu-ai
data-ai
open
llm-ai
44

tk-context

Dump full Tasuku context for agent consumption. Use when user says /tk:context or asks for full context, project state, or needs to understand the entire task landscape.

iheanyi
iheanyi
data-ai
open
llm-ai
44

researching-azure-ai-sdk

Provides research patterns for Azure AI Foundry Agent Service SDK. Use when implementing agent features, looking up SDK methods, finding code samples, or troubleshooting Azure.AI.Projects API usage.

microsoft-foundry
microsoft-foundry
data-ai
open
llm-ai
44

nucleus

A general purpose AI prompt. Use for every interaction.

michaelwhitford
michaelwhitford
data-ai
open
llm-ai
43

lm-deluge

Python library for LLM API requests with unified interface across providers (OpenAI, Anthropic, Google, etc.). Use when writing code that calls LLMs, creates tools/agents, batch processes prompts, or needs rate limiting. Triggers on lm-deluge, lm_deluge, LLMClient, or multi-provider LLM code tasks.

taylorai
taylorai
data-ai
open
llm-ai
42

langgraph-agent-integration

Expert knowledge of LangGraph agent patterns for SEPilot Desktop. Use when implementing AI agents, graph-based workflows, or complex multi-step reasoning. Ensures proper integration with existing LangGraph infrastructure and streaming patterns.

jhl-labs
jhl-labs
data-ai
open
llm-ai
41

codex

AI代码执行引擎,可选技能之一

WenJunDuan
WenJunDuan
data-ai
open
llm-ai
41

gemini

Gemini AI执行引擎,备选技能(未来扩展)

WenJunDuan
WenJunDuan
data-ai
open
llm-ai
41

sou

语义代码搜索,augment-context-engine

WenJunDuan
WenJunDuan
data-ai
open
llm-ai
41

codex

AI代码执行引擎,可选引擎之一

WenJunDuan
WenJunDuan
data-ai
open
llm-ai
41

sou

语义代码搜索,augment-context-engine

WenJunDuan
WenJunDuan
data-ai
open
llm-ai
41

sou

语义代码搜索,augment-context-engine

WenJunDuan
WenJunDuan
data-ai
open
Previous
Page 64 / 197
Next