Skill 디렉토리

AI Agent를 위한 재사용 가능한 Skill을 찾으세요.

작업으로 실제 GitHub Skill을 검색하고 사용 전에 Stars, 신뢰, 감사, 카테고리, 설치 경로를 확인하세요.

모든 추천은 리포지토리, 감사, 설치 경로와 명확하게 연결됩니다.

검색 결과: conversation

영문 디렉토리

Turn the current conversation and codebase context into a structured implementation spec, then publish it to the configured project issue tracker.

165K
Stars
81/100
신뢰
카테고리: coding-agents감사

Break a plan, spec, or conversation into independently actionable tracer-bullet tickets with explicit blocking relationships.

177K
Stars
81/100
신뢰
카테고리: coding-agents감사

Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces.

18K
Stars
87/100
신뢰
카테고리: design-creative감사

Errbot is a chatbot, a daemon that connects to your favorite chat service and bring your tools and some fun into the conversation.

3.3K
Stars
85/100
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카테고리: devops감사

Export and Share your ChatGPT conversation history

2.6K
Stars
77/100
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카테고리: document-processing감사

Voice AI SDK is a reusable Android library that gives any app a full voice-driven AI conversation pipeline in minutes. Voice Assistant + Android Voide AI + SDK + MVVM + Kotlin

2.6K
Stars
76/100
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카테고리: agent-frameworks감사

A plugin for OpenCode that provides dynamic skill loading, context injection, and other tools for using reusable AI agent skills.

262
Stars
77/100
신뢰
카테고리: coding-agents감사

Claude Code plugin that generates individualized knowledge systems from conversation. You describe how you think and work, have a conversation and get a complete second brain as markdown files you own.

3.5K
Stars
77/100
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카테고리: document-processing감사

MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversation

1.1K
Stars
76/100
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카테고리: support-automation감사

Installable agent skills for creating and managing reversible themes for AI desktop apps like Codex and WorkBuddy.

194
Stars
76/100
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카테고리: design-creative감사

Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.

34K
Stars
77/100
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카테고리: research감사