技能目录

为 AI Agent 发现可复用技能。

按任务搜索真实的 GitHub 技能,并在使用前查看 Stars、信任、审计、分类和安装路径。

每个推荐都保留与其仓库、审计和安装路径的明确关联。

搜索结果: conversation

英文目录

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
信任
分类: coding-agents审计

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

177K
Stars
81/100
信任
分类: coding-agents审计

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
信任
分类: design-creative审计

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
信任
分类: devops审计

Export and Share your ChatGPT conversation history

2.6K
Stars
77/100
信任
分类: document-processing审计

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
信任
分类: agent-frameworks审计

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

262
Stars
77/100
信任
分类: coding-agents审计

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
信任
分类: document-processing审计

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

1.1K
Stars
76/100
信任
分类: support-automation审计

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

194
Stars
76/100
信任
分类: design-creative审计

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
信任
分类: research审计