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5,088 skills indexed with the new KISS metadata standard.
The Custom Skill is used instead of the Home Skill because the Home skill assumes you have a OAuth service managing the IoT devices where the Custom Skill can just invoke a Lambda function with a custom intent mapping.
Goal
* 增译法
> 来源：https://annatarhe.github.io/2016/04/19/hack-js-code.html
Begin by copying one of the skilllevel entries:
Добро пожаловать, путник! \
- [Overview](#overview)
> ctrl + c & ctrl + v 的一章
工欲善其事，必先利其器。上篇文章快读搭建并运行一个App应用，但离工程化开发还是远不够的。调试程序是开发过程中必不可少的，高效的调试技能可以提高开发效率，也可以及时发现bug。
[APP从启动到显示流程](https://www.jianshu.com/p/08855d69c0bf)
The AEA gym skill demonstrates how a custom Reinforcement Learning agent, that uses OpenAI's <a href="https://www.gymlibrary.dev/" target="_blank">gym</a> library, may be embedded into an AEA skill and connection.
**Location**: `packages/skills/CalendarSkill/`
[wget][wget] 是一个命令行的下载工具。对于我们这些 Linux 用户来说，几乎每天都在使用它。下面为大家介绍几个有用的 wget 小技巧，可以让你更加高效而灵活的使用 wget。
Enables you to use skills and the skillbar and such.
generic skill
> 不定时更新
CLI forensic tool for Telegram Desktop artifact analysis. Extracts and analyzes data from `tdata` directory.
Current multi-agent frameworks—including LangGraph, CrewAI, and AutoGen's MagenticOne—suffer from **architectural stagnation**. While agents coordinate within conversations, they cannot evolve between runs. Poor performance requires manual developer intervention, creating a scalability bottleneck.
Macrograph is a visual programming platform with node-based graph interfaces. Supports both desktop (single-project) and server (multi-project) environments with real-time event processing and type-safe ID management.
for (aSlave in hudson.model.Hudson.instance.slaves) {
AI-powered agents appear on-chain, from trading bots to DAO participants, raising big questions.
发布时间：2024年10月22日
Agents are components that use reasoning to make decisions and take actions, designed to autonomously perform tasks or provide services with some degree of agency. LLM chains can only perform hardcoded sequences of actions, while agents use LLMs to reason through which actions to take, and in which