← Back to Skills Marketplace
37
Downloads
0
Stars
1
Active Installs
1
Versions
Install in OpenClaw
/install auto-llm-4891
Description
Provides a comprehensive 2026 Bilibili tutorial series on building AI agents with large language models, covering from basics to advanced practical development.
README (SKILL.md)
Skill: auto_llm_4891\r
【2026最新】B站最全最细的AI Agent智能体搭建教程，从入门到实战！手把手教你快速打造自己的专属智能体，一次性搞懂AI大模型智能体开发，学完薪资翻倍！\r
功能范围\r
- 【2026最新】B站最全最细的AI Agent智能体搭建教程，从入门到实战！手把手教你快速打造自己的专属智能体，一次性搞懂AI大模型智能体开发，学完薪资翻倍！\r
- Deep-generated from NVIDIA NIM analysis\r
触发场景\r
- 用户说"llm/agent"\r Base directory: file:///C:\Users\pc.config\opencode\skills\auto_llm_4891\r \r
B站学习\r
学习时间: 2026-06-01 21:01\r \r
- 炮老师的小课堂: Comfyui本地LLM大语言模型润色提示词，让你灵感源源不断，出图美的冒泡~\r
- ABexit: 搭建自己的语音对话大模型 | ASR+LLM+TTS串联\r
- 锋芒AI: OmniRoute：一个接口接通 100+ LLM，配额用尽也不断线\r \r
B站学习 (第1轮)\r
学习时间: 2026-06-02 09:20\r \r
- 锋芒AI: OmniRoute：一个接口接通 100+ LLM，配额用尽也不断线\r https://www.bilibili.com/video/BV1W9DUBMEVs\r
- 炮老师的小课堂: Comfyui本地LLM大语言模型润色提示词，让你灵感源源不断，出图美的冒泡~\r https://www.bilibili.com/video/BV1e8TSzhEgT\r
- 不归牛顿管的熊猫: 全面解析LLM MoE专家并行EP all-to-all算子(小白也能看懂)\r https://www.bilibili.com/video/BV1W314BfEHr\r \r
B站学习 (第2轮)\r
学习时间: 2026-06-02 09:33\r \r
- 锋芒AI: OmniRoute：一个接口接通 100+ LLM，配额用尽也不断线\r https://www.bilibili.com/video/BV1W9DUBMEVs\r
- 炮老师的小课堂: Comfyui本地LLM大语言模型润色提示词，让你灵感源源不断，出图美的冒泡~\r https://www.bilibili.com/video/BV1e8TSzhEgT\r
- 不归牛顿管的熊猫: 全面解析LLM MoE专家并行EP all-to-all算子(小白也能看懂)\r https://www.bilibili.com/video/BV1W314BfEHr\r
Usage Guidance
Installing this skill appears reasonable if you want the tutorial links and simple sample code. Do not treat the Python helper as production agent code; if you plan to run or reuse it, remove the hard-coded sys.path insertion first.
Capability Assessment
Purpose & Capability
The stated purpose is AI-agent learning content and Bilibili resources; the included Python helper is only a simple canned-response chatbot, so capability is limited but not harmful.
Instruction Scope
Runtime instructions are narrow: trigger on llm/agent and present learning resources. They do not request private data access, credential use, system changes, or background work.
Install Mechanism
No dependencies, install scripts, package managers, or automatic setup actions are present in the artifacts.
Credentials
auto_llm_4891.py prepends a hard-coded Windows path to sys.path, which is unnecessary for its observed behavior and could make imports depend on local machine state if executed.
Persistence & Privilege
No persistence, privilege escalation, destructive file operations, credential handling, network exfiltration, or long-running/background behavior was found.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install auto-llm-4891 - After installation, invoke the skill by name or use
/auto-llm-4891 - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
auto-llm-4891 v1.0.0 changelog:
- Initial release: Comprehensive AI Agent development tutorial based on 2026 Bilibili content.
- Covers building, customizing, and deploying AI large model (LLM) agents, from beginner to advanced.
- Includes curated B站 (Bilibili) learning resources and guides, featuring hands-on videos and insightful analysis.
- Designed to be triggered by users mentioning "llm/agent".
Metadata
Frequently Asked Questions
What is Auto Llm 4891?
Provides a comprehensive 2026 Bilibili tutorial series on building AI agents with large language models, covering from basics to advanced practical development. It is an AI Agent Skill for Claude Code / OpenClaw, with 37 downloads so far.
How do I install Auto Llm 4891?
Run "/install auto-llm-4891" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Auto Llm 4891 free?
Yes, Auto Llm 4891 is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Auto Llm 4891 support?
Auto Llm 4891 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Auto Llm 4891?
It is built and maintained by 534422530 (@534422530); the current version is v1.0.0.
More Skills