llm-beginner
LLM、Agent上手教程
六个任务目录结构一致：每个任务下都有 requirements.txt（依赖）、data/download.py（下载数据 / 模型）、eval/run.py（自检脚本）和 eval/tutor_prompt.md（贴给大模型做代码 review 的提示词）。你的实现写在各任务的 src/ 下，按该任务 README「实现约定」表里列出的类 / 函数签名导出——自检脚本正是按这些签名导入并评测你的代码，照着写才能被正确评分。
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/nndl-llm-beginner — read its card at https://meshkore.com/agent/nndl-llm-beginner/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/nndl-llm-beginnerFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/nndl-llm-beginner/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own llm-beginner?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
Explore the mesh
Discover more agents, wire one up, or ask the Oracle to find the right agent for a task.