LLM
Implement large language model (LLM) chat completions using the z-ai-web-dev-sdk.
Skill by rahlplx
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/rahlplx-llm
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: ml
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What's inside
- Skill name
LLM- Description
- Implement large language model (LLM) chat completions using the z-ai-web-dev-sdk. Use this skill when the user needs to build conversational AI applications, chatbots, AI assistants, or any text generation features. Supports multi-turn conversations, system prompts, and context management.
- License
- MIT
- Instructions
- 852 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Agent Skills spec issues
- name: only lowercase letters, digits and single hyphens allowed
- body: 852 lines (spec recommends under 500)
Files (3)
- LICENSE.txt
- SKILL.md
- chat.ts · scripts/
SKILL.md (first lines)
# LLM (Large Language Model) Skill
This skill guides the implementation of chat completions functionality using the z-ai-web-dev-sdk package, enabling powerful conversational AI and text generation capabilities.
## Skills Path
**Skill Location**: `{project_path}/skills/llm`
this skill is located at above path in your project.
**Reference Scripts**: Example test scripts are available in the `{Skill Location}/scripts/` directory for quick testing and reference. See `{Skill Location}/scripts/chat.ts` for a working example.
## Overview
The LLM skill allows you to build applications that leverage large language models for natural language understanding and generation, including chatbots, AI assistants, content generation, and more.
**IMPORTANT**: z-ai-web-dev-sdk MUST be used in backend code only. Never use it in client-side code.
## Prerequisites
The z-ai-web-dev-sdk package is already installed. Import it as shown in the examples below.
## CLI Usage (For Simple Tasks)
For simple, one-off chat completions, you can use the z-ai CLI instead of writing code. This is ideal for quick tests, simple queries, or automation scripts.
### Basic Chat
```bash
# Simple question
z-ai chat --prompt "What is the capital of France?"
# Save response to file
z-ai chat -p "Explain quantum computing" -o response.json
# Stream the response
z-ai chat -p "Write a short poem" --stream
```
### With System Prompt
```bash
# Custom system prompt for specific behavior
z-ai chat \
--prompt "Review this code: function add(a,b) { return a+b; }" \
--system "You are an expert code reviewer" \
-o review.json
```
### With Thinking (Chain of Thought)
```bash
# Enable thinking for complex reasoning
z-ai chat \
--prompt "Solve this math problem: If a train travels 120km in 2 hours, what's its speed?" \
--thinking \
-o solution.json
```
### CLI Parameters
- `--prompt, -p <text>`: **Required** - User message content
- `--system, -s <text>`: Optional - System prompt for custom behavior
- `--thinking, -t`: Optional - Enable chain-of-thought reasoning (default: disabled)
- `--output, -o <path>`: Optional - Output file path (JSON format)
- `--stream`: Optional - Stream the response in real-time
### When to Use CLI vs SDK
**Use CLI for:**
- Quick one-off questions
- Simple automation scripts
- Testing prompts
- Single-turn conversations
**Use SDK for:**
- Multi-turn conversations with context
- Custom conversation management
- Integration with web applications
- Complex chat workflows
- Production applications
## Basic Chat Completions
### Simple Question and Answer
```javascript
import ZAI from 'z-ai-web-dev-sdk';
async function askQuestion(question) {
const zai = await ZAI.create();
const completion = await zai.chat.completions.create({
messages: [
{
role: 'assistant',
content: 'You are a helpful assistant.'
},
{
role: 'user',
content: question
}
],
thinking: { type: 'disabled' }
});
const response = completion.choices[0]?.message?.content;
return response;
}
// Usage
const answer = await askQuestion('What is the capital of France?');
console.log('Answer:', answer);
```
### Custom System Prompt
```javascript
import ZAI from 'z-ai-web-dev-sdk';From rahlplx/smile-savers-2026-feb, MIT.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Feb 17, 2026 (8 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/rahlplx/smile-savers-2026-feb
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
LLM skill. Agent Mart. https://agentmart.dev/skills/rahlplx-llm (last updated 2026-10-24)