Agent skill
llm-integration
Integrate LLMs into applications - APIs, prompting, fine-tuning, and context management
Stars
163
Forks
31
Install this agent skill to your Project
npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/testing/llm-integration-pluginagentmarketpla-custom-plugin-ai-age
SKILL.md
LLM Integration
Integrate Large Language Models with production-grade reliability.
When to Use This Skill
Invoke this skill when:
- Connecting to Claude, OpenAI, or other LLM APIs
- Designing effective prompts and system messages
- Optimizing token usage and costs
- Implementing streaming responses
Parameter Schema
| Parameter | Type | Required | Description | Default |
|---|---|---|---|---|
provider |
enum | Yes | anthropic, openai, google, local |
- |
task |
string | Yes | Integration goal | - |
streaming |
bool | No | Enable streaming | true |
max_tokens |
int | No | Response token limit | 4096 |
Quick Start
python
# Anthropic Claude
from anthropic import Anthropic
client = Anthropic()
response = client.messages.create(
model="claude-sonnet-4-20250514",
max_tokens=1024,
messages=[{"role": "user", "content": "Hello!"}]
)
# OpenAI
from openai import OpenAI
client = OpenAI()
response = client.chat.completions.create(
model="gpt-4-turbo",
messages=[{"role": "user", "content": "Hello!"}]
)
Prompt Templates
System Prompt
python
SYSTEM = """You are {role}, an expert in {domain}.
Your task: {task}
Constraints: {constraints}
Output format: {format}"""
Chain-of-Thought
python
COT = """Think step by step:
1. Understand the problem
2. Break it down
3. Solve each part
4. Combine results"""
Cost Optimization
| Model | Input $/1M | Output $/1M | Best For |
|---|---|---|---|
| Claude Haiku | $0.25 | $1.25 | High volume |
| Claude Sonnet | $3 | $15 | Complex tasks |
| Claude Opus | $15 | $75 | Most demanding |
Troubleshooting
| Issue | Solution |
|---|---|
| 429 Rate Limited | Exponential backoff |
| Context overflow | Truncate/summarize |
| Poor output quality | Add examples, lower temp |
| High costs | Use cheaper model, cache |
Best Practices
- Always implement retry with backoff
- Use streaming for better UX
- Cache repeated queries
- Monitor token usage
Related Skills
ai-agent-basics- Agent architecturerag-systems- Retrieval augmentationtool-calling- Function calling
References
Didn't find tool you were looking for?