openai-llm
Invoke OpenAI models for text generation, reasoning, and code tasks using the Python openai SDK. Supports gpt-4o (multimodal), o1 (reasoning), o3-mini (fast reasoning), and gpt-4o-mini (fast).
npx skills add majiayu000/claude-skill-registry --skill openai-llm --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# OpenAI LLM Skill Invoke OpenAI models for text generation, reasoning, code analysis, and complex tasks using the Python `openai` SDK. ## Available Models | Model ID | Description | Best For | |----------|-------------|----------| | `gpt-4o` | Flagship multimodal model | General tasks, vision, analysis | | `gpt-4o-mini` | Fast and cost-efficient | Quick tasks, high throughput | | `o1` | Advanced reasoning model | Complex reasoning, math, code | | `o1-mini` | Fast reasoning | Moderate reasoning tasks | | `o3-mini` | Newest reasoning model | Deep reasoning, planning | ## Configuration **API Key Location**: `C:\Users\USERNAME\env` (OPENAI_API_KEY) **Default API Key**: Use environment variable `OPENAI_API_KEY` ## Usage ### Basic Text Generation ```bash python -c " from openai import OpenAI client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY")) response = client.chat.completions.create( model='gpt-4o', messages=[{'role': 'user', 'content': 'YOUR_PROMPT_HERE'}] ) print(response.choices[0].message.content) " ``` ### With System Instructions ```bash python -c " from openai import OpenAI client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY")) response = client.chat.completions.create(
- Available Models
- Configuration
- Usage
- Basic Text Generation
- With System Instructions
- Streaming Response
- Using Reasoning Models (o1, o3-mini)
- Workflow
- Example Invocations
- Code Review
- Complex Reasoning (with o1)
- Generate Code
- Multi-turn Conversations
- Model Notes
python -c "
from openai import OpenAI
client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"))
response = client.chat.completions.create(
stream = client.chat.completions.create(
for chunk in stream:
if chunk.choices[0].delta.content:
def calculate_total(items):
total = 0
for item in items:What does the openai-llm skill do?
Invoke OpenAI models for text generation, reasoning, and code tasks using the Python openai SDK. Supports gpt-4o (multimodal), o1 (reasoning), o3-mini (fast reasoning), and gpt-4o-mini (fast).
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill openai-llm --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.