ai-agent

Get LLM Power with oterm

Run LLMs from your terminal with oterm, a tool for founders
2,411 stars137 forksPythonGuide quality 8/10Updated 7/25/2026100% free · open source
What it does

Oterm is a terminal client that allows you to interact with large language models (LLMs) directly from your terminal.

When to use it
  • You need to quickly test and iterate on LLM prompts without leaving your terminal.
  • You want to automate tasks that involve generating text using LLMs.
  • You prefer a lightweight, command-line interface for interacting with LLMs.
Ready-to-paste prompt
oterm prompt 'Generate a product description for a new smartwatch with a focus on fitness tracking.'
Heads up: Make sure you have the necessary API keys and credentials set up in your `~/.oterm/config.json` file to use oterm with your preferred LLM model.
Saves to your device
Use with Claude
New

Skip the builder — one click puts this in Claude, Cursor, Antigravity and more.

🔑 Needs an API key

Works after you add credentials — the setup agent will ask you for them.

Try it instantly — no install
Claude Code
mkdir -p ~/.claude/skills/oterm && curl -fsSL https://workflowstacks.com/api/skills/oterm/claude-skill -o ~/.claude/skills/oterm/SKILL.md
Open in another AI app

Opens the app with this repo with the prompt ready to go — no copy-paste needed.

Connect the whole catalog (MCP)
claude mcp add --transport http workflowstacks https://workflowstacks.com/api/mcp

Adds a WorkflowStacks connector to Claude Code: search and load any skill here by chatting.

How Get LLM Power with oterm works
Codeflow
Free to inspect

Get LLM Power with oterm is a medium Python project (~4.1k lines across 48 code files, plus 46 test files). Setup is light: installs like a normal app. Reading the code is optional. Last commit this month, MIT license, has a test suite.

Size
Medium codebase
~4.1k lines · 48 code files · 34 min skim
Setup
One-command install
Installs like a normal app. Reading the code is optional.
Runs on
Python
No API keys detected
Python 100%
Where to start reading
  1. 1
    README.md
    Start here — what it does and how to install it
  2. 2
    pyproject.toml
    Dependencies and the commands it exposes
  3. 3
    src/oterm/__init__.py
    Inside src/ — the main logic begins here
What's in each folder
src/Core code — the actual logic47 files
docs/Documentation26 files
overrides/Folder2 files
tests/Tests — proof it works47 files
.github/CI / automation (GitHub Actions)6 files
READMEHas testsDocumentedCI checksMIT licenseUpdated this month
Quick Actions
Details
Creator
ggozad
Language
Python
Category
ai-agent
Published
10/10/2023

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