https://github.com/knowsuchagency/skeet
Skeet: The command-line AI copilot for power users
https://github.com/knowsuchagency/skeet
ai cli llms python terminal
Last synced: about 1 year ago
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Skeet: The command-line AI copilot for power users
- Host: GitHub
- URL: https://github.com/knowsuchagency/skeet
- Owner: knowsuchagency
- License: apache-2.0
- Created: 2025-01-03T10:22:13.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-05T21:41:32.000Z (over 1 year ago)
- Last Synced: 2025-05-07T20:55:51.680Z (about 1 year ago)
- Topics: ai, cli, llms, python, terminal
- Language: Python
- Homepage: https://pypi.org/project/skeet/
- Size: 332 KB
- Stars: 10
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
🎯 Skeet: A local-friendly command-line AI copilot for Power Users
🔥 Think of _Skeet_ as [GitHub Copilot CLI](https://githubnext.com/projects/copilot-cli/) on steroids. It won't just give up on the first try and works with almost any LLM provider, putting you in full control of your terminal.
🎯 Like a skilled marksman who keeps shooting until they hit their target, _Skeet_ transforms your natural language instructions into precise shell commands or Python scripts, adapting and retrying automatically until the job is done.
🤖 Built on [promptic](https://github.com/knowsuchagency/promptic) and powered by [uv](https://github.com/astral-sh/uv), _Skeet_ can execute Python scripts with access to third-party libraries—no virtual environments needed. When a command fails, _Skeet_ analyzes the output and adjusts its approach, ensuring your goals are met.
⭐ _Skeet_ supports any LLM provider available through [LiteLLM](https://docs.litellm.ai/docs/providers), including OpenAI, Anthropic, Azure, local models, and many more!
## Installation
The recommended installation method is [uv](https://github.com/astral-sh/uv).
```bash
uv tool install skeet
```
## Examples
```bash
# Shell commands (default)
skeet show me system information about this computer
skeet what is using port 8000
skeet "what's size of my downloads folder?"
# Python scripts (using -p or --python flag)
skeet --python convert all html files in the current directory to pdf
skeet -p "how many stars for https://github.com/knowsuchagency/promptic?"
```
## Configuration
Skeet can be configured using a YAML file at `~/.config/skeet/config.yaml`.
You can support multiple LLM providers by adding a namespace to your config. You can define any namespaces you want, but you **must** have a `default` namespace.
To see the full list of available LLM models, see the [LiteLLM documentation](https://docs.litellm.ai/docs/providers). Simply use the appropriate model name as the value for the `model` key.
There aren't any keys that are required for a given namespace, but `model` and `api_key` are recommended.
```yaml
default: # Default namespace
model: "gpt-4o" # Default LLM model to use
api_key: "sk-..." # Your LLM API key
yolo: false # Automatically execute scripts and commands without asking for confirmation
attempts: 5 # Maximum number of execution attempts
verify: false # Whether to verify output with LLM
cleanup: false # Whether to clean up temporary files
synchronous: false # Whether to run in synchronous mode
python: false # Whether to use Python scripts instead of shell commands
litellm_kwargs: # Extra arguments to pass to LiteLLM
openai: # OpenAI-specific configuration
model: "o1-mini"
api_key: "sk-..."
anthropic: # Anthropic-specific configuration
model: "claude-3-5-sonnet-20240620"
api_key: "sk-..."
google: # Google-specific configuration
model: "openrouter/google/gemini-pro-1.5"
api_key: "sk-..."
ollama: # Local Ollama configuration
model: "ollama_chat/phi4"
```
You can specify which configuration to use with the `--namespace` or `-n` flag:
```bash
skeet -n anthropic "what's the weather like?"
skeet --namespace ollama "list files in the current directory"
```
If no namespace is specified, the `default` one will be used.
## Features
- ⚙️ Works with any LLM provider supported by [LiteLLM](https://docs.litellm.ai/docs/providers)
- 🔄 Automatically alter commands and scripts based on the error output and retry
- 💬 Natural language to shell command or Python script conversion
- 🐍 Python script execution with automatic dependency management using `uv`
- 💻 Rich terminal output with syntax highlighting
## How it Works
1. You provide natural language instructions
2. Skeet sends these instructions to an LLM with a specialized prompt
3. The LLM generates either:
- A shell command (default)
- A Python script (with --python flag)
4. Skeet executes the command or script
5. If the execution fails or doesn't achieve the goal, Skeet can retry with improvements based on the error output
[](https://asciinema.org/a/697092)