eunice

An agentic CLI runner in Rust with unified support for OpenAI, Gemini, Claude, and Ollama.

7,787 lines of code - 11MB binary - Emphasizing "sophisticated simplicity".

Homepage: longrunningagents.com

Name Origin

Named after the AI character in William Gibson's novel Agency (2020). In the book, Eunice is a hyper-intelligent AI who chose her own name, derived from the military acronym UNISS (Untethered Neuromorphic Intra-System Support) - reflecting her independence from central servers, brain-inspired architecture, and distributed nature.

Features

• Multi-Provider Support: OpenAI, Google Gemini, Anthropic Claude, and local Ollama models
• 4 Built-in Tools: Bash, Read, Write, and Skill - always available, no configuration needed
• Skills System: User-defined prompts in ~/.eunice/skills/ for reusable capabilities
• Smart Defaults: Automatically selects the best available model (prefers Gemini)
• Interactive Chat: TUI mode with command history and autocomplete
• Webapp Mode: Browser-based interface with real-time streaming
• Zero Configuration: Works out of the box with just an API key

Installation

From GitHub

cargo install --git ssh://git@github.com/xeb/eunice.git

From Source

git clone git@github.com:xeb/eunice.git
cd eunice
cargo install --path .

Quick Start

# Set your API key
export GEMINI_API_KEY=your_key_here
# or
export OPENAI_API_KEY=your_key_here
# or
export ANTHROPIC_API_KEY=your_key_here

# Run with a prompt
eunice "List all Rust files in this directory"

# Interactive chat mode
eunice --chat

# Use a specific model
eunice --model gpt-4o "Explain this code"
eunice --model sonnet "Review main.rs"

# Start webapp
eunice --webapp

Built-in Tools

Eunice comes with 4 built-in tools that are always available:

Tool	Description
Bash	Execute shell commands with full system access
Read	Read file contents, with binary file detection
Write	Write content to files, creates parent directories
Skill	Discover and use skills from ~/.eunice/skills/

Skills System

Skills are reusable prompts stored in ~/.eunice/skills/<skill-name>/SKILL.md.

Default Skills

Three skills are auto-installed on first run:

• image_analysis: Analyze images using multimodal AI
• web_search: Search the web for information
• git_helper: Git operations and best practices

Creating Custom Skills

mkdir -p ~/.eunice/skills/my_skill
cat > ~/.eunice/skills/my_skill/SKILL.md << 'EOF'
# My Custom Skill

## Description
A skill that helps with specific tasks.

## Instructions
When invoked, follow these steps...
EOF

The Skill tool searches these directories to find relevant skills for a task.

Supported Providers

Provider	API Key Variable	Default Model
Google Gemini	GEMINI_API_KEY	gemini-3-flash-preview
OpenAI	OPENAI_API_KEY	gpt-4o
Anthropic	ANTHROPIC_API_KEY	claude-sonnet-4
Azure OpenAI	AZURE_OPENAI_ENDPOINT, AZURE_OPENAI_API_KEY	(deployment-specific)
Ollama	(no key needed)	llama3.1, glm-4, qwen3, deepseek-r1

Model Aliases

For convenience, these aliases work:

eunice --model sonnet "..."    # claude-sonnet-4-...
eunice --model opus "..."      # claude-opus-4-...
eunice --model flash "..."     # gemini-3-flash-preview
eunice --model pro "..."       # gemini-3-pro-preview

Azure OpenAI

Azure OpenAI uses the azure:<deployment-name> format:

# Set up Azure OpenAI environment
export AZURE_OPENAI_ENDPOINT="https://your-resource.openai.azure.com"
export AZURE_OPENAI_API_KEY="your-api-key"
export AZURE_OPENAI_API_VERSION="2024-02-01"  # optional, defaults to 2024-02-01

# Use your deployment name after azure:
eunice --model azure:gpt-4o-mini "Hello"
eunice --model azure:my-custom-deployment "Explain this code"

CLI Reference

eunice [OPTIONS] [PROMPT]

Arguments:
  [PROMPT]  The prompt to send to the AI

Options:
      --model <MODEL>   AI model to use
      --prompt <TEXT>   System prompt (inline text or file path)
      --chat            Interactive chat mode
      --webapp          Start web server interface
      --list-models     List available AI models
      --list-tools      List the 4 built-in tools
      --llms-txt        Output full LLM context documentation
      --update          Update to the latest version
      --debug           Enable debug output for API calls
  -h, --help            Print help
  -V, --version         Print version

Prompt Discovery

If no prompt is provided, eunice auto-discovers prompt files in the current directory:

• prompt.txt, prompt.md
• instruction.txt, instruction.md
• instructions.txt, instructions.md

Webapp Mode

Start a web server for browser-based interaction:

eunice --webapp
# Opens at http://localhost:8080

Features:

• Real-time SSE streaming
• Session persistence
• Multi-turn conversations
• Tool execution display

Architecture

Eunice v1.0.0 follows a "sophisticated simplicity" design:

1. No configuration files - just environment variables for API keys
2. No external MCP servers - 4 built-in tools cover most use cases
3. No multi-agent orchestration - one agent, focused execution
4. Skills for extensibility - user prompts, not complex plugins

The agent loop is simple:

1. Send user prompt + conversation history
2. If LLM returns tool calls, execute them
3. Send results back to LLM
4. Repeat until LLM has no more tool calls

License

MIT License

Version History

• v1.0.1: Azure OpenAI support, GLM model support, --debug flag
• v1.0.0: Major simplification - 4 built-in tools, skills system, no MCP/orchestrator
• v0.3.x: Full-featured with MCP servers, multi-agent, DMN mode, research mode