co-mono/packages/coding-agent/README.md

@mariozechner/coding-agent

Interactive CLI coding assistant powered by multiple LLM providers. Chat with AI models that can read files, execute commands, and make precise edits to your codebase.

Installation

npm install -g @mariozechner/coding-agent

Quick Start

# Set your API key (see API Keys section)
export ANTHROPIC_API_KEY=sk-ant-...

# Start the interactive CLI
pi

Once in the CLI, you can chat with the AI:

You: Create a simple Express server in src/server.ts

The agent will use its tools to read, write, and edit files as needed, and execute commands via Bash.

API Keys

The CLI supports multiple LLM providers. Set the appropriate environment variable for your chosen provider:

# Anthropic (Claude)
export ANTHROPIC_API_KEY=sk-ant-...
# Or use OAuth token (retrieved via: claude setup-token)
export ANTHROPIC_OAUTH_TOKEN=...

# OpenAI (GPT)
export OPENAI_API_KEY=sk-...

# Google (Gemini)
export GEMINI_API_KEY=...

# Groq
export GROQ_API_KEY=gsk_...

# Cerebras
export CEREBRAS_API_KEY=csk-...

# xAI (Grok)
export XAI_API_KEY=xai-...

# OpenRouter
export OPENROUTER_API_KEY=sk-or-...

# ZAI
export ZAI_API_KEY=...

If no API key is set, the CLI will prompt you to configure one on first run.

Slash Commands

The CLI supports several commands to control its behavior:

/model

Switch models mid-session. Opens an interactive selector where you can type to search (by provider or model name), use arrow keys to navigate, Enter to select, or Escape to cancel.

/thinking

Adjust thinking/reasoning level for supported models (Claude Sonnet 4, GPT-5, Gemini 2.5). Opens an interactive selector where you can use arrow keys to navigate, Enter to select, or Escape to cancel.

/export [filename]

Export the current session to a self-contained HTML file:

/export                          # Auto-generates filename
/export my-session.html          # Custom filename

The HTML file includes the full conversation with syntax highlighting and is viewable in any browser.

/session

Show session information and statistics:

/session

Displays:

• Session file path and ID
• Message counts (user, assistant, total)
• Token usage (input, output, cache read/write, total)
• Total cost (if available)

Editor Features

The interactive input editor includes several productivity features:

Path Completion

Press Tab to autocomplete file and directory paths:

• Works with relative paths: ./src/ + Tab → complete files in src/
• Works with parent directories: ../../ + Tab → navigate up and complete
• Works with home directory: ~/Des + Tab → ~/Desktop/
• Use Up/Down arrows to navigate completion suggestions
• Press Enter to select a completion
• Shows matching files and directories as you type

File Drag & Drop

Drag files from your OS file explorer (Finder on macOS, Explorer on Windows) directly onto the terminal. The file path will be automatically inserted into the editor. Works great with screenshots from macOS screenshot tool.

Multi-line Paste

Paste multiple lines of text (e.g., code snippets, logs) and they'll be automatically coalesced into a compact [paste #123 <N> lines] reference in the editor. The full content is still sent to the model.

Keyboard Shortcuts

• Ctrl+K: Delete current line
• Ctrl+C: Clear editor (first press) / Exit pi (second press)
• Tab: Path completion
• Enter: Send message
• Shift+Enter: Insert new line (multi-line input)
• Arrow keys: Move cursor
• Ctrl+A / Home / Cmd+Left (macOS): Jump to start of line
• Ctrl+E / End / Cmd+Right (macOS): Jump to end of line

Project Context Files

The agent automatically loads context from AGENT.md or CLAUDE.md files at the start of new sessions (not when continuing/resuming). These files are loaded in hierarchical order to support both global preferences and monorepo structures.

File Locations

Context files are loaded in this order:

1. Global context: ~/.pi/agent/AGENT.md or CLAUDE.md

   • Applies to all your coding sessions
   • Great for personal coding preferences and workflows

2. Parent directories (top-most first down to current directory)

   • Walks up from current directory to filesystem root
   • Each directory can have its own AGENT.md or CLAUDE.md
   • Perfect for monorepos with shared context at higher levels

3. Current directory: Your project's AGENT.md or CLAUDE.md

   • Most specific context, loaded last
   • Overwrites or extends parent/global context

File preference: In each directory, AGENT.md is preferred over CLAUDE.md if both exist.

What to Include

Context files are useful for:

• Project-specific instructions and guidelines
• Common bash commands and workflows
• Architecture documentation
• Coding conventions and style guides
• Dependencies and setup information
• Testing instructions
• Repository etiquette (branch naming, merge vs. rebase, etc.)

Example

# Common Commands
- npm run build: Build the project
- npm test: Run tests

# Code Style
- Use TypeScript strict mode
- Prefer async/await over promises

# Workflow
- Always run tests before committing
- Update CHANGELOG.md for user-facing changes

All context files are automatically included in the system prompt at session start, along with the current date/time and working directory. This ensures the AI has complete project context from the very first message.

Image Support

Send images to vision-capable models by providing file paths:

You: What is in this screenshot? /path/to/image.png

Supported formats: .jpg, .jpeg, .png, .gif, .webp

The image will be automatically encoded and sent with your message. JPEG and PNG are supported across all vision models. Other formats may only be supported by some models.

Session Management

Sessions are automatically saved in ~/.pi/agent/sessions/ organized by working directory. Each session is stored as a JSONL file with a unique timestamp-based ID.

To continue the most recent session:

pi --continue
# or
pi -c

To browse and select from past sessions:

pi --resume
# or
pi -r

This opens an interactive session selector where you can:

• Type to search through session messages
• Use arrow keys to navigate the list
• Press Enter to resume a session
• Press Escape to cancel

Sessions include all conversation messages, tool calls and results, model switches, and thinking level changes.

To run without saving a session (ephemeral mode):

pi --no-session

To use a specific session file instead of auto-generating one:

pi --session /path/to/my-session.jsonl

CLI Options

pi [options] [messages...]

Options

--provider Provider name. Available: anthropic, openai, google, xai, groq, cerebras, openrouter, zai. Default: anthropic

--model Model ID. Default: claude-sonnet-4-5

--api-key API key (overrides environment variables)

--system-prompt Custom system prompt (overrides default coding assistant prompt)

--mode Output mode for non-interactive usage. Options:

• text (default): Output only the final assistant message text
• json: Stream all agent events as JSON (one event per line). Events are emitted by @mariozechner/pi-agent and include message updates, tool executions, and completions
• rpc: JSON mode plus stdin listener for headless operation. Send JSON commands on stdin: {"type":"prompt","message":"..."} or {"type":"abort"}. See test/rpc-example.ts for a complete example

--no-session Don't save session (ephemeral mode)

--session Use specific session file path instead of auto-generating one

--continue, -c Continue the most recent session

--resume, -r Select a session to resume (opens interactive selector)

--help, -h Show help message

Examples

# Start interactive mode
pi

# Single message mode (text output)
pi "List all .ts files in src/"

# JSON mode - stream all agent events
pi --mode json "List all .ts files in src/"

# RPC mode - headless operation (see test/rpc-example.ts)
pi --mode rpc --no-session
# Then send JSON on stdin:
# {"type":"prompt","message":"List all .ts files"}
# {"type":"abort"}

# Continue previous session
pi -c "What did we discuss?"

# Use different model
pi --provider openai --model gpt-4o "Help me refactor this code"

Tools

Built-in Tools

The agent has access to four core tools for working with your codebase:

read Read file contents. Supports text files and images (jpg, png, gif, webp). Images are sent as attachments. For text files, defaults to first 2000 lines. Use offset/limit parameters for large files. Lines longer than 2000 characters are truncated.

write Write content to a file. Creates the file if it doesn't exist, overwrites if it does. Automatically creates parent directories.

edit Edit a file by replacing exact text. The oldText must match exactly (including whitespace). Use this for precise, surgical edits. Returns an error if the text appears multiple times or isn't found.

bash Execute a bash command in the current working directory. Returns stdout and stderr. Commands run with a 30 second timeout.

MCP & Adding Your Own Tools

You don't need MCP to extend pi's capabilities. Agents are excellent at writing code and running bash commands - leverage that instead.

The simple approach:

• Write small CLI scripts for your specific needs (Node.js, Python, whatever)
• Put them in your PATH or a dedicated ~/agent-tools directory
• Document them in a README that you point your agent to when needed

Why this works:

• Token efficient: A 225-token README beats a 13,000-token MCP server description
• Composable: Chain tools with bash pipes, save outputs to files, process results with code
• Easy to extend: Need a new tool? Ask your agent to write it for you
• No overhead: No server processes, no protocol complexity, just executables

Example structure:

# Set up tools directory
mkdir -p ~/agent-tools/browser-tools
cd ~/agent-tools/browser-tools

# Create minimal CLI tools (e.g., start.js, nav.js, screenshot.js)
# Document them in README.md
# Add to PATH or reference in AGENT.md

# In your session:
# "Read ~/agent-tools/browser-tools/README.md and use those tools"

The agent already knows how to use bash, write code, and compose results. Building on these primitives is often simpler, more flexible, and more efficient than integrating an MCP server.

For a detailed walkthrough and real examples, see: What if you don't need MCP at all?

Security (YOLO by default)

This agent runs in full YOLO mode and assumes you know what you're doing. It has unrestricted access to your filesystem and can execute any command without permission checks or safety rails.

What this means:

• No permission prompts for file operations or commands
• No pre-checking of bash commands for malicious content
• Full filesystem access - can read, write, or delete anything
• Can execute any command with your user privileges

Why:

• Permission systems add massive friction while being easily circumvented
• Pre-checking tools for "dangerous" patterns introduces latency, false positives, and is ineffective

Prompt injection risks:

• By default, pi has no web search or fetch tool
• However, it can use curl or read files from disk
• Both provide ample surface area for prompt injection attacks
• Malicious content in files or command outputs can influence behavior

Mitigations:

• Run pi inside a container if you're uncomfortable with full access
• Use a different tool if you need guardrails
• Don't use pi on systems with sensitive data you can't afford to lose
• Fork pi and add all of the above

This is how I want it to work and I'm not likely to change my stance on this.

Use at your own risk.

License

MIT

See Also

• @mariozechner/pi-ai: Core LLM toolkit with multi-provider support
• @mariozechner/pi-agent: Agent framework with tool execution