kittycode 0.1.2

Minimal AI coding agent with a simple tool loop and skill support.

KittyCode

KittyCode is a minimal terminal coding agent focused on a compact, readable implementation. It keeps the core runtime straightforward, with an agent loop, local tools, context compression, a small command-line interface, and support for both OpenAI-compatible and Anthropic APIs.

Background

KittyCode follows a simple terminal-agent runtime model:

• A user message is sent through the configured model interface.
• The model can either answer directly or call tools.
• Tool calls are executed locally and the results are fed back into the conversation.
• The loop continues until the model returns plain text.

The project is intentionally small. It includes the core agent runtime, a compact CLI, session persistence, context compression, and a default built-in tool set.

Features

• Minimal agent loop with optional parallel execution for multiple tool calls.
• LLM adapter that supports both OpenAI-compatible and Anthropic interfaces.
• Built-in tools for shell commands, file reading, file writing, targeted editing, glob search, regex search, and sub-agents.
• Startup skill discovery from ~/.kittycode/skills, with skill metadata injected into the system prompt each round.
• Interactive REPL and one-shot command mode.
• ANSI pixel-cat startup banner.
• Esc interrupt support for stopping the current agent run at the next safe checkpoint.
• Context compression to keep long sessions manageable.
• Session save and resume support.

Requirements

• Python 3.10 or newer
• An API key for either an OpenAI-compatible endpoint or an Anthropic-compatible endpoint

Installation

Clone the repository and install it in editable mode:

cd KittyCode
python -m pip install -e .

If you also want the development test dependency:

python -m pip install -e .[dev]

Configuration

KittyCode reads startup configuration from ~/.kittycode/config.json.

Supported fields:

• interface: openai or anthropic
• api_key
• model
• base_url
• max_tokens
• temperature
• max_context

OpenAI-compatible example:

{
	"interface": "openai",
	"api_key": "sk-...",
	"model": "gpt-4o",
	"base_url": "https://api.openai.com/v1",
	"max_tokens": 4096,
	"temperature": 0,
	"max_context": 128000
}

Anthropic example:

{
	"interface": "anthropic",
	"api_key": "sk-ant-...",
	"model": "claude-3-7-sonnet-latest",
	"base_url": "https://api.anthropic.com",
	"max_tokens": 4096,
	"temperature": 0,
	"max_context": 128000
}

The CLI still allows explicit overrides such as --model, --interface, --base-url, and --api-key.

Skills

At startup, KittyCode scans ~/.kittycode/skills for skill folders. Each skill should live in its own directory and include a SKILL.md file at the top level.

Expected layout:

~/.kittycode/skills/
	example-skill/
		SKILL.md
		other-files...

KittyCode reads the leading name and description fields from each SKILL.md, keeps the resulting skill list in memory, and inserts the list into the system prompt at the start of every round. The prompt includes:

• name
• description
• path

This allows the model to see which local skills are available and decide when to read and use them.

Before each round, KittyCode checks whether the skill directory changed and reloads the cached skill metadata when needed, so adding or editing skills does not require restarting the process.

You can also invoke a loaded skill directly from the CLI with /<skill name>.

• /<skill name> selects that skill for your next non-command message.
• /<skill name> <task> runs the next request immediately with that skill.

Usage

Run the interactive terminal UI:

kittycode

When the CLI is busy, press Esc to interrupt the current run. The stop is cooperative: KittyCode cancels at the next safe checkpoint between LLM streaming, tool dispatch, and loop rounds. A blocking external call may still need to return before the run fully stops.

You can also use the module entry point:

python -m kittycode

Run a one-shot prompt and exit:

kittycode -p "Explain the project structure"

Resume a saved session:

kittycode -r session_1234567890

Override model, interface, or endpoint from the command line:

kittycode --interface anthropic --model claude-3-7-sonnet-latest

Interactive Commands

Inside the REPL, KittyCode supports:

• /help
• /reset
• /skills
• /<skill name>
• /model <name>
• /tokens
• /compact
• /save
• /sessions
• /quit

The /skills command refreshes the local skill cache if the skill directory has changed and then prints the currently loaded skills. Slash commands also support prefix matching while typing, so entering / shows matching commands and skills through completion suggestions.

If kittycode Is Still Not Found After pip install -e .

The project already declares the console entry point in pyproject.toml:

[project.scripts]
kittycode = "kittycode.cli:main"

So if kittycode is still unavailable, the usual cause is the local Python install location rather than missing packaging metadata.

Check which Python/pip you used:

python3 -m pip --version
python3 -m site --user-base

On macOS, a user install commonly places scripts under:

~/Library/Python/3.11/bin

If that directory is not in PATH, the editable install may succeed but the shell still will not find kittycode.

For zsh, add the corresponding bin directory to your shell profile:

export PATH="$HOME/Library/Python/3.11/bin:$PATH"

Then reload the shell:

source ~/.zshrc

If the install itself fails with a permissions error while writing a .pth file under ~/Library/Python/.../site-packages, fix that environment issue first or install into a virtual environment before retrying.

Project Layout

• kittycode/agent.py: core agent loop
• kittycode/llm.py: streaming LLM wrapper
• kittycode/context.py: context compression
• kittycode/cli.py: interactive and one-shot CLI
• kittycode/session.py: session persistence
• kittycode/tools/: built-in tools
• tests/: focused runtime and tool tests

Development

Run the test suite:

python -m pytest -q

The current test suite covers the exported API, config-file behavior, provider conversion helpers, context compression, session helpers, the default tool registry, and skill discovery/prompt injection.