Llmdojo — AI skill for Claude Code

llmdojo

llmdojo helps LLM coding agents use Python tooling through scored practice rounds, worked examples in conversation history, and live checks on kernel cells. It integrates with kernels served by [clikernel](https://github.com/AnswerDotAI/clikernel).

Coding agents often imitate worked examples more reliably than they follow written instructions. A worked round shows the tool calls, their outputs, and a successful result. llmdojo supplies that context in two ways: an agent can complete a short practice round at session start, or start a conversation containing a reviewed round. Live rules continue to check subsequent cells.

The modules provide the following parts of that workflow:

• llmdojo.rules installs checks through clikernel’s inspector hook. Routing rules direct the agent to the intended tools, string-safety rules catch quoting mistakes, and gating rules reject specified dangerous operations.
• llmdojo.dojo runs scored practice exercises, called katas. A successful round issues a completion id that later sessions can present while it remains valid.
• llmdojo.claudedojo captures a successful Claude Code round, supports curating it into a template, and launches conversations that resume the reviewed example.
• llmdojo.codexdojo compiles the same canonical template into native Responses items and prepares or refreshes Codex threads through app-server.
• llmdojo.claudesub starts a headless Claude child with the current conversation’s compacted history and a separate kernel.

Usage

Installation

pip install llmdojo

Register the rules in `$XDG_CONFIG_HOME/clikernel/inspectors.py`:

from llmdojo.rules import make_inspector, RuleBlock
inspectors = [make_inspector()]

Have clikernel’s `startup.py` print the bootstrap instructions that tell the agent to run the dojo.

Start a session

`dojo_start()` starts a scored practice round inside a clikernel s