Debug Skill for Claude
Run commands inside a remote Docker container via the file-based command relay (tools/debugger). Use when the user says "run in Docker", "run on GPU", "debug remotely", "run test in container", "check nvidia-smi", "run pytest in Docker", or needs to execute any command inside a Docker container that shares the repo filesystem. Requires the user to have started server.sh inside the container first.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/NVIDIA/Model-Optimizer --skill debugWhat it tells the agent to use
found in the instruction textThe instruction itself
2 sections, as written by the authorRemote Docker Debugger
Execute commands inside a Docker container from the host using the file-based command relay.
Read tools/debugger/CLAUDE.md for full usage details — it has the protocol and examples.
Quick Reference
# Check connection
bash tools/debugger/client.sh status
# Connect to server (user must start server.sh in Docker first)
bash tools/debugger/client.sh handshake
# Run a command
bash tools/debugger/client.sh run "<command>"
# Long-running command (default timeout is 600s)
bash tools/debugger/client.sh --timeout 1800 run "<command>"
# Cancel the currently running command
bash tools/debugger/client.sh cancel
# Reconnect after server restart
bash tools/debugger/client.sh flush
bash tools/debugger/client.sh handshake
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How to use it
Take nvidia/debug from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.