Loading...
Loading...
Found 6 Skills
Operate Google Colab environments via the `colab` CLI. Use when asked to create or manage GPU/TPU sessions, run Python/shell on a remote Colab VM, sync files, automate environment setup (packages, auth, Drive), or export session history.
Orchestrate Google Colab Pro/Pro+ GPU instances as remote training backends via SSH. Compounds /agent-browser (to launch Colab sessions and install colab-ssh) with SSH (to operate the runtime remotely). Use when: (1) launching a Colab notebook for GPU training, (2) running training jobs on Colab from the local terminal, (3) transferring datasets/checkpoints to/from Colab, (4) monitoring GPU utilization on a Colab instance, (5) integrating Colab GPU compute with /autoany EGRI optimization loops, (6) reconnecting to a Colab session after timeout. Triggers on: "colab", "colab-remote", "colab ssh", "colab training", "remote GPU", "colab pro", "train on colab", "google colab".
Use Google Colab CLI from a terminal agent to provision CPU, GPU, or TPU runtimes, run Python scripts and notebooks remotely, install packages, move files, export logs, diagnose authentication or allocation failures, and clean up sessions. Use for Colab runtime work, remote GPU/TPU execution, QLoRA or fine-tuning on Colab, notebook execution, Colab CLI troubleshooting, or `colab` command guidance.
Disposable builder skill (delete after the harness is built): scaffolds a Colab-centric project — a repository whose deliverable is Google Colab notebooks, mirrored locally and validated in an official Colab-runtime devcontainer before running on real Colab. Use when creating or hardening a repository that produces notebooks people open and run in Colab — tutorials, course materials, runnable demos, shareable analyses — or when a project uses Colab as its runtime, including driving Colab VMs as disposable compute for local scripts. Not for generic Jupyter-notebook work, projects where notebooks are incidental exploration beside a library or pipeline, or mature migrations; preserves working choices.
Use for Jupyter, JupyterLab, marimo, and Google Colab workflows. Choose this skill when creating, converting, or improving reproducible notebooks for data exploration, analysis, documentation, or teaching.
7 code execution skills. Trigger: running code, interactive notebooks, Jupyter, Colab, sandboxed execution. Design: execution environment guides with setup instructions and best practices.