kaggle git:20260929.8242017A

Immutable. This exact content never changes and is served at /api/v1/blob/d19b9e8e32963408.

---
name: kaggle
description: "Operate Kaggle competitions, datasets, kernels, models, and submissions."
license: MIT
metadata:
  kind: connector
  author: Médéric HURIER (Fmind)
  source: github.com/fmind/dot/tree/main/skills/kaggle
  created: "2026-09-16"
  updated: "2026-09-29"
---

# Kaggle CLI

Use `kaggle` for competition, dataset, kernel, and model operations from the shell. The official Kaggle skills document every command and metadata file; this skill owns authentication, download scope, and the authority boundary around submissions and publications.

## Workflow

1. **Resolve the account**: `kaggle auth login` (OAuth) or `KAGGLE_API_TOKEN` in the environment; the legacy `~/.kaggle/kaggle.json` still works. Never run `kaggle auth print-access-token` during ordinary work.
1. **Read before writing**: use bounded list/file commands and `kaggle competitions submission-limits <slug> --json` to inspect available data and submission limits. Read the competition's current rules separately; these API calls do not return the full rules or authorize accepting them.
1. **Download into an ignored directory**: accept the competition rules on the website first (the CLI returns 403 otherwise).

   ```bash
   kaggle competitions download <slug> -p data/
   kaggle datasets download <owner>/<name> -p data/ --unzip
   ```

1. **Enter competitions and schedule reminders**: after accepting rules, inspect the timeline with `kaggle competitions pages list list <slug> --content` (the repeated `list` is required by the CLI parser). Schedule milestone reminders in Google Calendar using `gws` (one week before the entry and team merger deadline, and on the final submission day) so entry cutoffs, team merger deadlines, and final submission locks are never missed.
1. **Kernels as code**: `kaggle kernels init -p <dir>` writes `kernel-metadata.json`. Before an authorized `kaggle kernels push -p <dir>`, inspect the upload directory, target ID, data sources, `is_private`, accelerator, internet access, and run timeout: pushing uploads code and starts remote execution. Keep `is_private: true` unless public release was explicitly requested, and inspect `kaggle quota` before accelerator use. Verify with `kaggle kernels status <owner>/<slug>` and retrieve artifacts with `kaggle kernels output <owner>/<slug> -p out/`.
1. **Submit with authority**: a submission counts against the daily limit and shows on the leaderboard, so confirm the competition, file, and message first, then verify.

   ```bash
   kaggle competitions submit <slug> -f submission.csv -m "<message>"
   kaggle competitions submissions <slug>
   ```

1. **Publish with authority**: `kaggle datasets create -p <dir>` creates a private dataset unless `--public` is explicitly authorized. `kaggle datasets version -p <dir> -m "<message>"` updates an existing dataset and retains its visibility; it has no `--public` flag. Verify the target dataset's current visibility before uploading a version, and confirm the license and intended audience before either operation.

## Gotchas

- **Pinned version**: in a project that pins `kaggle`, call `uv run kaggle` so the pinned version runs instead of the global shim.
- **Quota**: `kaggle quota` shows the accelerator budget before a kernel push with `--accelerator`.
- **Scripts**: pass `-W` to silence the out-of-date warning so JSON output stays parseable.

## Official Skills

Upstream: `Kaggle/kaggle-cli` for command guidance and `Kaggle/kaggle-skills` for competition formats. Follow the shared [vendor-skill policy](../agent-project/references/vendor-skills.md) and install only the source relevant to the task.

## Documentation

- [Kaggle CLI](https://github.com/Kaggle/kaggle-cli) · [Kaggle API](https://www.kaggle.com/docs/api)
- Releases: [Kaggle CLI](https://github.com/Kaggle/kaggle-cli/releases)
- Companion skills: [gws](../gws/SKILL.md) (schedule competition timeline and deadline reminders in Google Calendar), [python-stack](../python-stack/references/foundation/GUIDE.md) (project layout), [duckdb](../duckdb/SKILL.md) (inspect downloads), [hf](../hf/SKILL.md) (Hub models and datasets), [colab](../colab/SKILL.md) (rented accelerators).