Kaggle — Unified Skill
Complete Kaggle integration for any LLM or agentic coding system (Claude Code, gemini-cli, Cursor, etc.): account setup, competition reports, dataset/model downloads, notebook execution, competition submissions, hackathon writeup retrieval, badge collection, and general Kaggle questions. Five integrated modules working together.
Network requirements: outbound HTTPS to api.kaggle.com, www.kaggle.com,
and storage.googleapis.com.
Modules
| Module | Purpose |
|---|---|
| registration | Account creation, API key generation, credential storage |
| comp-report | Competition landscape reports (Python API + optional Playwright via host agent) |
| kllm | Core Kaggle interaction (kagglehub, CLI, MCP) — includes the hackathon/ submodule for writeup retrieval and overview/rubric extraction |
| badge-collector | Systematic badge earning across 5 phases |
Credential Setup
Always run the credential checker first:
python3 shared/check_all_credentials.py
Primary credential (recommended):
| Variable | How to Get | Purpose |
|---|---|---|
KAGGLE_API_TOKEN | "Generate New Token" at kaggle.com/settings | Works with CLI (>= 1.8.0), kagglehub (>= 0.4.1), MCP |
Legacy credentials (optional, for older tools):
| Variable | How to Get | Purpose |
|---|---|---|
KAGGLE_USERNAME | Account creation | Identity (auto-detected from token) |
KAGGLE_KEY | "Create Legacy API Key" at kaggle.com/settings | Legacy key for older CLI/kagglehub versions |
Store your API token in ~/.kaggle/access_token (recommended) or as an env var.
If any are missing, follow the registration walkthrough:
Read modules/registration/README.md for the full step-by-step guide.
Security: Never echo, log, or commit actual credential values.
Module: Registration
Walks users through creating a Kaggle account and generating API credentials
(API token as primary, legacy key as optional). Saves to ~/.kaggle/access_token
and optionally .env and ~/.kaggle/kaggle.json.
Key commands:
python3 modules/registration/scripts/check_registration.py
bash modules/registration/scripts/setup_env.sh
Read modules/registration/README.md for the complete walkthrough.
Module: Competition Reports
Generates comprehensive landscape reports of recent Kaggle competition activity.
Uses Python API for metadata; SPA-only content (problem statement,
rendered evaluation details, winner writeup links) requires the host
agent to provide Playwright MCP tools — the skill itself does not bundle
them. For most overview content, prefer list_competition_pages in the
kllm module (no Playwright required).
6-step workflow:
- Verify credentials
- Gather competition list across all categories
- Get structured details per competition (files, leaderboard, kernels)
- Scrape problem statements, evaluation metrics, writeups via Playwright
- Compose markdown report with Methods & Insights analysis
- Present inline
python3 modules/comp-report/scripts/list_competitions.py --lookback-days 30 --output json
python3 modules/comp-report/scripts/competition_details.py --slug SLUG
Read modules/comp-report/README.md for full details including hackathon handling.
Module: Kaggle Interaction (kllm)
Four methods to interact with kaggle.com:
| Method | Best For |
|---|---|
| kagglehub | Quick dataset/model download in Python |
| kaggle-cli | Full workflow scripting |
| MCP Server | AI agent integration |
| Kaggle UI | Account setup, verification |
Capability matrix:
| Task | kagglehub | kaggle-cli | MCP | UI |
|---|---|---|---|---|
| Download dataset | dataset_download() | datasets download | Yes | Yes |
| Download model | model_download() | models instances versions download | Yes | Yes |
| Execute notebook | — | kernels push/status/output | Yes | Yes |
| Submit to competition | — | competitions submit | Yes | Yes |
| Publish dataset | dataset_upload() | datasets create | Yes | Yes |
| Publish model | model_upload() | models create | Yes | Yes |
Known issues:
dataset_load()broken in kagglehub v0.4.3 — usedataset_download()+pd.read_csv()competitions downloadhas no--unzipin CLI >= 1.8- Competition-linked datasets return 403 — use standalone copies
Read modules/kllm/README.md for full details and all task workflows.
Sub-module: kllm/hackathon
Retrieves hackathon writeups, rules, and judging rubrics from Kaggle's MCP hackathon endpoints. Lives under kllm because it's a focused MCP-workflow surface like the rest of kllm. Built around the endpoint order from the 2026-04-22 audit (retested 2026-05-04):
get_hackathon_overview— rules, eligibility, rubric, prizeslist_hackathon_write_ups— submission roster (paginated, with track ids)list_hackathon_tracks— resolve numeric track ids to titlesget_writeup— preferred full-body fetch (simpler arg shape thanget_hackathon_write_up)get_writeup_by_topic/get_writeup_by_slug— fallbacks when id missingget_resolved_writeup_links— host/judge-gated link enrichment
python3 modules/kllm/hackathon/scripts/hackathon_overview.py --competition kaggle-measuring-agi
python3 modules/kllm/hackathon/scripts/list_writeups.py --competition kaggle-measuring-agi
python3 modules/kllm/hackathon/scripts/fetch_writeup.py --writeup-id 123456
Live-server status (verified 2026-05-04):
get_hackathon_write_up— was broken in the 2026-04-22 audit, now works.get_benchmark_leaderboard— was permission-blocked in 2026-04-22, now PASS for ordinary KGAT tokens.get_competitionfor classic competitions — now PASS (recovered upstream).download_hackathon_write_upsmay return CSV header only in some host contexts.get_resolved_writeup_linksis role-gated; participants get an explicit denial.
Read modules/kllm/hackathon/README.md for the full retrieval workflow,
role-specific guidance (host/judge vs. participant), and the bundle shape
returned to the agent.
Module: Badge Collector
Systematically earns ~38 automatable Kaggle badges across 5 phases:
| Phase | Name | Badges | Time |
|---|---|---|---|
| 1 | Instant API | ~16 | 5-10 min |
| 2 | Competition | ~7 | 10-15 min |
| 3 | Pipeline | ~3 | 15-30 min |
| 4 | Browser | ~8 | 5-10 min |
| 5 | Streaks | ~4 | Setup only |
python3 modules/badge-collector/scripts/orchestrator.py --dry-run
python3 modules/badge-collector/scripts/orchestrator.py --phase 1
python3 modules/badge-collector/scripts/orchestrator.py --status
Read modules/badge-collector/README.md for full details.
Orchestration Workflow
This skill is primarily a reference — use the modules and scripts as needed based on the user's request. When explicitly asked to run the full Kaggle workflow, follow these steps:
Step 1: Check Credentials
python3 shared/check_all_credentials.py
If any credentials are missing, walk through the registration module. Never echo or log actual credential values.
Step 2: Generate Competition Landscape Report
Run the comp-report workflow: list competitions, get details, scrape with Playwright, compose report. Output inline.
Step 3: Summarize Kaggle Interaction Methods
Present a concise summary of the four ways to interact with Kaggle (kagglehub, kaggle-cli, MCP Server, UI) with the capability matrix from the kllm module.
Step 4: Present Interactive Menu
Ask the user what they'd like to do next:
- Earn Kaggle badges — Run the badge collector (5 phases, ~38 automatable badges)
- Explore recent competitions — Dive deeper into specific competitions from the report
- Enter a Kaggle competition — Register, download data, build a submission, submit
- Download a Kaggle dataset — Search for and download any public dataset