kaggle

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, badge collection, and general Kaggle questions. Four integrated modules working together. Overlap guard: For hackathon grading evaluation and alignment analysis, use the kaggle-hackathon-grading skill instead. 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 with Playwright scraping kllm Core Kaggle interaction (kagglehub, CLI, MCP, UI) badge-collector Systematic badge earning across 5 phases Credential Setup Always run the credential checker first: python3 skills/kaggle/shared/check_all_credentials.py Three credential types are needed for full compatibility: Variable Format Purpose KAGGLE_USERNAME Kaggle handle Identity for all tools KAGGLE_KEY 32-char hex Legacy key (CLI, kagglehub, most MCP) KAGGLE_API_TOKEN KGAT_ -prefixed Scoped token (some MCP endpoints) 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 all three API credentials. Saves to .env and ~/.kaggle/kaggle.json . Key commands: python3 skills/kaggle/modules/registration/scripts/check_registration.py bash skills/kaggle/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 + Playwright MCP tools for SPA content. 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 skills/kaggle/modules/comp-report/scripts/list_competitions.py --lookback-days 30 --output json python3 skills/kaggle/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 — use dataset_download() + pd.read_csv() competitions download has no --unzip in CLI >= 1.8 Competition-linked datasets return 403 — use standalone copies Read modules/kllm/README.md for full details and all task workflows. 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 skills/kaggle/modules/badge-collector/scripts/orchestrator.py --dry-run python3 skills/kaggle/modules/badge-collector/scripts/orchestrator.py --phase 1 python3 skills/kaggle/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 skills/kaggle/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 Download a Kaggle model — Download pre-trained models (LLMs, CV, etc.) Run a notebook on Kaggle — Push and execute a notebook on KKB with free GPU/TPU Publish to Kaggle — Upload a dataset, model, or notebook Learn about Kaggle progression — Tiers, medals, how to rank up Something else — Free-form Kaggle help Step 5: Execute and Continue Handle the user's choice using the appropriate module, then loop back to offer more options. Security Never commit .env , kaggle.json , or any credential files Never echo or log actual credential values in terminal output The .gitignore excludes .env , kaggle.json , and related files Set file permissions: chmod 600 .env ~/.kaggle/kaggle.json If credentials are accidentally exposed, rotate them immediately at https://www.kaggle.com/settings Scope of Operations This skill performs both read-only and write operations on kaggle.com. Read-only operations (no account side-effects): List/search competitions, datasets, models, notebooks Download datasets, models, competition data View leaderboards, competition details, badge progress Generate competition landscape reports Write operations (create or modify resources on your account): Create/publish datasets, notebooks, models (always private by default) Submit predictions to competitions Push and execute notebooks on Kaggle Kernel Backend (KKB) Earn badges through API activity (profile-visible) Phase 5 (Streaks) generates a local shell script for daily execution but does not auto-install cron jobs or launchd plists. Users must manually configure scheduling if desired. Scripts Index Shared: shared/check_all_credentials.py — Unified credential checker (all 3 types) Registration: modules/registration/scripts/check_registration.py — Check all 3 credentials modules/registration/scripts/setup_env.sh — Auto-configure credentials from env/dotenv Competition Reports: modules/comp-report/scripts/utils.py — Credential check, API init, rate limiting modules/comp-report/scripts/list_competitions.py — Fetch competitions across categories modules/comp-report/scripts/competition_details.py — Files, leaderboard, kernels per competition Kaggle Interaction (kllm): modules/kllm/scripts/setup_env.sh — Auto-configure credentials (with .env loading) modules/kllm/scripts/check_credentials.py — Verify and auto-map credentials modules/kllm/scripts/network_check.sh — Check Kaggle API reachability modules/kllm/scripts/cli_download.sh — Download datasets/models via CLI modules/kllm/scripts/cli_execute.sh — Execute notebook on KKB modules/kllm/scripts/cli_competition.sh — Competition workflow (list/download/submit) modules/kllm/scripts/cli_publish.sh — Publish datasets/notebooks/models modules/kllm/scripts/poll_kernel.sh — Poll kernel status and download output modules/kllm/scripts/kagglehub_download.py — Download via kagglehub modules/kllm/scripts/kagglehub_publish.py — Publish via kagglehub Badge Collector: modules/badge-collector/scripts/orchestrator.py — Main entry point modules/badge-collector/scripts/badge_registry.py — 59 badge definitions modules/badge-collector/scripts/badge_tracker.py — Progress persistence modules/badge-collector/scripts/utils.py — Shared utilities modules/badge-collector/scripts/phase_1_instant_api.py — Instant API badges modules/badge-collector/scripts/phase_2_competition.py — Competition badges modules/badge-collector/scripts/phase_3_pipeline.py — Pipeline badges modules/badge-collector/scripts/phase_4_browser.py — Browser badges modules/badge-collector/scripts/phase_5_streaks.py — Streak automation References Index modules/registration/references/kaggle-setup.md — Full credential setup guide with troubleshooting modules/comp-report/references/competition-categories.md — Competition types and API mapping modules/kllm/references/kaggle-knowledge.md — Comprehensive Kaggle platform knowledge modules/kllm/references/kagglehub-reference.md — Full kagglehub Python API reference modules/kllm/references/cli-reference.md — Complete kaggle-cli command reference modules/kllm/references/mcp-reference.md — Kaggle MCP server reference modules/badge-collector/references/badge-catalog.md — Complete 59-badge catalog