Search Kaggle datasets, competitions, notebooks, and models through its official command-line tool. Download public data into a chosen directory and preserve audit records and file hashes, identifiers used to check downloaded files.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Use when a research task needs reproducible Kaggle discovery, metadata inspection, bounded public-data downloads, competition or kernel discovery, model discovery, or an explicitly approved Kaggle write/delete operation through the official CLI.
실행 점수 미검증
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Use the official Kaggle CLI through the policy-enforcing wrapper in this skill. The wrapper records bounded, redacted audit data; confines downloads to an approved directory; and blocks remote mutation unless the user explicitly authorizes it.
Confirm the requested Kaggle resource and whether the action is read, download, write, or delete. Do not broaden user authority.
Use an isolated Python 3.11+ environment with kaggle>=2.2,<3.
Configure Kaggle authentication outside commands and source files. Never read, print, echo, log, or commit credential values.
Run the non-mutating prerequisite check:
python scripts/kaggle_research.py doctor --json
Run discovery commands before downloads or mutations. Keep every download under an explicitly chosen output root.
Preserve generated audit JSON and artifact hashes with the research outputs.
Report exact commands, resource references, timestamps, failures, and generated artifacts. Distinguish verified observations from assumptions.
Pass Kaggle arguments after -- so their order is preserved:
python scripts/kaggle_research.py run --audit artifacts/audit.json -- datasets list -s iris -v
python scripts/kaggle_research.py run --output-root artifacts/kaggle -- datasets download -d owner/dataset
Preview any potentially mutating command first:
python scripts/kaggle_research.py run --dry-run --allow-write -- datasets create -p dataset-package
An actual remote write additionally requires explicit user authorization and
--allow-write. A delete additionally requires --allow-delete and
--confirm-resource matching the exact resource classified by the wrapper.
The runtime never retries writes or deletes.
The live smoke workflow calls Kaggle's real service, inspects all supported resource groups, downloads a small public dataset, and verifies its hash:
python scripts/kaggle_research.py smoke-readonly --output-root artifacts/kaggle-smoke --report artifacts/kaggle-smoke-report.json
The corresponding integration test is opt-in so normal unit tests do not depend on network access:
AERS_KAGGLE_LIVE=1 python -m unittest discover -s tests -p "test_live_readonly.py" -v
Only run the live lane when credentials are already available in the process environment. It must remain read/download-only.
Read only the reference page required for the active task.
아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
로그인 없이 쓸 수 있습니다. 사용 후기, 질문, 작동하지 않은 환경 등을 편하게 남겨 주세요.
아직 댓글이 없습니다. 첫 댓글을 남겨 보세요.
Turn a broad research idea into clear, testable questions. Compare familiar and less conventional approaches, structure the selected question around its population and methods, and assess variables, feasibility, and potential theoretical contributions.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Helps build a research framework by comparing theories, mapping relationships between variables, and deriving testable hypotheses. Explores less conventional options, examines weaknesses and competing explanations, and produces diagrams with anticipated reviewer objections.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Clarify the philosophical assumptions behind a research project and check whether they fit the proposed methods. Get a reasoned research stance, draft proposal wording, and guidance for explaining how the researcher's background and values shape the study.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Plan and draft academic papers through specialized agent roles covering literature, arguments, citations, and review. Get chapter guidance, revision roadmaps, Traditional Chinese and English abstracts, and documents formatted as LaTeX, DOCX, PDF, or Markdown.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Turn a detailed outline into a philosophy or interdisciplinary manuscript. Draft chapters with repeated quality reviews, check terminology and arguments across sections, and prepare the manuscript, evaluation reports, abstract, and metadata for submission.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.
Simulate academic peer review through five reviewer roles tailored to the paper's field. Receive separate critiques, an editorial decision, and a prioritized revision roadmap, or check whether a revised manuscript addresses earlier comments.
한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.