kaggle

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Original

English

🇨🇳

Translation

Chinese

Kaggle — Unified Skill

Kaggle — 统一技能

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

为任何LLM或智能编码系统（Claude Code、gemini-cli、Cursor等）提供完整的Kaggle集成支持：涵盖账户设置、竞赛报告、数据集/模型下载、Notebook执行、竞赛提交、徽章收集以及各类Kaggle相关通用问题。由四个集成模块协同工作。

重叠防护： 若用于黑客松评分评估和一致性分析，请使用kaggle-hackathon-grading技能替代。

网络要求： 需能对外访问HTTPS地址

api.kaggle.com

、

www.kaggle.com

和

storage.googleapis.com

。

Modules

模块

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

模块	用途
registration	账户创建、API密钥生成、凭证存储
comp-report	基于Playwright爬取的竞赛格局报告
kllm	核心Kaggle交互（kagglehub、CLI、MCP、UI）
badge-collector	分5个阶段系统性获取徽章

Credential Setup

凭证设置

Always run the credential checker first:

bash

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.

请始终先运行凭证检查工具：

bash

python3 skills/kaggle/shared/check_all_credentials.py

完整兼容需要三种类型的凭证：

变量	格式	用途
`KAGGLE_USERNAME`	Kaggle用户名	所有工具的身份标识
`KAGGLE_KEY`	32位十六进制字符串	传统密钥（适用于CLI、kagglehub、大多数MCP场景）
`KAGGLE_API_TOKEN`	以 `KGAT_` 为前缀	范围限定令牌（适用于部分MCP端点）

若缺少任何凭证，请遵循注册指南操作：查看

modules/registration/README.md

获取完整分步指引。

安全提示： 切勿回显、记录或提交实际凭证值。

Module: Registration

模块：注册

Walks users through creating a Kaggle account and generating all three API credentials. Saves to

.env

and

~/.kaggle/kaggle.json

Key commands:

bash

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.

引导用户完成Kaggle账户创建及所有三种API凭证的生成流程。将凭证保存至

.env

和

~/.kaggle/kaggle.json

。

关键命令：

bash

python3 skills/kaggle/modules/registration/scripts/check_registration.py
bash skills/kaggle/modules/registration/scripts/setup_env.sh

查看

modules/registration/README.md

获取完整操作指南。

Module: Competition Reports

模块：竞赛报告

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

bash

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.

生成近期Kaggle竞赛活动的全面格局报告。结合Python API获取元数据，以及Playwright MCP工具爬取SPA内容。

6步工作流：

验证凭证
收集全品类竞赛列表
获取每个竞赛的结构化详情（文件、排行榜、代码内核）
通过Playwright爬取问题描述、评估指标、技术文档
撰写包含方法与洞察分析的Markdown报告
在线展示报告

bash

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

查看

modules/comp-report/README.md

获取完整详情，包括黑客松场景处理方式。

Module: Kaggle Interaction (kllm)

模块：Kaggle交互（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.

提供四种与kaggle.com交互的方式：

方式	适用场景
kagglehub	Python环境下快速下载数据集/模型
kaggle-cli	全流程脚本化操作
MCP Server	AI Agent集成
Kaggle UI	账户设置、验证操作

能力矩阵：

任务	kagglehub	kaggle-cli	MCP	UI
下载数据集	`dataset_download()`	`datasets download`	支持	支持
下载模型	`model_download()`	`models instances versions download`	支持	支持
执行Notebook	—	`kernels push/status/output`	支持	支持
提交竞赛结果	—	`competitions submit`	支持	支持
发布数据集	`dataset_upload()`	`datasets create`	支持	支持
发布模型	`model_upload()`	`models create`	支持	支持

已知问题：

kagglehub v0.4.3中
```
dataset_load()
```
功能损坏 — 请使用
```
dataset_download()
```
+
```
pd.read_csv()
```
替代
CLI版本 >=1.8时
```
competitions download
```
命令无
```
--unzip
```
参数
竞赛关联数据集返回403错误 — 请使用独立副本

查看

modules/kllm/README.md

获取完整详情及所有任务工作流。

Module: Badge Collector

模块：徽章收集器

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

bash

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.

分5个阶段系统性获取约38个可自动化获取的Kaggle徽章：

阶段	名称	徽章数量	耗时
1	即时API类	~16	5-10分钟
2	竞赛类	~7	10-15分钟
3	工作流类	~3	15-30分钟
4	浏览器操作类	~8	5-10分钟
5	连续操作类	~4	仅需初始设置

bash

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

查看

modules/badge-collector/README.md

获取完整详情。

Orchestration Workflow

编排工作流

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:

本技能主要作为参考工具使用 — 根据用户需求选用相应模块和脚本。当用户明确要求运行完整Kaggle工作流时，请遵循以下步骤：

Step 1: Check Credentials

步骤1：检查凭证

bash

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.

bash

python3 skills/kaggle/shared/check_all_credentials.py

若缺少任何凭证，请引导用户完成注册模块流程。切勿回显或记录实际凭证值。

Step 2: Generate Competition Landscape Report

步骤2：生成竞赛格局报告

Run the comp-report workflow: list competitions, get details, scrape with Playwright, compose report. Output inline.

运行comp-report工作流：列出竞赛、获取详情、通过Playwright爬取内容、撰写报告。在线输出报告。

Step 3: Summarize Kaggle Interaction Methods

步骤3：总结Kaggle交互方式

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.

简要介绍四种与Kaggle交互的方式（kagglehub、kaggle-cli、MCP Server、UI），并展示kllm模块中的能力矩阵。

Step 4: Present Interactive Menu

步骤4：展示交互式菜单

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

询问用户下一步操作：

获取Kaggle徽章 — 运行徽章收集器（5个阶段，约38个可自动化获取的徽章）
探索近期竞赛 — 深入分析报告中的特定竞赛
参与Kaggle竞赛 — 注册、下载数据、构建提交结果、提交竞赛
下载Kaggle数据集 — 搜索并下载任意公开数据集
下载Kaggle模型 — 下载预训练模型（LLM、CV等）
在Kaggle上运行Notebook — 推送并在KKB上执行Notebook，使用免费GPU/TPU
发布内容至Kaggle — 上传数据集、模型或Notebook
了解Kaggle进阶体系 — 等级、奖牌、晋升方式
其他需求 — 自定义Kaggle相关帮助

Step 5: Execute and Continue

步骤5：执行并循环

Handle the user's choice using the appropriate module, then loop back to offer more options.

使用对应模块处理用户选择，然后返回菜单提供更多选项。

Security

安全注意事项

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

切勿提交
```
.env
```
、
```
kaggle.json
```
或任何凭证文件
切勿在终端输出中回显或记录实际凭证值
```
.gitignore
```
已排除
```
.env
```
、
```
kaggle.json
```
及相关文件
设置文件权限：
```
chmod 600 .env ~/.kaggle/kaggle.json
```
若凭证意外泄露，请立即在https://www.kaggle.com/settings页面轮换凭证

Scope of Operations

操作范围

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.

本技能可在kaggle.com上执行只读和写入操作。

只读操作（无账户副作用）：

列出/搜索竞赛、数据集、模型、Notebook
下载数据集、模型、竞赛数据
查看排行榜、竞赛详情、徽章进度
生成竞赛格局报告

写入操作（在账户中创建或修改资源）：

创建/发布数据集、Notebook、模型（默认设为私有）
提交竞赛预测结果
在Kaggle Kernel Backend（KKB）上推送并执行Notebook
通过API活动获取徽章（将显示在个人主页）

阶段5（连续操作类）会生成本地Shell脚本用于每日执行，但不会自动安装cron任务或launchd配置。用户需手动配置调度任务（若需要）。

Scripts Index

脚本索引

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

共享脚本：

```
shared/check_all_credentials.py
```
— 统一凭证检查工具（支持所有3种凭证类型）

注册模块：

modules/registration/scripts/check_registration.py

— 检查所有3种凭证

```
modules/registration/scripts/setup_env.sh
```
— 从环境变量/.env自动配置凭证

竞赛报告模块：

```
modules/comp-report/scripts/utils.py
```
— 凭证检查、API初始化、速率限制

modules/comp-report/scripts/list_competitions.py

— 获取全品类竞赛列表

```
modules/comp-report/scripts/competition_details.py
```
— 获取单个竞赛的文件、排行榜、代码内核信息

Kaggle交互模块（kllm）：

```
modules/kllm/scripts/setup_env.sh
```
— 自动配置凭证（支持加载.env文件）

modules/kllm/scripts/check_credentials.py

— 验证并自动映射凭证

```
modules/kllm/scripts/network_check.sh
```
— 检查Kaggle API可达性
```
modules/kllm/scripts/cli_download.sh
```
— 通过CLI下载数据集/模型
```
modules/kllm/scripts/cli_execute.sh
```
— 在KKB上执行Notebook
```
modules/kllm/scripts/cli_competition.sh
```
— 竞赛工作流（列出/下载/提交）
```
modules/kllm/scripts/cli_publish.sh
```
— 发布数据集/Notebook/模型
```
modules/kllm/scripts/poll_kernel.sh
```
— 轮询内核状态并下载输出结果

modules/kllm/scripts/kagglehub_download.py

— 通过kagglehub下载内容

modules/kllm/scripts/kagglehub_publish.py

— 通过kagglehub发布内容

徽章收集器模块：

modules/badge-collector/scripts/orchestrator.py

— 主入口脚本

modules/badge-collector/scripts/badge_registry.py

— 59个徽章的定义信息

modules/badge-collector/scripts/badge_tracker.py

— 进度持久化工具

modules/badge-collector/scripts/utils.py

— 共享工具函数

modules/badge-collector/scripts/phase_1_instant_api.py

— 即时API类徽章获取

modules/badge-collector/scripts/phase_2_competition.py

— 竞赛类徽章获取

modules/badge-collector/scripts/phase_3_pipeline.py

— 工作流类徽章获取

modules/badge-collector/scripts/phase_4_browser.py

— 浏览器操作类徽章获取

modules/badge-collector/scripts/phase_5_streaks.py

— 连续操作类自动化

References Index

参考文档索引

```
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

modules/registration/references/kaggle-setup.md

— 完整凭证设置指南及故障排除

modules/comp-report/references/competition-categories.md

— 竞赛类型及API映射

modules/kllm/references/kaggle-knowledge.md

— 全面的Kaggle平台知识

modules/kllm/references/kagglehub-reference.md

— 完整的kagglehub Python API参考

modules/kllm/references/cli-reference.md

— 完整的kaggle-cli命令参考

modules/kllm/references/mcp-reference.md

— Kaggle MCP服务器参考

modules/badge-collector/references/badge-catalog.md

— 完整的59个徽章目录