kandada/skills/data_cleaning
skills/data_cleaning/SKILL.md
# Data Cleaning Skill ## 描述 数据清洗工具，处理缺失值、去除重复项、数据格式标准化等。 ## 调用示例： Action: clean_data Action Input: {"file_path": "data.csv", "operations": ["remove_duplicates", "normalize_text"]} ## 输入参数 - `file_path` (str, 必需): 数据文件路径(CSV) - `operations` (list, 必需): 操作列表 - `remove_duplicates`: 去除重复行 - `fill_missing`: 填充缺失值(需指定method) - `normalize_text`: 标准化文本 - `remove_outliers`: 移除异常值 - `convert_types`: 类型转换 - `output_path` (str, 可选): 输出路径 ## 输出 - `success`: 是否成功 - `file_path`: 处理后的文件 - `operat
$ install --global
skillsauthnpx skillsauth add kandada/aacode skills/data_cleaningInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 16, 2026, 6:49 AM4.4s2 files scanned
SKILL.md
Data Cleaning Skill
描述
数据清洗工具，处理缺失值、去除重复项、数据格式标准化等。
调用示例：
Action: clean_data Action Input: {"file_path": "data.csv", "operations": ["remove_duplicates", "normalize_text"]}
输入参数
file_path(str, 必需): 数据文件路径(CSV)operations(list, 必需): 操作列表remove_duplicates: 去除重复行fill_missing: 填充缺失值(需指定method)normalize_text: 标准化文本remove_outliers: 移除异常值convert_types: 类型转换
output_path(str, 可选): 输出路径
输出
success: 是否成功file_path: 处理后的文件operations_performed: 执行的操作stats: 统计信息
Related Skills
kandada/skills/pandas
development
VerifiedTrustedCommunity
## Description Python pandas data analysis. Auto-injects `import pandas as pd; import numpy as np`. Returns DataFrame preview (shape / columns / head). ## Parameters - code: pandas code string to execute; last expression result included in return value ## Example run_skills("pandas", {"code": "pd.read_csv('data.csv').head()"}) run_skills("pandas", {"code": "df = pd.DataFrame({'a': [1,2], 'b': [3,4]}); df.describe()"})
82SKILL.mdUpdated May 8, 2026
kandada/skills/numpy
development
VerifiedTrustedCommunity
## Description Python numpy numerical computing. Auto-injects `import numpy as np`. ## Parameters - code: numpy code string to execute; last expression result included in return value ## Example run_skills("numpy", {"code": "np.array([1,2,3]).mean()"}) run_skills("numpy", {"code": "a = np.random.randn(1000); a.mean(), a.std()"})
82SKILL.mdUpdated May 8, 2026
kandada/skills/web_scraper
development
VerifiedTrustedCommunity
# Web Scraper Skill ## 描述 网页抓取和数据提取工具，支持单页和多页并发抓取。 ## 调用示例： Action: scrape_web Action Input: {"url": "https://example.com", "operations": ["extract_text", "extract_links"]} ## 输入参数 ### scrape_web - `url` (str, 必需): 目标URL - `operations` (list, 必需): 操作列表 [extract_text, extract_links, extract_images, extract_tables, extract_metadata, clean_content] - `selector` (str, 可选): CSS选择器 - `timeout` (int, 可选): 超时时间(秒)，默认30 ### scrape_multiple - `urls` (list, 必需): URL列表 - `operations` (list, 必需): 操作列表 -
82SKILL.mdUpdated Apr 16, 2026
kandada/skills/playwright
tools
VerifiedTrustedCommunity
## Description Browser automation tool using Playwright. Supports dynamic web pages, data extraction, frontend testing, screenshots. ## Parameters - url: Target URL - headless: Headless mode, default true - browser_type: Browser type [chromium, firefox, webkit], default chromium - timeout: Timeout (ms), default 30000 - retry_count: Retry count, default 2 ## Example run_skills("playwright", {"func": "browser_automation", "url": "https://example.com"}) run_skills("playwright", {"func": "take_scr
82SKILL.mdUpdated Apr 16, 2026