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Implementing WCAG accessibility guidelines, semantic HTML5, and screen reader ARIA roles.
How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
基于 SOC 职业分类
正在显示 SKILL.md
| name | beautifulsoup-scraping |
| description | Parsing HTML web structures, searching tags, and extracting text using BeautifulSoup4. |
| allowed-tools | Read Write Edit Bash |
| license | MIT license |
| metadata | {"skill-author":"Lord1Egypt"} |
BeautifulSoup parses raw HTML and XML pages, providing intuitive DOM tree search systems.
Use to parse data out of static web pages or crawled page sources.
from bs4 import BeautifulSoup
import requests
r = requests.get("https://example.com")
soup = BeautifulSoup(r.content, "html.parser")
# Find the primary heading element
heading = soup.find("h1").text
print("Heading Text:", heading)
Search elements using regex patterns, navigate sibling tag nodes, extract attributes, and clean HTML bodies.