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Found 1,637 Skills
Apply Web Scraping with Python practices (Ryan Mitchell). Covers First Scrapers (Ch 1: urllib, BeautifulSoup), HTML Parsing (Ch 2: find, findAll, CSS selectors, regex, lambda), Crawling (Ch 3-4: single-domain, cross-site, crawl models), Scrapy (Ch 5: spiders, items, pipelines, rules), Storing Data (Ch 6: CSV, MySQL, files, email), Reading Documents (Ch 7: PDF, Word, encoding), Cleaning Data (Ch 8: normalization, OpenRefine), NLP (Ch 9: n-grams, Markov, NLTK), Forms & Logins (Ch 10: POST, sessions, cookies), JavaScript (Ch 11: Selenium, headless, Ajax), APIs (Ch 12: REST, undocumented), Image/OCR (Ch 13: Pillow, Tesseract), Avoiding Traps (Ch 14: headers, honeypots), Testing (Ch 15: unittest, Selenium), Parallel (Ch 16: threads, processes), Remote (Ch 17: Tor, proxies), Legalities (Ch 18: robots.txt, CFAA, ethics). Trigger on "web scraping", "BeautifulSoup", "Scrapy", "crawler", "spider", "scraper", "parse HTML", "Selenium scraping", "data extraction".
Use when modeling structured string patterns. Use when parsing DSLs like CSS selectors. Use when transforming string types. Use when validating string formats. Use when combining with mapped types.
Initialize the Platonic Coding system for any project. Scaffolds specs infrastructure (.platonic.yml, RFC templates, impl guide directory) and scans existing codebases to recover missing conceptual and architecture design specs as Draft RFCs. Use when adopting platonic coding for a new or existing project.
Scans code against 17 named design smells and produces a structured diagnostic report. Use when reviewing a PR for design quality, evaluating unfamiliar code against a comprehensive checklist or when the user asks for a red flags scan. Not for diagnosing why code feels complex (use complexity-recognition) or evaluating whether a PR maintains design trajectory (use code-evolution).
Evaluate and validate Claude Code rules in .claude/rules/ directories. Use when auditing rule file quality, validating frontmatter and glob patterns, or checking rules organization before deployment. Do not use when writing new rules from scratch - use rule authoring guides instead. Do not use when evaluating skills or hooks - use skills-eval or hooks-eval instead.
Fast file finding using fd command-line tool with smart defaults, gitignore awareness, and parallel execution. Use when searching for files by name, extension, or pattern across directories.
Use when adding LangChain-based LLM routes or services in Python or Next.js stacks; pair with architect-stack-selector.
Use when every architecture and implementation decision must be traceable with explicit rationale; pair with architect-stack-selector and addon-human-pr-review-gate.
INVOKE THIS SKILL when building evaluation pipelines for LangSmith. Covers three core components: (1) Creating Evaluators - LLM-as-Judge, custom code; (2) Defining Run Functions - how to capture outputs and trajectories from your agent; (3) Running Evaluations - locally with evaluate() or auto-run via LangSmith. Uses the langsmith CLI tool.
INVOKE THIS SKILL when creating evaluation datasets, uploading datasets to LangSmith, or managing existing datasets. Covers dataset types (final_response, single_step, trajectory, RAG), CLI management commands, SDK-based creation, and example management. Uses the langsmith CLI tool.
A comprehensive skill for using agent-browser, a CLI tool for browser automation designed for AI agents, developed by Vercel Labs. This skill covers installation, core commands, selectors (refs, CSS, XPath, semantic locators), agent mode, sessions, options, and best practices. Use this skill whenever the user needs to automate browser interactions via CLI commands, especially for AI agents that need to interact with web pages.
When the user wants to create, optimize, or audit blog page structure and content. Also use when the user mentions "blog page," "blog index," "blog layout," "content hub," "blog homepage," "blog listing," "subdomain vs subdirectory," "blog structure," or "blog SEO."