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Found 4,751 Skills
Unified portfolio dashboard. Traffic, revenue, errors - all products at a glance. Weekly traction check in 2 minutes. Auto-invoke when: user asks about metrics, traction, analytics, revenue across products.
Executes implementation plans with smart task grouping. Groups related tasks to share context, parallelizes across independent subsystems.
Estimate fair market rates for creator partnerships based on platform, follower count, engagement rate, niche, and deliverable type. This skill should be used when estimating influencer rates, calculating creator pricing, building a rate card for a campaign, checking if a creator's rate is fair, comparing influencer costs across platforms, budgeting for a creator campaign, evaluating a creator's rate card, figuring out how much to pay an influencer, benchmarking creator rates against market data, or assessing whether a creator is overcharging. For negotiating rates after estimation, see rate-negotiation-playbook. For full creator vetting beyond pricing, see creator-vetting-scorecard.
Conduct rigorous, adversarial code reviews with zero tolerance for mediocrity. Use when users ask to "critically review" my code or a PR, "critique my code", "find issues in my code", or "what's wrong with this code". Identifies security holes, lazy patterns, edge case failures, and bad practices across Python, R, JavaScript/TypeScript, SQL, and front-end code. Scrutinizes error handling, type safety, performance, accessibility, and code quality. Provides structured feedback with severity tiers (Blocking, Required, Suggestions) and specific, actionable recommendations.
One-click comprehensive analysis of cryptocurrencies. Collect data from five dimensions - price, news sentiment, sector comparison, market environment, and project fundamentals - through parallel sub-agents, and output an HTML report (including 24-hour market trends and 7-day trends) after cross-analysis. Trigger phrases: Analyze BTC, analyze ETH, How is Bitcoin?, Is SOL worth buying?
Migrate existing Python projects to uv from pip, Poetry, Pipenv, or Conda. Learn how to convert dependency files, preserve development environment setup, validate the migration, and plan team rollout. Use when converting legacy projects to modern uv tooling, consolidating different package managers, or standardizing Python development workflows across teams.
Intelligent README.md generation prompt that analyzes project documentation structure and creates comprehensive repository documentation. Scans .github/copilot directory files and copilot-instructions.md to extract project information, technology stack, architecture, development workflow, coding standards, and testing approaches while generating well-structured markdown documentation with proper formatting, cross-references, and developer-focused content.
Code quality gatekeeper and auditor. Enforces strict quality gates, resolves the AI verification gap, and evaluates codebases across 12 critical dimensions with evidence-based scoring. Use when auditing code quality, reviewing AI-generated code, scoring codebases against industry standards, or enforcing pre-commit quality gates. Use for quality audit, code review, codebase evaluation, security assessment, technical debt analysis.
This skill generates a structured chapter outline for intelligent textbooks by analyzing course descriptions, learning graphs, and concept dependencies. Use this skill after the learning graph has been created and before generating chapter content, to design an optimal chapter structure that respects concept dependencies and distributes content evenly across all of the chapter in a book.
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".
UI/UX design intelligence with page standards & audit mode. 85 styles, 115 palettes, 72 font pairings, 35 charts, 61 components, 50 animations, 57 WCAG criteria, 42 responsive patterns, 40 dark mode rules, 51 design tokens, 13 stacks, 15 page types with mandatory sections, 44 audit rules, SEO per page type. Actions: plan, build, create, design, implement, review, fix, improve, optimize, enhance, refactor, check, audit. Styles: glassmorphism, brutalism, neumorphism, bento, dark mode, view transitions, scroll-driven, container queries, AI-native, liquid glass. Topics: color, accessibility, animation, layout, typography, spacing, shadow, gradient, responsive, dark mode, WCAG 2.2, design tokens, components, page standards, navigation, SEO, auth, empty states.
Blog strategy development including topic cluster architecture with hub-and-spoke design, audience mapping, competitive landscape analysis, AI citation surface strategy across ChatGPT/Perplexity/AI Overviews, distribution channel planning (YouTube, Reddit, review platforms for GEO), content scoring targets, measurement framework, and content differentiation through original research and first-hand experience. Use when user says "blog strategy", "content strategy", "blog positioning", "what should I blog about", "blog topics", "content pillars", "blog ideation".