Record a web app workflow on a desktop with a visible system cursor. It produces an MP4 video and a separate log of clicks, hovers, scrolling, and typing, and can re-record existing demo scripts.
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Turn a product idea into a PRD, a product requirements document, through focused questions about the problem, scope, success, and user journeys. Record whether to proceed and produce a Markdown file before technical design begins.
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Monitor automated build and test runs in Nx Cloud, review suggested fixes, and apply or improve them when runs fail. Set monitoring limits and approval preferences, then follow subsequent runs to check the outcome.
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Explore and configure an Nx monorepo, where multiple projects share one repository. Inspect resolved project settings, identify projects affected by changes, and improve project boundaries, build caching, and CI/CD pipelines.
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Review a pull request using repository checks, verified code references, and current official documentation. Assess correctness, security, structure, and unnecessary code, then post one consolidated GitHub review with inline findings and an evidence-based verdict.
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Investigate failing GitHub Actions checks on a pull request using the GitHub CLI. The skill gathers logs, summarizes failures, and proposes a fix plan, then implements changes only after explicit approval and reports changes and tests.
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Write, review, and refactor React and Next.js code using performance guidelines from Vercel Engineering. Prioritize improvements to data fetching, downloaded code size, server processing, and unnecessary rendering, with rule files providing explanations and code examples.
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Run builds, tests, code checks, and development servers in an Nx workspace. Choose one project, several projects, or projects affected by changes, with options for parallel execution, cached results, and failure handling.
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Create, audit, and improve pages for AI search engines by checking crawl access, metadata, clear answers, sources, and structured data that describes page content. It produces prioritized fixes and citation-friendly pages without guaranteeing inclusion in AI answers.
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Analyze git history to map contributors to security-sensitive files and identify ownership gaps. Estimate bus factor, a measure of dependence on few people, group files that change together, and export CSV or JSON for further analysis.
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Turn descriptions or code analysis into Mermaid diagrams for workflows, system architecture, and database relationships. Check diagram syntax and export SVG, PNG, or text-based ASCII output, with themes and batch rendering options.
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Define ideal customers and a clear market position for an AI product. Use customer evidence to separate customer fit from buying intent, turn technical capabilities into business messages, and plan recurring checks of product-market fit.
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Review Python, JavaScript/TypeScript, and Go code against security guidance for the languages and frameworks in use. Identify important weaknesses, suggest improvements, and produce prioritized reports with code references, or apply secure defaults when writing new code.
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Create a Markdown threat model grounded in a codebase. Identify valuable assets, boundaries between trusted and untrusted components, realistic attack paths, and mitigations, then prioritize risks using explicit assumptions about likelihood and impact.
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Plan personalized video outreach for prospective customers, from useful sample deliverables and short scripts to tool selection and follow-up sequences. Use viewing data to guide next steps and design product demos prospects can watch independently.
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Improve how search engines discover and understand a website by reviewing titles, descriptions, links, and sitemaps. Add structured data, machine-readable descriptions of page content, and use checklists to identify technical and on-page SEO issues.
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Measure website performance with Lighthouse, interpret scores and reports, and compare results across builds. Set limits for loading times and resource sizes, then integrate audits into CI, an automated workflow that checks code changes.
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Plan AI sales development systems that qualify prospects, organize outreach, classify replies, and hand opportunities to people. Use customer criteria, budget, CRM setup, and sales goals to shape platform choices and a four-week rollout plan.
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Plan AI-assisted SEO, from keyword research and competitor comparison pages to content production using data and templates. It also guides content changes for AI search citations, tool selection, quality checks, and ongoing performance tracking.
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Plan UGC campaigns, ads built around user-style content, from creator recruitment and production briefs to AI video variations. Organize organic testing, paid promotion, and creative refreshes for TikTok, Meta, and YouTube Shorts.
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Design a content marketing system that connects posts, videos, and newsletters to sales opportunities. It helps analyze successful content, adapt one core piece for multiple platforms, plan follow-up conversations, and measure which content contributes to deals.
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Design automation for sales and marketing workflows, including lead scoring, routing, CRM updates, and AI agent tasks. The skill helps choose platforms, organize shared customer context, and define monitoring and feedback loops around team needs and budget.
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Choose metrics for AI product revenue, sales efficiency, retention, and computing costs. Plan dashboards and weekly reviews, assess customer data quality, and decide how to credit marketing and sales interactions for completed deals.
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Plan a product launch across discovery sites, social media, and communities. Select channels for the intended audience, build a waitlist, prepare launch materials, coordinate launch-day activities, and organize follow-up promotion and measurement.
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