By tonone-ai
Writes landing page and marketing copy: hero sections, problem/solution blocks, proof points, and CTAs for homepages, feature pages, and product surfaces.
Based on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
npx claudepluginhub tonone-ai/tonone --plugin pitch-copy|
Product, legal, and business specialists - product strategy, licensing, project management, UX research
App launch preparation toolkit with SEO analysis, automated screenshots across viewports, buyer persona creation, social media ad generation, technical article writing, and landing page proposals. Orchestrates all marketing deliverables.
Engineering process for solo founders and teams up to 50 engineers. Agents do architecture, code review, QA, and security. You make two decisions per feature.
Your virtual AI team. Treats your solopreneur workflow as a virtual company with specialized AI employees, SOPs, team meetings, and performance reviews.
Toolkit for solo developers to build, manage, and grow their business - customer profiling, brand guidelines, design system, SEO strategy, X/Twitter growth strategy, and more
Design and build networking infrastructure — VPCs, subnets, DNS, load balancers, firewall rules. Use when asked to "set up networking", "VPC design", "configure DNS", "load balancer setup", "network architecture", or "firewall rules".
Generate onboarding documentation — what this project does, how to set up locally, where things live, key decisions, how to deploy. Written for day-one engineers who know nothing. Use when asked for "onboarding docs", "new engineer guide", "how to get started", or "developer setup".
Implement a reusable, accessible, typed component from a design spec. Use when asked to "create a component", "build a widget", "implement this design", or "reusable UI element".
Verify observability posture — audit monitoring coverage, find blind spots, prioritize gaps. Use when asked "is monitoring sufficient", "observability review", "are we covered", or "pre-launch monitoring check".
ML reconnaissance — inventory all models, pipelines, data sources, and monitoring. Use when asked "what ML do we have", "model inventory", or "ML assessment".