By tonone-ai
Builds SEO strategies with keyword research, topic clusters, competitor gap analysis, on-page audits, and prioritized roadmaps for product sites.
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npx claudepluginhub tonone-ai/tonone --plugin ink-seoContent marketing reconnaissance — audit current content, SEO health, competitor content gaps, and content distribution. Use when asked to "audit our content", "what's our SEO state", "where are the content gaps", or before designing a content strategy.
Editorial "SEO Specialist" bundle for Claude Code from Antigravity Awesome Skills.
SEO analysis with authority building, cannibalization detection, and content refresh
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
59 expert skills for non-technical founders building SaaS with AI tools. Covers the full lifecycle: planning, design, build, database, integrations, AI features, security, testing, debugging, deployment, monitoring, plus marketing, pricing, growth, and business strategy.
For easy problems, start here. For harder problems, do this after Explore.
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".