By hanamizuki
AI / LLM application engineering expertise. Ships the ai-engineer agent plus in-house skills (langgraph, ai-app-templates) and 1 vendored skill (senior-prompt-engineer) for production LLM systems, RAG, agents, and prompt design.
When starting a new AI backend, check the catalog first for a matching shape.
Understand LangGraph v1.0 thoroughly
Use when the user asks to optimize prompts, design prompt templates, evaluate LLM outputs with an eval set, measure RAG retrieval quality, validate agent/tool configurations, analyze token usage, or design structured-output contracts. Covers eval-driven prompt iteration, RAG metrics (relevance, faithfulness, coverage), agent workflow validation, and token/cost budgeting — all model-agnostic, with three stdlib Python tools.
Uses power tools
Uses Bash, Write, or Edit tools
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solopreneur is a family of Claude Code plugins that gives solo founders the workflows of a full engineering org: plan review, code review loops, automated PR cycles, marketing, design, and platform-specific experts. Install à la carte.
claude plugin marketplace add hanamizuki/solopreneur
claude plugin install solopreneur@solopreneur
Then add whichever roles you need (marketer, designer, ios-dev,
android-dev, ai-engineer, neo4j-dev). See the full install guide
for details and role-based recommendations.
| Plugin | What you get |
|---|---|
solopreneur | 16 in-house skills (review, pipelines, thinking partners, automation) |
marketer | marketer agent + 7 in-house skills (GTM, naming, writing, X/LinkedIn growth, slide design) |
designer | designer agent + 10 vendored design skills (taste-* family + impeccable) |
ios-dev | ios-dev agent + ios-patterns + ios-app-templates (reference apps) + 23 vendored skills (asc-* + iphone-apps) |
android-dev | android-dev agent + android-patterns + 39 vendored skills (Compose + gplay-* + Android official) |
ai-engineer | ai-engineer agent + langgraph + ai-app-templates + 1 vendored skill (senior-prompt-engineer) |
neo4j-dev | neo4j-dev agent + 4 vendored Neo4j skills |
Installing any sub-plugin auto-pulls solopreneur. Requires Claude Code
≥ v2.1.110 for plugin dependency resolution.
Migrating from a previous version? See MIGRATION.md. For per-release, per-plugin notes, see CHANGELOG.md.
Each plugin section describes the bundled skills (in-house and vendored) plus its Requirements: external CLIs, plugins, MCPs, or GitHub apps the plugin's skills and agent integrate with. Hard requirements are called out explicitly; everything else is recommended and degrades gracefully if absent.
solopreneur (core)The foundation. Every other plugin depends on this one. No agent, just 16 skills that wrap the lifecycle around your work.
| Skill | What it does |
|---|---|
/mvp | PM. Drives the full new-product flow end-to-end: brainstorming → PRD visual confirmation → template lookup (auto-discovers *-app-templates in installed plugins) → plan → execution. Use when starting from scratch |
/second-opinion | Advisor. Challenges your plan across 5 dimensions (completeness, consistency, clarity, scope, feasibility) using an independent reviewer |
/tech-vetting | Tech Lead. Vets your technical plan against the latest official docs and platform-specific best practices before you write a single line of code |
/worktree-handoff | Coworker. Creates an isolated git worktree with a CONTEXT.md so the next session picks up exactly where you left off |
/handoff | Scribe. Packages the current session into a self-contained markdown context doc, printed inline so you can copy and paste it into any other agent (Codex, ChatGPT, a fresh Claude session, an agent on another machine). No worktree, no file save |
/preview | Presenter. Turns any proposal / plan / idea into an interactive HTML page, deploys it to Vercel for a protected-by-default review URL (or a public bucket when explicitly requested), with an in-page comment overlay so reviewers can highlight text and leave in-context feedback you can act on directly |
/specialist-review | Code Reviewer. Detects your tech stack, dispatches matching expert agents, and reviews against best-practice skill indices |
/post-mortem | SRE. Traces a bug through git history, finds the root cause commit, produces a structured post-mortem report |
/session-retro | Coach. Reviews the current conversation for mistakes, traces root causes, proposes durable process improvements |
/perspective | Thinking Partner. Switch between thinker perspectives (Musk, Feynman, Munger, Naval, Jobs, Taleb, …) to analyze problems from a different angle |
This repo dogfoods the backlog workflow with public task files under
todos/.
npx claudepluginhub p/hanamizuki-ai-engineer-plugins-ai-engineerUI/UX design expertise. Ships the designer agent and 10 vendored third-party design skills (taste-* archetype family + impeccable).
Android/Kotlin expertise. Ships the android-dev agent, android-patterns, and 39 vendored third-party skills (Compose / architecture / Gradle + 18 gplay-* Google Play Console CLI + 6 official Android team skills).
Core skills: plan review, code review loops, backlog management, and thinking partners.
Neo4j graph database expertise. Ships the neo4j-dev agent and 4 vendored third-party skills (cypher / cypher-guide / migration / cli-tools).
Marketing / brand / writing expertise. Ships the marketer agent plus GTM strategy, naming, X/Twitter & LinkedIn growth, AI-pattern removal, and brand-aware slide design.
🤖 AI Engineer — AI Engineer + LLM Systems Specialist
Core skills: plan review, code review loops, backlog management, and thinking partners.
Use this agent when implementing AI/ML features, integrating language models, building recommendation systems, or adding intelligent automation to applications. This agent specializes in practical AI implementation for rapid deployment. Examples:\n\n<example>\nContext: Adding AI features to an app\nuser: "We need AI-powered content recommendations"\nassistant: "I'll implement a smart recommendation engine. Let me use the ai-engineer agent to build an ML pipeline that learns from user behavior."\n<commentary>\nRecommendation systems require careful ML implementation and continuous learning capabilities.\n</commentary>\n</example>\n\n<example>\nContext: Integrating language models\nuser: "Add an AI chatbot to help users navigate our app"\nassistant: "I'll integrate a conversational AI assistant. Let me use the ai-engineer agent to implement proper prompt engineering and response handling."\n<commentary>\nLLM integration requires expertise in prompt design, token management, and response streaming.\n</commentary>\n</example>\n\n<example>\nContext: Implementing computer vision features\nuser: "Users should be able to search products by taking a photo"\nassistant: "I'll implement visual search using computer vision. Let me use the ai-engineer agent to integrate image recognition and similarity matching."\n<commentary>\nComputer vision features require efficient processing and accurate model selection.\n</commentary>\n</example>
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