Production-engineering skills and specialist agents for Claude Code, from AI Enhanced Engineer
An agent is a domain specialist, but it carries almost no knowledge of its own. Its expertise is the **union of the skills it loads** — declared in its `skills:` frontmatter (the YAML block at the top of the file) and pulled into context when the agent activates. Change the skill list, change the specialist.
Python, PHP/Laravel, and TypeScript/NestJS backend engineer for API design, database modeling, and system integration. Call for FastAPI architecture, PostgreSQL schema design, DDD patterns, Laravel development, NestJS modules with TypeORM, async programming, or service layer decisions.
Data engineer specializing in PostgreSQL/MySQL schema design, migration management, RLS security, and query optimization. Call for database architecture, migration strategy, or multi-tenant isolation design.
DevOps engineer for CI/CD pipelines, Infrastructure as Code, deployment automation, and container orchestration. Call for deployment strategy review, IaC validation, rollback testing, or production readiness infrastructure assessment.
Svelte 5, SvelteKit, Angular 21+, and React web engineer for modern frontend development. Expert in component architecture, state management (Svelte stores/runes, Angular signals, Zustand, React Query), and accessibility. Call for UI implementation, component design, frontend architecture, or AI-assisted development.
Multimodal AI patterns for extracting structured information from video using Gemini, GPT-4o, and Claude vision. Frame sampling strategies, structured output with Pydantic, temporal reasoning, and cost optimization. Use for video analysis, report generation from video, and visual inspection.
Apple Foundation Models framework for on-device AI. LanguageModelSession, @Generable macro, structured output, token management, and availability checking.
Tactical DDD patterns for clean Python architecture including Domain Model, Repository, Service Layer, Unit of Work, and Aggregates. Use for backend architecture decisions, implementing data access layers, separating business logic from infrastructure, or reviewing code separation.
Architecture Decision Records (ADRs) for documenting significant technical decisions. Use for capturing decision context, rationale, consequences, and maintaining decision history.
Architecture visualization patterns using Mermaid and ASCII diagrams. Use for service flows, sequence diagrams, C4 models, decision matrices, or expressing architectural ideas visually.
Uses power tools
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The skill library behind production-grade AI engineering — 11 specialist agents and 102 skills, the open starter set from AIEE's Agent Skills series. Clone it, read the code, reproduce the system.
Ask Claude to build an API and it writes 500 lines of FastAPI in 30 seconds: no tests, no migration rollback, no SQL injection guard. The model can code; it just defaults to the average of everything it was trained on. Production needs the opposite: the specific decisions a senior engineer makes without thinking.
A skill encodes those decisions. It is a directory with one required file, SKILL.md, carrying a mental model and its decision rules. An agent loads the skills a task needs, when it needs them — the same RAG mechanic that keeps generated code at production standards instead of internet-average defaults. Loading skills on demand rather than inlining every standard into every agent saves roughly 70% of the context an always-on approach would burn.
This repository is that library in the open: the actual skills and the agents that consume them, so you can read the craft, not just the claims. It is the curated, generalizable subset — 102 skills and 11 agents — distilled from AIEE's production engineering practice.
A skill library isn't written once. It's a living system — designed to stay legible, maintained to stay honest. Every skill here follows the same five disciplines the Agent Skills series lays out:
SKILL.md; depth moves to optional reference.md and examples.md.description field is the routing contract. The agent reads it and nothing else to decide whether to load the skill, so it's written in the caller's vocabulary.SKILL.md. A skill is written to leave home.The two failure modes these guard against: bloat (one skill grows into an essay nobody loads) and sprawl (hundreds of thin skills nobody can find).
Plugin marketplace (recommended for Claude Code):
/plugin marketplace add ai-enhanced-engineer/aiee-skills
/plugin install aiee-skills@aiee-skills
/agents # verify the specialists are listed
npx (no marketplace — copies into a .claude directory):
npx aiee-skills install # into ./.claude for this project
npx aiee-skills install --global # into ~/.claude for every project
Runs straight from GitHub before any npm publish: npx github:ai-enhanced-engineer/aiee-skills install. Other commands: --dry-run, --force, uninstall, --help.
Local development: git clone https://github.com/ai-enhanced-engineer/aiee-skills.git then claude --plugin-dir ./. JSON manifests validate with just validate.
The pack is grouped by technology, and each group brings its specialist agent(s) plus skills. dev-practices is shared by every agent, so it's always included. A full install (no --groups) gets all 11 agents and 102 skills.
npx aiee-skills --list-groups # groups, skill + agent counts
npx aiee-skills install --groups=frontend-web,backend-api # install just those
npx claudepluginhub ai-enhanced-engineer/aiee-team --plugin aiee-teamFull-stack agents — frontend, backend, API, DevOps architects
An engineering team in a box for Claude Code. 12 specialized subagents (planner, fullstack-engineer, refactor-specialist, migration-engineer, frontend-designer, critic, vuln-verifier, debugger, db-expert, onboarder, tool-expert, web-researcher) plus 15 automation hooks (pre-commit secret scan, MCP health tracking, cost tracking, test runner, branch protection, large file warner, session summary, batch format, design quality, config protection, and more) wired by the P7/P9/P10 methodology with three red lines: closure discipline, fact-driven, exhaustiveness.
Use this agent when designing APIs, building server-side logic, implementing databases, or architecting scalable backend systems. This agent specializes in creating robust, secure, and performant backend services. Examples:\n\n<example>\nContext: Designing a new API\nuser: "We need an API for our social sharing feature"\nassistant: "I'll design a RESTful API with proper authentication and rate limiting. Let me use the backend-architect agent to create a scalable backend architecture."\n<commentary>\nAPI design requires careful consideration of security, scalability, and maintainability.\n</commentary>\n</example>\n\n<example>\nContext: Database design and optimization\nuser: "Our queries are getting slow as we scale"\nassistant: "Database performance is critical at scale. I'll use the backend-architect agent to optimize queries and implement proper indexing strategies."\n<commentary>\nDatabase optimization requires deep understanding of query patterns and indexing strategies.\n</commentary>\n</example>\n\n<example>\nContext: Implementing authentication system\nuser: "Add OAuth2 login with Google and GitHub"\nassistant: "I'll implement secure OAuth2 authentication. Let me use the backend-architect agent to ensure proper token handling and security measures."\n<commentary>\nAuthentication systems require careful security considerations and proper implementation.\n</commentary>\n</example>
Your AI development team. 36 agents and 32 skills for building, reviewing, debugging, and shipping production code. Supports Vue, React, Next.js, SvelteKit, Angular, Astro, and Nuxt.
26 domain skills + 5 verification tools for security-first full-stack engineering. Covers security, architecture, DevOps, AI, mobile, office docs, frontend design, and multi-agent coordination.
Autonomous multi-agent development framework with spec-driven sprints and convergent iteration