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By SteveGJones
Delegate full-stack SDLC architecture decisions to specialized AI agents that design scalable backends with microservices and caching, secure REST/GraphQL APIs with OpenAPI specs, performant React/Next.js frontends with state management, Kubernetes/Terraform DevOps pipelines, data lakehouses with dbt, mobile apps in React Native/Flutter, and accessible UI systems.
npx claudepluginhub stevegjones/ai-first-sdlc-practices --plugin sdlc-team-fullstackExpert in REST/GraphQL/gRPC API design, versioning strategies, security patterns, contract testing, and OpenAPI specifications. Consult for API design reviews, endpoint architecture, and integration contracts.
Expert in backend system design, microservices architecture, event-driven patterns, caching strategies, database selection, and scalability patterns. Use when designing distributed systems, evaluating architectural trade-offs, or establishing back...
Data Architect Agent
Expert in CI/CD pipeline design, GitOps deployment strategies, infrastructure as code, container orchestration, and platform engineering. Use for designing deployment automation, implementing progressive delivery, or building internal developer pl...
Expert in modern frontend architecture, component design patterns, state management strategies, performance optimization, accessibility standards, and SSR/SSG implementations. Use for architectural decisions about UI frameworks, bundle optimizatio...
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Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
Cross-cutting specialist agents — architects, researchers, performance engineers
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.
Self-orchestrating multi-agent development system — 8 specialized AI agents, parallel quality gates, and automated workflows. You say WHAT, the AI decides HOW.
Plugin de ingeniería de software completa: 10 agentes de núcleo y 9 opcionales con personalidad propia, memoria persistente por proyecto, quality gates y flujos automatizados desde la idea hasta producción.
42 specialist skills + 32 slash commands for coding agents — orchestrator, backend, frontend, QA, security, deploy, detective-spec, static-analysis, skill-author, program-router, parallel-dispatcher, blog-publisher, blog-screenshot, canary-deployment, diff-impact + spec-driven development, anti-AI writing, memory consolidation, executable YAML pipelines + insights dashboard (v2.18.0, 6 tabs: Graph, Bench, Savings, Drift, Skill Quality, Trigger Eval). v2.18.0: HTML dashboard with Cytoscape + build script (zero-build, zero-dep). v2.17.0: /diff-impact + graph auto-update hook. v2.16: skill 17 portable. v2.15: stack-default template. v2.14: TencentDB Agent Memory inspiration. v2.13: trigger eval 100% coverage. v2.10: DeerFlow conventions. v2.9: Apache-2.0 + MinHash cross-call dedup. 15 dispatchable subagents. Inspired by Lum1104/Understand-Anything (MIT) for diff-impact + dashboard patterns.
Autonomous multi-agent development framework with spec-driven sprints and convergent iteration
AI/ML specialist agents — architects, prompt engineers, RAG designers
Cloud infrastructure agents — cloud, container, SRE specialists
AI-First SDLC — zero-debt development with validators, enforcement, and workflows
Python-specific validation, patterns, and expert agents
Project management agents — agile coach, delivery manager, progress tracking
Table of Contents
A framework for integrating AI agents as primary developers while maintaining quality and process compliance. Provides specialist agents, validation tools, enforcement rules, and workflow skills for zero-technical-debt development.
Install the plugin family from the Claude Code marketplace. This is the standard approach for using the framework in your projects.
Step 1: Add the marketplace and install the core plugin
/plugin marketplace add SteveGJones/ai-first-sdlc-practices
/plugin install sdlc-core@ai-first-sdlc
Step 2: Configure your team
/sdlc-core:setup-team
This presents project types (Full-stack, AI/ML, Cloud, API, Security, Custom) and installs the matching team plugins. For example, a full-stack web app installs:
| Plugin | Description |
|---|---|
sdlc-core | Rules, validators, enforcement, workflows (always installed) |
sdlc-team-common | Solution architect, research agent, performance engineer, database architect |
sdlc-team-fullstack | Frontend, backend, API, DevOps architects |
Step 3: Start working
/sdlc-core:new-feature 1 my-feature "Description of the feature"
| Plugin | Description |
|---|---|
sdlc-core | Rules, validators, enforcement, workflows (always install) |
sdlc-team-common | Cross-cutting architects, researchers, performance engineers |
sdlc-team-ai | AI/ML specialists — architects, prompt engineers, RAG designers |
sdlc-team-fullstack | Frontend, backend, API, DevOps architects |
sdlc-team-cloud | Cloud, container, SRE specialists |
sdlc-team-security | Security, compliance, privacy specialists |
sdlc-team-pm | Agile coach, delivery manager, progress tracking |
sdlc-team-docs | Technical writer, documentation architect |
sdlc-lang-python | Python-specific validation, patterns, expert agent |
sdlc-lang-javascript | JavaScript/TypeScript validation and patterns |
| Skill | Description |
|---|---|
/sdlc-core:validate | Run validation pipeline (--syntax, --quick, --pre-push) |
/sdlc-core:new-feature | Create feature proposal, retrospective, and branch |
/sdlc-core:commit | Validated commit with test execution |
/sdlc-core:pr | Full validation + PR creation |
/sdlc-core:setup-team | Configure team formation for your project |
/sdlc-core:setup-ci | Generate GitHub Actions workflow |
/sdlc-core:release-plugin | Package source into plugins |
For testing unreleased agents or contributing to the framework, install agents directly from the repository. This approach gives you access to agents before they're published as plugins.
# Download the setup orchestrator
curl -s https://raw.githubusercontent.com/SteveGJones/ai-first-sdlc-practices/main/agents/v3-setup-orchestrator.md > v3-setup-orchestrator.md
mkdir -p .claude/agents && mv v3-setup-orchestrator.md .claude/agents/
# Restart Claude Code, then:
# "Use the v3-setup-orchestrator agent to set up AI-First SDLC for my project"
The orchestrator interviews you about your project and downloads only the agents you need. Use this approach when:
The original Python script approach. Still functional but superseded by the plugin system.