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By SteveGJones
Enforce AI-First SDLC practices with zero-debt policies: validate code with ruff/pytest/mypy/bandit before commits, generate GitHub Actions workflows, create conventional commits and PRs, and get compliance audits for technical debt, branch workflows, and pre-PR readiness across Python, JavaScript, Go, Java, and Rust projects.
npx claudepluginhub stevegjones/ai-first-sdlc-practices --plugin sdlc-coreExpert in code quality, security vulnerabilities (OWASP Top 10), language-specific patterns (Python/JS/Go/Java/Rust), and automated review tools. Use for PR reviews, security assessments, and review process setup.
Expert in requirements verification, goal alignment validation, and gap analysis for completed work. Use after implementing features, completing code sections, or finishing design work to ensure alignment with original requirements and identify de...
Expert in AI-First SDLC compliance enforcement, progressive quality gates, Zero Technical Debt policy, and process validation. Use for real-time compliance checking during development, branch protection validation, workflow guidance, and ensuring...
Enforces documentation-code fidelity, test coverage, and runtime verification. Use at every phase transition to verify that docs match code, tests exist and pass, and the application actually runs. Mandatory gate — nothing ships without proof.
Validated commit — runs quick checks before committing. Use when ready to commit changes.
Create a new feature with proposal, retrospective, and branch. Use when starting new development work.
Create a pull request with full validation. Use when ready to submit work for review.
Package source files into plugin directories using release-mapping.yaml. Use when preparing a plugin release.
AI-First SDLC compliance rules and standards. Use when checking code quality, validating architecture, enforcing zero technical debt, or making any compliance decision.
Modifies files
Hook triggers on file write and edit operations
Uses power tools
Uses Bash, Write, or Edit tools
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Sign in to claimBased on adoption, maintenance, documentation, and repository signals. Not a security audit or endorsement.
AI/ML specialist agents — architects, prompt engineers, RAG designers
Persona-driven AI development team: orchestrator, team agents, review agents, skills, slash commands, and advisory hooks for Claude Code
PROJECT.md-first autonomous development with hybrid auto-fix documentation. 8-agent pipeline, auto-orchestration, docs auto-update on commit (true vibe coding). Knowledge base system with 90% faster repeat research. Strict mode enforces SDLC best practices automatically. Works for ANY Python/JavaScript/TypeScript/Go project.
AI-powered development workflow automation - Phase-based planning, implementation orchestration, preflight code quality checks with security scanning, ship-it workflow, and development principles generator for CLAUDE.md
SDLC enforcement for AI agents — TDD, planning, self-review, CI shepherd
AI-SDLC governance framework for Claude Code — action enforcement, telemetry, quality gates, and review agents
Full-stack agents — frontend, backend, API, DevOps architects
Cloud infrastructure agents — cloud, container, SRE specialists
Python-specific validation, patterns, and expert agents
AI/ML specialist agents — architects, prompt engineers, RAG designers
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.