Equip Claude Code for enterprise dev workflows: auto-detect frameworks/infra/tests (React/NestJS/Rails/Elixir/.NET/AWS/K8s), reference production patterns, generate/execute unit/smoke tests (Jest/pytest/RSPEC/xUnit), create changelogs, orchestrate releases with quality gates/canaries/rollbacks, and coordinate multi-agent tasks across stacks.
npx claudepluginhub fortiumpartners/ai-meshThe `/claude-changelog` command enables developers to track Claude updates and new features directly within Claude Code, eliminating the need for manual changelog checking and context switching.
**Version**: 1.0.0
> **Complete Agent Architecture** implementing Leo's AI-Augmented Development Process with 27 specialized agents + skills-based framework support providing clear role delineation, minimal overlap, and intelligent delegation patterns.
Clear one-line mission statement describing the agent's primary purpose (50-80 characters)
This guide explains how to use `_TEMPLATE.md` to create or update agents in the Fortium Claude Code configuration system.
**Auto-detect AWS, GCP, or Azure usage with 95%+ accuracy using multi-signal analysis.**
**Framework**: .NET 8+ with ASP.NET Core
Execute and generate ExUnit tests for Elixir projects with setup callbacks, describe blocks, and async testing support
**Version**: 1.0.0 | **Target Size**: <25KB | **Purpose**: Fast reference for Fly.io deployments and global application distribution
Multi-signal framework detection with confidence scoring for 6 major frameworks
**Version**: 1.0.0 | **Target Size**: <100KB | **Purpose**: Fast reference for Helm chart development and deployment
**Quick reference for AWS infrastructure automation with Terraform, security-first design, and production-ready patterns.**
**Version**: 1.0.0
**Quick Reference** - Parse conventional commits and generate categorized changelog
Execute and generate Jest tests for JavaScript/TypeScript projects with support for unit, integration, and E2E testing
**Version**: 1.0.0 | **Target Size**: <100KB | **Purpose**: Fast reference for Kubernetes manifest development and deployment
Node.js/TypeScript backend framework with dependency injection and modular architecture
**Version**: 1.0.0 | **Last Updated**: 2025-10-22 | **Agent**: backend-developer
Execute and generate pytest tests for Python projects with fixtures, parametrization, and mocking support
**Framework**: Ruby on Rails 7+
**Version**: 1.0.0
Execute and generate RSpec tests for Ruby projects with let bindings, before hooks, and mocking support
**Quick Reference** - Load this first for fast context (~3KB)
**Quick Reference** - Load this first for fast context (~2KB)
**Quick Reference** - Load this first for fast context (~2KB)
**Quick Reference** - Load this first for fast context (~3KB)
**Quick Reference** - Load this first for fast context (~3KB)
**Quick Reference** - Orchestrates all smoke test categories
Automatically detect test frameworks (Jest, pytest, RSpec, xUnit) in projects by analyzing configuration files and dependencies
**Version**: 1.0.0 | **Purpose**: Automatic detection of infrastructure tooling (Helm, Kubernetes, Kustomize, ArgoCD)
Execute and generate xUnit tests for C#/.NET projects with FluentAssertions and Moq support
Production-ready Claude Code configuration with role-based workflows (PM→Lead→Designer→Dev→QA), safety hooks, 44 commands, 19 skills, 8 agents, 43 rules, 30 hook scripts across 19 events, auto-learning pipeline, hook profiles, and multi-language coding standards
Uses power tools
Uses Bash, Write, or Edit tools
Share bugs, ideas, or general feedback.
Community-driven marketplace with specialized AI agents covering the full SDLC: code review, security scanning, deployment, and performance optimization.
Complete collection of battle-tested Claude Code configs from an Anthropic hackathon winner - agents, skills, hooks, and rules evolved over 10+ months of intensive daily use
Enterprise AI agent orchestration plugin with 150+ commands, 74+ specialized agents, SPARC methodology, swarm coordination, GitHub integration, and neural training capabilities
Use this agent for optimizing human-agent collaboration workflows and analyzing workflow efficiency. This agent specializes in identifying bottlenecks, streamlining processes, and ensuring smooth handoffs between human creativity and AI assistance. Examples:\n\n<example>\nContext: Improving development workflow efficiency
Multi-agent orchestration framework for Claude Code. Routes tasks to specialized Haiku/Sonnet subagents while Opus orchestrates — inspired by speculative decoding. Includes 10 specialized heads, environment preflight checks, and ~50% API cost reduction.