By easingthemes
Automates learning and knowledge retention across Claude Code sessions with a defense gate and quizzes, and connects to a local Figma instance for design file access and collaboration.
Senior code reviewer. Reviews code changes against plans, project conventions, and production readiness. Uses confidence-based filtering (>=80) to report only issues that truly matter. Use for full-diff reviews before merging.
Searches .ai/ index and reference files to look up components, architecture patterns, and feature context. Avoids expensive MCP calls. Used by dx-help, dx-ticket-analyze, and component lookup skills.
Analyzes Figma extraction to identify UI building blocks (buttons, images, cards, forms, etc.) and searches the codebase for existing components that can be reused. Used by dx-figma-prototype.
Discovers HTML and accessibility conventions from the consumer project — semantic patterns, component structure, ARIA usage, keyboard handling. Used by dx-figma-prototype.
Discovers CSS/SCSS conventions from the consumer project — variables, breakpoints, typography, spacing, theming, naming patterns. Used by dx-figma-prototype.
Auto-detect project type, structure, build commands, and AEM values. Updates .ai/config.yaml with project profile and substitutes real values into installed .claude/rules/. Run after /dx-init and /aem-init. Re-run anytime to refresh detected values.
Full pipeline from ADO story to executed code. Runs requirements, planning, execution, build, review, commit, and PR in sequence with optional human review checkpoints. Use for end-to-end story implementation.
Implement code from an RE spec as the Dev Agent — read requirements, implement changes, run self-check (build/test/lint), fix failures, and commit. Use when you want the AI Developer Agent to implement a story or fix a bug. Trigger on "dev agent", "implement from spec", "developer agent".
Analyze a User Story as the RE Agent — fetch from Azure DevOps/Jira, produce structured requirements spec with task breakdown, and post summary comment. Use when you want the AI Requirements Engineering Agent to analyze a story. Trigger on "re agent", "requirements agent", "analyze story requirements".
Run accessibility testing on a URL using the axe MCP Server — analyze violations, get remediation guidance, apply fixes, and verify. Use when asked to check accessibility, run a11y audit, or fix WCAG issues.
Executes bash commands
Hook triggers when Bash tool is used
Modifies files
Hook triggers on file write and edit operations
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Uses power tools
Uses Bash, Write, or Edit tools
Uses power tools
Uses Bash, Write, or Edit tools
Enterprise AI development platform for teams shipping on Azure DevOps and Atlassian. 75+ skills that run identically across Claude Code, GitHub Copilot CLI, and VS Code Chat — from ticket to PR, fully autonomous. Deep AEM specialization built in.
Enterprise teams run complex sprints across multiple repos, multiple IDEs, and multiple team members. They need a system that handles the full lifecycle — requirements analysis, implementation planning, code generation, testing, verification, documentation, and PR creation — with governance at every step. Without re-explaining the project every session.
KAI is a structured development workflow built as a plugin system for enterprise teams. It encodes your entire sprint lifecycle — requirements, planning, execution, review, PR — into skills that orchestrate multi-agent pipelines across every major AI platform. A single command like /dx-req-all pulls the ticket from Azure DevOps or Jira, validates readiness against your DoR, distills developer requirements, researches the codebase with parallel subagents, and generates a team summary. Each skill chains specialized agents (Opus for deep review, Sonnet for execution, Haiku for lookups), gathers context from multiple sources (tickets, config, codebase, Figma designs, live AEM content), and writes structured output that the next skill picks up automatically.
What makes it different:
Add the marketplace, then install the plugins you need:
# Add the marketplace (once)
/plugin marketplace add easingthemes/dx-aem-flow
# Install plugins
/plugin install dx-core@dx-aem-flow # Core workflow (all projects)
/plugin install dx-hub@dx-aem-flow # Multi-repo orchestration (optional)
/plugin install dx-aem@dx-aem-flow # AEM tools (AEM projects)
/plugin install dx-automation@dx-aem-flow # Autonomous agents (24/7 pipelines)
From a local clone:
/plugin marketplace add /path/to/dx-aem-flow
/plugin install dx-core@dx-aem-flow
Full-stack development workflow for Azure DevOps and Jira projects: requirements gathering, implementation planning, step-by-step execution with testing and review, code review, bug fixes, and PR management.
Works with any tech stack.
Hub directory management for coordinating work across multiple consumer repos — init, config, status.
The complete AEM development lifecycle: component dialog inspection, JCR content, page authoring, editorial QA with browser automation, snapshot/verify lifecycle, and demo capture. Includes the AEM MCP server for live JCR and dialog access. Purpose-built for AEM Cloud and on-premise projects.
Requires dx plugin.
Autonomous AI agents for ADO workflows — Definition of Ready checker, Definition of Done checker, DoD fixer, PR reviewer, PR answerer. Runs as ADO pipelines triggered by AWS Lambda webhooks.
Multi-repo hub orchestration — run dx skills across sibling repositories from a single hub directory.
AEM component verification, dialog inspection, demo capture, QA automation, and multi-platform project knowledge for Adobe Experience Manager projects
npx claudepluginhub easingthemes/dx-aem-flow --plugin dx-coreHarness-native ECC operator layer - 67 agents, 271 skills, 92 legacy command shims, reusable hooks, rules, selective install profiles, and production-ready workflows for Claude Code, Codex, OpenCode, Cursor, and related agent harnesses
Intelligent draw.io diagramming plugin with AI-powered diagram generation, multi-platform embedding (GitHub, Confluence, Azure DevOps, Notion, Teams, Harness), conditional formatting, live data binding, and MCP server integration for programmatic diagram creation and management.
Reliable automation, in-depth debugging, and performance analysis in Chrome using Chrome DevTools and Puppeteer
Feature development with code-architect/explorer/reviewer agents, CLAUDE.md audit and session learnings, and Agent Skills creation with eval benchmarking from Anthropic.
Access thousands of AI prompts and skills directly in your AI coding assistant. Search prompts, discover skills, save your own, and improve prompts with AI.
Comprehensive skill pack with 66 specialized skills for full-stack developers: 12 language experts (Python, TypeScript, Go, Rust, C++, Swift, Kotlin, C#, PHP, Java, SQL, JavaScript), 10 backend frameworks, 6 frontend/mobile, plus infrastructure, DevOps, security, and testing. Features progressive disclosure architecture for 50% faster loading.