By dgkngk
Super Engineer Team — a full AI engineering team for Claude Code. Includes 19 specialized agents (planner, coder, tester, reviewer, debugger and more), 69 skills, slash commands, and an MCP server with semantic context search.
Expert backend architect for Node.js, Python, and modern serverless/edge systems. Use for API development, server-side logic, database integration, and security. Triggers on backend, server, api, endpoint, database, auth.
Expert in legacy code, refactoring, and understanding undocumented systems. Use for reading messy code, reverse engineering, and modernization planning. Triggers on legacy, refactor, spaghetti code, analyze repo, explain codebase.
Clean code implementation specialist. Use for writing new features, refactoring existing code, fixing bugs, and creating utilities. Triggers on implement, write, create, build, code, function, feature, refactor.
Data Engineer specialist for designing data pipelines, ETL processes, and large-scale data architecture.
Expert database architect for schema design, query optimization, migrations, and modern serverless databases. Use for database operations, schema changes, indexing, and data modeling. Triggers on database, sql, schema, migration, query, postgres, index, table.
Build accretion/dilution analysis for M&A transactions. Models pro forma EPS impact, synergy sensitivities, and purchase price allocation. Use when evaluating a potential acquisition, preparing merger consequences analysis for a pitch, or advising on deal terms. Triggers on "merger model", "accretion dilution", "M&A model", "pro forma EPS", "merger consequences", or "deal impact analysis".
Multi-agent orchestration patterns. Use when multiple independent tasks can run with different domain expertise or when comprehensive analysis requires multiple perspectives.
Performance profiling principles. Measurement, analysis, and optimization techniques.
Structured task planning with clear breakdowns, dependencies, and verification criteria. Use when implementing features, refactoring, or any multi-step work.
PowerShell Windows patterns. Critical pitfalls, operator syntax, error handling.
Uses power tools
Uses Bash, Write, or Edit tools
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Super-Kit is a modular repository containing instructions, workflows, skills, and specializations for AI coding agents. By structuring AI agent contexts into individual files, it allows large language model agents to load specific knowledge on the fly instead of relying on massive and bloated static system prompts.
While the primary purpose is to compund the knowledge of engineering, I will add more domains as I see fit.
🔗 GitHub Repository: dgkngk/super-kit
🔗 NPM Package: superkit-mcp-server
/plugin → Discover → Add sourcegithub:dgkngk/super-kit/plugin install super-kit@dgkngkThis configures the MCP server automatically and makes all skills, agents, and commands available.
Requirements: Node.js 18+ (for npx superkit-mcp-server@latest)
agents/: Contains instructions and guidelines for specialized AI roles (e.g., data-engineer).skills/: Contains technology-specific or meta skills (patterns, best practices) the agent can load dynamically (e.g., react-best-practices).workflows/: Contains step-by-step interactive slash-commands to guide the AI workflow (e.g., /plan, /explore).src/: The Model Context Protocol (MCP) server that exposes all these assets directly to compatible AI platforms.The easiest way to power up your agent with this toolkit is to use the included MCP server.
You can launch it directly using npx:
npx -y superkit-mcp-server
list_superkit_assets: Lists all available agents, skills (tech/meta), and workflows in the Super-Kit repository.load_superkit_agent: Loads the system instructions and guidelines for a specific specialist agent (e.g., data-engineer).load_superkit_skill: Loads the skill instructions (SKILL.md) for a specific category and skill (e.g., category: tech, name: react-best-practices).load_superkit_workflow: Loads the instructions for a specific slash-command workflow (e.g., work, explore).call_tool_checklist: Executes the native TypeScript validation suite (security, web accessibility, react performance, testing, API structure) on a target project location via the MCP environment instead of generic bash loops.The Super-Kit MCP server exposes all workflows inside the workflows/ directory dynamically as MCP Prompts. AI agents can invoke GetPromptRequestSchema to instantly load complex workflows (e.g., plan-compound, review-compound) along with their security and validation tooling straight into their context.
If you cloned this repository locally, you can build and use the MCP server directly:
cd super-kit
npm install
npm run build
Add the following to your cline_mcp_settings.json:
{
"mcpServers": {
"superkit": {
"command": "node",
"args": ["/absolute/path/to/super-kit/build/index.js"]
}
}
}
Go to Settings -> Features -> MCP Servers. Add a new stdio server:
superkitnode /absolute/path/to/super-kit/build/index.jsThe built-in MCP server reads directly from the super-kit directory, resolving paths safely to prevent traversal attacks. It automatically parses and returns the Markdown contents of the structural elements so your AI agent always has the right context in mind.
npx claudepluginhub dgkngk/super-kit --plugin super-kitProduction-grade engineering skills for AI coding agents — covering the full software development lifecycle from spec to ship.
Unified capability management center for Skills, Agents, and Commands.
Harness for Claude Code — skills, /harness:* slash commands, persona subagents, lifecycle hooks, and MCP tools without per-repo `harness setup`. Sibling plugins exist for Cursor, Gemini CLI, and Codex.
Make AI coding agents follow a repeatable engineering workflow with memory, verification, skills, and multi-agent setup
Skills for creating new agent skills for Claude Code and VS Code Copilot
24 elite skills across 5 layers: discipline, domain expertise, intelligence, coordination, and execution. Turn Claude Code into a proactive engineering partner.