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compound-engineering

Automate planning, coding, review, and deployment with specialized agents.

Updated Aug 23, 2026
Search Tags:#code review#knowledge management#agent orchestration#frontend development#ai-assisted development#autonomous workflows
One-click install
npx skills add https://github.com/TrendpilotAI/invesco-demo --skill compound-engineering-trendpilotai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: compound-engineering
Source: https://github.com/TrendpilotAI/invesco-demo/tree/main/skills/compound-engineering
Command: npx skills add https://github.com/TrendpilotAI/invesco-demo --skill compound-engineering-trendpilotai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a suite of AI-powered tools to streamline the entire software development lifecycle, from planning and coding to review and deployment, making engineering work more efficient and compounding knowledge over time.

Core Features & Use Cases

  • Autonomous Workflows: Orchestrate complex tasks like feature development from start to finish (/lfg, /slfg).
  • Intelligent Code Review: Leverage specialized agents for security, performance, style, and architecture reviews (/workflows:review).
  • Enhanced Planning: Deepen implementation plans with research, best practices, and parallel agent analysis (/workflows:deepen-plan).
  • Knowledge Management: Capture and organize solved problems into a searchable knowledge base (/workflows:compound, skills/compound-docs).
  • Specialized Tools: Utilize skills for browser automation (skills/agent-browser), image generation (skills/gemini-imagegen), and Git worktree management (skills/git-worktree).

Quick Start

Use the compound engineering skill to plan and execute a new feature by running the /lfg command with a description of the feature.

Frequently Asked Questions about compound-engineering

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate AI-assisted feature development from planning to deployment?▼

AI-assisted feature development is automated by orchestrating specialized agents that handle planning, coding, review, and deployment processes. You can trigger autonomous workflows using commands like /lfg to execute tasks end-to-end.

What is multi-agent orchestration for autonomous software workflows?▼

Multi-agent orchestration coordinates specialized agents for code analysis, research, design, and workflow execution. This enables autonomous feature development by running parallel agent swarms through a unified interface to compound engineering knowledge.

How do I run an intelligent code review for security and architecture?▼

Intelligent code review is executed by leveraging specialized agents focused on security, performance, style, and architecture. You can trigger this workflow to analyze your codebase and identify issues across multiple dimensions automatically.

Can I manage Git worktrees and browser automation within an AI development workflow?▼

Git worktree management and browser automation are supported through specialized tool components within the workflow. These skills integrate into the unified interface to support autonomous development and testing tasks.

How do I capture and organize solved coding problems into a knowledge base?▼

Solved coding problems are captured and organized into a searchable knowledge base using knowledge management workflows. This process compounds engineering knowledge by documenting solutions and making them retrievable for future development.

What's the best way to deepen implementation plans with AI research?▼

Implementation plans are deepened by applying research, best practices, and parallel agent analysis. This workflow enhances your initial plan by leveraging specialized agents to evaluate architectural approaches and technical constraints.

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