Stop copy-pasting prompts and instructions. Start packaging them.
β
Works with GitHub Copilot, Cursor, Claude, Codex, Gemini and all AGENTS.md adherents
β
2-minute setup - zero config
β
Team collaboration - composable context, without wheel reinvention
π¦ Mix and match what your team needs:
- Agents - Agentic workflows (.prompt.md files)
- Context - Company rules, standards, knowledge (.instructions.md files) and domain boundaries (.chatmode.md)
Note
π Prerequisites: Get tokens at github.com/settings/personal-access-tokens/new
GITHUB_COPILOT_PAT- User-scoped Fine-grained PAT with Copilot CLI subscription accessGITHUB_APM_PAT- (optional) - Fine-grained PAT for access to private APM modules
π Complete Setup Guide: Getting Started
# Set up APM (one-time)
export GITHUB_COPILOT_PAT=your_token_here
curl -sSL "https://raw.githubusercontent.com/danielmeppiel/apm/main/install.sh" | sh
# 3. Set up GitHub Copilot CLI
apm runtime setup copilot
# Run any prompt from GitHub - zero config needed
apm run github/awesome-copilot/prompts/architecture-blueprint-generator# Create project with layered context from multiple APM packages
apm init my-project && cd my-project
# Install context + workflows from packages
apm install danielmeppiel/design-guidelines
apm install danielmeppiel/compliance-rules
# Compile into single AGENTS.md guardrails
# Now all agents respect design + compliance rules automatically
apm compile
# Run a prompt from the installed packages above
apm run design-reviewThat's it! Your project now has reliable AI workflows that work with any coding agent.
GitHub Enterprise: Works with GitHub Enterprise Server and Data Residency Cloud. Configuration β
Here's what your apm.yml configuration file looks like (similar to package.json in npm):
name: my-project
version: 1.0.0
description: My AI-native project
author: Developer
dependencies:
apm:
- danielmeppiel/compliance-rules
- danielmeppiel/design-guidelines
- github/awesome-copilot/prompts/architecture-blueprint-generator.prompt.md
mcp:
- github/github-mcp-server
- microsoft/azure-devops-mcp
scripts:
start: "copilot --full-auto -p hello-world.prompt.md"Virtual Packages: Install individual files directly from any repo (e.g.,
apm install github/awesome-copilot/prompts/code-review.prompt.md). Learn more β
- Agent Workflows - Agent executable processes (.prompt.md files)
- Context System - Project knowledge that grounds AI responses
- Dependency Management -
apm_modules/with shared context from other projects - Universal Compatibility - Works with any coding agent supporting the
Agents.mdstandard (e.g. GitHub Copilot, Cursor, Claude, Codex, Gemini...)
APM solves the AI agent context scalability problem through constraint satisfaction optimization.
Learn more about the Context Optimization Engine β
apm init <project> # Initialize AI-native project
apm runtime setup # Install coding agents (copilot recommended)
apm compile # Generate AGENTS.md for compatibility
apm install # Install APM and MCP dependencies from apm.yml
apm deps list # List installed APM dependencies
apm run <workflow> # Execute Agent workflowsbrew tap danielmeppiel/apm-cli
brew install apm-clipip install apm-cliSee complete installation guide for all options and troubleshooting.
APM Packages (reusable modules):
- π’
compliance-rules- GDPR contexts + audit workflows - π€
design-guidelines- Accessibility rules + UI review workflows
Application using APM:
- π Corporate Website - Complete showcase demonstrating Context Optimization Engine + both packages above as dependencies
Copy this badge for your APM packages
Install any of the below APM packages with: apm install <owner>/<repo>
- DevExpGbb/platform-mode - The Future of AI-Enhanced Platform Engineering
- Add yours here!
- π Complete Documentation - Deep dive into APM
- π Getting Started Guide - Extended setup and first project
- π§ Core Concepts - AI-Native Development framework
- π¦ Examples & Use Cases - Real-world workflow patterns
- π§ Agent Primitives Guide - Build advanced workflows
- π€ Contributing - Join the AI-native ecosystem
Learning Guide β Awesome AI Native
A practical companion guide that inspired APM CLI: https://danielmeppiel.github.io/awesome-ai-native
A friendly, step by step example-driven learning path for AI-Native Development β leveraging APM CLI along the way.
APM transforms any project into reliable AI-Native Development
