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docs/README.md

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1---
2title: HVE Core Documentation
3description: Documentation index for HVE Core Copilot customizations
4author: Microsoft
5ms.date: 2026-01-22
6ms.topic: overview
7---
8
9HVE Core is an enterprise-ready prompt engineering framework for GitHub Copilot. It provides specialized agents, reusable prompts, instruction sets, and a validation pipeline with JSON schema enforcement. The framework separates AI concerns into distinct artifact types with clear boundaries, preventing runaway behavior through constraint-based design.
10
11## Audience
12
13| Role | Goal | Start Here | Key Resources |
14|------------------------|-----------------------------|-----------------------------------------------------|---------------------------------|
15| **Developers** | Use agents to ship features | [First Workflow](getting-started/first-workflow.md) | RPI agents, prompt patterns |
16| **TPMs & Leads** | Coordinate AI-assisted work | [Why RPI?](rpi/why-rpi.md) | Methodology, team adoption |
17| **Platform Engineers** | Maintain prompt libraries | [Build Workflows](architecture/workflows.md) | Validation pipeline, schemas |
18| **Contributors** | Create new artifacts | [AI Artifacts](contributing/ai-artifacts-common.md) | Authoring patterns, conventions |
19
20## Getting Started
21
22**Time to complete**: 15-30 minutes
23
24The Getting Started guide walks through installation, configuration, and running your first Copilot workflow.
25
26* [Installation Methods](getting-started/install.md) - Seven setup options from VSCode extension to submodule
27* [MCP Configuration](getting-started/mcp-configuration.md) - Model Context Protocol server setup
28* [First Workflow](getting-started/first-workflow.md) - End-to-end example with RPI agents
29
30**[Getting Started Guide →](getting-started/README.md)**
31
32## Agent Systems
33
34**Time to complete**: 10-15 minutes
35
36hve-core provides specialized agents organized into functional groups. Each group combines agents, prompts, and instruction files into cohesive workflows for specific engineering tasks.
37
38* [RPI Orchestration](rpi/README.md) separates complex tasks into research, planning, implementation, and review phases
39* [GitHub Backlog Manager](agents/github-backlog/README.md) automates issue discovery, triage, sprint planning, and execution across GitHub repositories
40* Additional systems documented in the [Agent Catalog](agents/README.md)
41
42**[Browse the Agent Catalog →](agents/README.md)**
43
44## RPI Methodology
45
46**Time to complete**: 20-40 minutes
47
48Research, Plan, Implement (RPI) is a structured methodology for complex AI-assisted engineering tasks. It separates concerns into three specialized agents that work together.
49
50* [Why RPI?](rpi/why-rpi.md) - Problem statement and design rationale
51* [Task Researcher](rpi/task-researcher.md) - Discovery and context gathering
52* [Task Planner](rpi/task-planner.md) - Structured task planning
53* [Task Implementor](rpi/task-implementor.md) - Execution with tracking
54* [Using Together](rpi/using-together.md) - Agent coordination patterns
55
56**[RPI Documentation →](rpi/README.md)**
57
58## Prompt Engineering
59
60**Time to complete**: 15-25 minutes
61
62HVE Core provides a structured approach to building AI artifacts with protocol patterns, input variables, and maturity lifecycle management.
63
64* [Prompt Builder Agent](../.github/agents/prompt-builder.agent.md) - Interactive artifact creation with sandbox testing
65* [AI Artifacts Overview](contributing/ai-artifacts-common.md) - Common patterns across artifact types
66* [Activation Context](architecture/ai-artifacts.md#activation-context) - When artifacts activate within workflows
67
68Key differentiators:
69
70| Capability | Description |
71|-------------------------|-----------------------------------------------------------|
72| Constraint-based design | Agents know their boundaries, preventing runaway behavior |
73| Subagent delegation | First-class pattern for decomposing complex tasks |
74| Maturity lifecycle | Four-stage model from experimental to deprecated |
75| Schema validation | JSON schema enforcement for all artifact types |
76
77## Contributing
78
79**Time to complete**: 10-20 minutes
80
81Learn how to create and maintain AI artifacts including agents, prompts, instructions, and skills.
82
83* [Instructions](contributing/instructions.md) - Passive reference guidance
84* [Prompts](contributing/prompts.md) - Task-specific procedures
85* [Agents](contributing/custom-agents.md) - Custom personas and modes
86* [Skills](contributing/skills.md) - Executable utilities with documentation
87
88**[Contributing Guide →](contributing/README.md)**
89
90## Architecture
91
92Technical documentation for system design, component relationships, and build pipelines.
93
94* [Component Overview](architecture/README.md) - System components and interactions
95* [AI Artifacts](architecture/ai-artifacts.md) - Four-tier artifact delegation model
96* [Build Workflows](architecture/workflows.md) - GitHub Actions CI/CD architecture
97* [Testing](architecture/testing.md) - PowerShell Pester test infrastructure
98
99**[Architecture Overview →](architecture/README.md)**
100
101## Templates
102
103Pre-built templates for common engineering documents:
104
105* [ADR Template](templates/adr-template-solutions.md) - Architecture Decision Records
106* [BRD Template](templates/brd-template.md) - Business Requirements Documents
107* [Security Plan Template](templates/security-plan-template.md) - Security planning
108
109**[Browse Templates →](templates/)**
110
111## Quick Links
112
113| Resource | Description |
114|--------------------------------------------|------------------------------------|
115| [CHANGELOG](../CHANGELOG.md) | Release history and version notes |
116| [CONTRIBUTING](../CONTRIBUTING.md) | Repository contribution guidelines |
117| [Scripts README](../scripts/README.md) | Automation script reference |
118| [Extension README](../extension/README.md) | VS Code extension documentation |
119
120🤖 *Crafted with precision by ✨Copilot following brilliant human instruction, then carefully refined by our team of discerning human reviewers.*
121