Engineer Guide

This guide is for you if you write code, implement features, fix bugs, review pull requests, or maintain production systems. Engineers get the deepest tooling in HVE Core, with 28+ addressable assets spanning research, planning, implementation, review, and delivery.

Recommended Collections

TIP

Install the HVE Core extension from the VS Code Marketplace to get all stable artifacts with zero configuration.

Your primary collections are hve-core (research, planning, implementation, and review agents) and coding-standards (language-specific instructions that auto-apply based on file type). For clone-based setups, use the hve-core-installer agent with install hve-core coding-standards.

What HVE Core Does for You

1. Researches codebase patterns, external APIs, and architecture before you write code
2. Creates structured implementation plans with step-by-step task breakdowns
3. Implements features following plans with phase-based execution and progress tracking
4. Reviews code changes against standards, patterns, and architectural guidelines
5. Generates conventional commit messages and pull request descriptions
6. Activates language-specific coding standards automatically based on file type (C#, Python, Bash, Bicep, Terraform, GitHub Actions)
7. Manages Git workflows including merge, rebase, and conflict resolution

Your Lifecycle Stages

NOTE

Engineers primarily operate in these lifecycle stages:

Stage 2: Discovery: Research requirements, investigate codebase, gather context Stage 3: Product Definition: Transform research into structured implementation plans Stage 6: Implementation: Build features, write code, execute plans Stage 7: Review: Review code, validate changes, ensure quality Stage 8: Delivery: Commit, create PRs, merge changes

Stage Walkthrough

1. Stage 2: Discovery. Start with the task-researcher agent to investigate requirements, explore codebase patterns, and gather evidence for your approach.
2. Stage 3: Product Definition. Use the task-planner agent to transform research into a structured implementation plan with phases, steps, and success criteria.
3. Stage 6: Implementation. Execute the plan with the task-implementor agent or /rpi mode=auto for automated phase-based implementation with progress tracking.
4. Stage 7: Review. Run the task-reviewer agent to validate implementation against the plan, check coding standards, and ensure architectural compliance.
5. Stage 8: Delivery. Use /git-commit for conventional commit messages, /pull-request for PR creation, and /git-merge for merge workflows.

Starter Prompts

/rpi Implement the user notification preferences API endpoint from work
item #4523. Follow the REST conventions in src/api/handlers/ and add
integration tests covering email, SMS, and push notification channels.

Select task-researcher agent:

Research the best approach for implementing a rate limiter in the API
gateway. Compare token bucket vs sliding window algorithms, evaluate
Redis vs in-memory storage for distributed deployments, and review
existing patterns in src/middleware/.

Select task-planner agent and attach the research document:

Create an implementation plan for the webhook delivery system. Include
phases for the event dispatcher, retry queue, and dead-letter handling.
Reference patterns in src/services/.

Select task-implementor agent and attach the plan instructions file:

Implement the webhook delivery system following the attached plan. Start
with the event dispatcher phase and execute the retry queue phase
second.

Select task-reviewer agent and attach the changes log:

Review my webhook delivery system implementation. Check for error
handling gaps, verify retry logic correctness, and validate compliance
with coding standards.

/git-commit Commit changes with a conventional message

/pull-request Create a PR for the current changes

Key Agents and Workflows

Agent	Purpose	Docs
task-researcher	Deep codebase and API research	Task Researcher
task-planner	Structured implementation planning	Task Planner
task-implementor	Phase-based code implementation	Task Implementor
task-reviewer	Code review and quality validation	Task Reviewer
rpi-agent	Full RPI orchestration in one agent	RPI Overview
pr-review	Pull request review automation	Agent file
memory	Session context and preference persistence	Agent file
prompt-builder	Create and refine prompt engineering artifacts	Agent file

Auto-activated instructions apply coding standards based on file type: C# (*.cs), Python (*.py), Bash (*.sh), Bicep (bicep/**), Terraform (*.tf), and GitHub Actions workflows (*.yml).

Tips

Do	Don't
Research before implementing multi-file changes	Jump straight to coding complex features
Use /rpi mode=auto for planned, multi-step work	Manually coordinate research, planning, and implementation
Let coding standards auto-activate by file type	Override or skip language-specific instructions
Review the research doc before starting the planning phase	Skip research for unfamiliar codebases or APIs
Clear context between RPI phases with /clear	Carry stale context across research, plan, and implement

Related Roles

• Engineer + Tech Lead: Feature development benefits from architecture review and standards enforcement. The Tech Lead validates design decisions while the Engineer implements. See the Tech Lead Guide.
• Engineer + Data Scientist: Analytics pipeline development pairs data specification and notebook prototyping with production-grade integration. See the Data Scientist Guide.
• New Contributor to Engineer: Contributors progress from guided mode through autonomous engineering. See the New Contributor Guide.

Next Steps

TIP

Run your first RPI workflow: First Workflow Guide Explore the full RPI methodology: RPI Documentation See how your stages connect: AI-Assisted Project Lifecycle

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🤖 Crafted with precision by ✨Copilot following brilliant human instruction, then carefully refined by our team of discerning human reviewers.