In this article
Copilot CLI Plugin
Install the complete HVE Core component set as a Copilot CLI plugin for terminal-based AI-assisted development workflows.
Prerequisites
- GitHub Copilot CLI installed and authenticated
Register hve-core as a Plugin Marketplace
Choose a registration that matches the content you need.
Register the ref-less development tip:
copilot plugin marketplace add microsoft/hve-core
Register a moving reviewed release channel:
copilot plugin marketplace add microsoft/hve-core#release/prerelease
copilot plugin marketplace add microsoft/hve-core#release/stable
Register an immutable channel tag:
copilot plugin marketplace add microsoft/hve-core#prerelease-v<version>
copilot plugin marketplace add microsoft/hve-core#v<version>
main is the development tip and its catalog entries omit source.ref.
release/prerelease and release/stable are moving registrations that resolve
their current reviewed branch catalog. Each branch catalog pins every entry to
its corresponding exact channel tag. Exact-tag registrations freeze both the
catalog selection and plugin source tag.
A published channel release provides release assurance for its exact tag, including release gates, SBOMs, attestations, provenance verification, and the configured publication path. The development tip does not provide that published-release assurance.
Browse Available Plugins
Type /plugin in a Copilot CLI chat session to browse available plugins.
Install a Plugin
Install hve-core from the registered marketplace through /plugin. The plugin includes the complete active HVE Core component set, including the Research, Plan, Implement, Review lifecycle.
copilot plugin install hve-core@hve-core
Update an Installed Plugin
Marketplace refresh and installed-plugin update are distinct actions. For a moving registration, refresh the catalog before requesting a plugin update:
copilot plugin marketplace update hve-core
copilot plugin update hve-core@hve-core
Switching registrations can require removing and re-adding the marketplace. Do not assume how the client handles duplicate same-name registrations; use the behavior supported by your Copilot CLI version.
Use the migration guide if you previously registered or installed a retired package identity.
Plugin Contents
Each plugin includes:
| Component | CLI Discovery | Description |
|---|---|---|
| Agents | Yes | Custom chat agents for specialized workflows |
| Commands | Yes | Task prompts accessible via the CLI |
| Skills | Yes | Self-contained skill packages |
| Instructions | No | Included for #file: references, not auto-applied |
Each plugin is a self-contained tree of regular files and real directories. Artifacts are copied from the source repository during generation, so a plugin installs the same way on every operating system and needs no symbolic link support.
Limitations
Instructions are not auto-applied from plugins
The Copilot CLI plugin spec
recognizes agents, skills, commands, hooks, mcpServers, and
lspServers as component types. There is no instructions component type.
The CLI loads path-specific instructions exclusively from
.github/instructions/**/*.instructions.md in the
project repo.
Instruction files in plugin directories are not auto-applied via applyTo
pattern matching.
Instruction files are still included in plugin output because agents and
prompts reference them via #file: directives. Those cross-file references
resolve correctly within the plugin directory tree. The difference is between
explicit inclusion (an agent pulls in instruction content at execution time)
and automatic application (the CLI matches applyTo patterns against the
files you are editing).
For full path-specific instruction behavior, copy instruction files into your
project's .github/instructions/ directory.
Other limitations
- Skills require skill-compatible agent environments
Using Agents After Installation
After installing a plugin, agents and named commands are available in your CLI session.
Named Commands vs Agent Mode
CLI plugins provide two distinct interaction patterns:
| Mode | Command | Behavior |
|---|---|---|
| Named Command | /git-commit | Executes a predefined workflow, then returns to default mode |
| Skill | /rpi-research | Activates one reusable RPI phase capability |
| Agent Mode | /agent RPI Agent | Switches to the coordinated RPI lifecycle |
Named commands (prompts) run a specific workflow and produce structured output. Agent mode enables freeform conversation with a specialized agent until you exit.
IMPORTANT
The CLI does not switch to a custom agent on behalf of an agent-bound
prompt. Select RPI Agent when you want lifecycle coordination, or invoke a
direct phase skill such as /rpi-research:
/agent RPI Agent
Research API authentication patterns before deciding whether planning is ready.
Prompts that do not require an agent context (e.g., /git-commit,
/git-merge) work directly from the default mode.
Example: Research Workflow
Invoke the Research phase skill directly:
> /rpi-research topic="API authentication patterns"
[Skill executes the research workflow and creates a research document]
Continue with follow-up questions in the same session:
> What are common API authentication patterns for REST APIs?
[Research conversation continues]
> How do OAuth2 and API keys compare for microservices?
[Follow-up within same agent context]
Available Agents
After installing the hve-core plugin, these agents are available via /agent <name>:
- RPI Agent - coordinates Research, Plan, Implement, Review, and Follow-up
- Documentation - audits, authors, and validates documentation
For the complete list, run /help in a CLI session to see all available commands and agents.
When to Use Each Mode
- Use named commands (
/git-commit-message,/git-merge) directly from default mode for workflows that do not require a custom agent. - Use direct skills (
/rpi-research,/rpi-plan,/rpi-implement,/rpi-review) for one bounded RPI responsibility. - Use agent mode with
/agent RPI Agentfor lifecycle coordination. - Stay in agent mode for exploratory conversations, follow-up questions, or tasks that don't fit a predefined prompt.
🤖 Crafted with precision by ✨Copilot following brilliant human instruction, then carefully refined by our team of discerning human reviewers.