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docs/contributing/custom-agents.md

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---
title: 'Contributing Agents to HVE Core'
description: 'Requirements and standards for contributing GitHub Copilot agent files to hve-core'
sidebar_position: 5
author: Microsoft
ms.date: 2026-03-14
ms.topic: how-to
---

This guide defines the requirements, standards, and best practices for contributing GitHub Copilot agent files (`.agent.md`) to the hve-core library.

⚙️ Common Standards: See [AI Artifacts Common Standards](ai-artifacts-common.md) for shared requirements (XML blocks, markdown quality, RFC 2119, validation, testing).

## What is an Agent?

An **agent** is a specialized AI configuration that defines behavior, available tools, and instructions for GitHub Copilot to follow when performing specific tasks. Agents enable consistent, repeatable workflows for complex development activities.

## Use Cases for Agents

Create an agent when you need to:

* Define a specialized AI agent role (e.g., security reviewer, PR analyzer, documentation generator)
* Orchestrate multi-step workflows requiring specific tool sequences
* Maintain consistent behavior patterns across development tasks
* Provide domain-specific expertise (e.g., ADR creation, work item processing)
* Automate complex decision-making with predefined logic flows

## Agents Not Accepted

The following agent types will likely be **rejected or closed automatically** because equivalent agents already exist in hve-core:

### Duplicate Agent Categories

#### Research or Discovery Agents

Agents that search for, gather, or discover information.

* ❌ Reason: Existing agents already handle research and discovery workflows
* ✅ Alternative: Use existing research-focused agents in `.github/agents/`

#### Indexing or Referencing Agents

Agents that catalog, index, or create references to existing projects.

* ❌ Reason: Existing agents already provide indexing and referencing capabilities
* ❌ Tool integration: Widely supported tools built into VS Code GitHub Copilot and MCP tools with extremely wide adoption are already supported by existing hve-core agents
* ✅ Alternative: Use existing reference management agents that use standard VS Code GitHub Copilot tools and widely-adopted MCP tools

#### Planning Agents

Agents that plan work, break down tasks, or organize backlog items.

* ❌ Reason: Existing agents already handle work planning and task organization
* ✅ Alternative: Use existing planning-focused agents in `.github/agents/`

#### Implementation Agents

General-purpose coding agents that implement features.

* ❌ Reason: Existing agents already provide implementation guidance
* ✅ Alternative: Use existing implementation-focused agents

### Rationale for Rejection

These agent types are rejected because:

1. Existing agents are hardened and heavily used: the hve-core library already contains production-tested agents in these categories
2. Consistency and maintenance: coalescing around existing agents reduces fragmentation and maintenance burden
3. Avoid duplication: multiple agents serving the same purpose create confusion and divergent behavior
4. Standard tooling already integrated: VS Code GitHub Copilot built-in tools and widely-adopted MCP tools are already used by existing agents

### Before Submitting

When planning to submit an agent that falls into these categories:

1. Question necessity: does your use case truly require a new agent, or can existing agents meet your needs?
2. Review existing agents: examine `.github/agents/` to identify agents that already serve your purpose
3. Check tool integration: verify whether the VS Code GitHub Copilot tools or MCP tools you need are already used by existing agents
4. Consider enhancement over creation: if existing agents don't fully meet your requirements, evaluate whether your changes are generic enough to benefit all users and valuable enough to justify modifying the existing agent
5. Propose enhancements: submit a PR to enhance an existing agent rather than creating a duplicate

### What Makes a Good New Agent

Focus on agents that:

| Criterion            | Description                                                                                     |
|----------------------|-------------------------------------------------------------------------------------------------|
| Fill gaps            | Address use cases not covered by existing agents                                                |
| Provide unique value | Offer specialized domain expertise or workflow patterns not present in the library              |
| Are non-overlapping  | Have clearly distinct purposes from existing agents                                             |
| Cannot be merged     | Represent functionality too specialized or divergent to integrate into existing agents          |
| Use standard tooling | Use widely-supported VS Code GitHub Copilot tools and MCP tools rather than custom integrations |

### Model Version Requirements

All agents **MUST** target the **latest available models** from **Anthropic and OpenAI only**.

Accepted: Latest Claude models (e.g., Claude Sonnet 4, Claude Opus 4) and latest GPT models (e.g., GPT-5.1, o1)

Not Accepted: Older model versions (e.g., GPT-3.5, GPT-4.1, Claude 2), models from other providers, custom/fine-tuned models

Rationale: Latest models provide superior capabilities, reduce maintenance burden, and ensure future compatibility. Older model versions will be deprecated.

## File Structure Requirements

### Location

Agent files are typically organized in a collection subdirectory by convention:

```text
.github/agents/{collection-id}/
├── your-agent-name.agent.md
└── subagents/
    └── your-subagent-name.agent.md
```

> [!NOTE]
> Collections can reference artifacts from any subfolder. The `path:` field in collection YAML files
> accepts any valid repo-relative path regardless of the artifact's parent directory.

### Naming Convention

* Use lowercase kebab-case: `security-reviewer.agent.md`
* Be descriptive and action-oriented: `task-planner.agent.md`, `pr-review.agent.md`, `rpi-agent.agent.md`
* Avoid generic names: `helper.agent.md` ❌ → `ado-work-item-processor.agent.md` ✅

### File Format

Agent files MUST:

1. Use the `.agent.md` extension
2. Start with valid YAML frontmatter between `---` delimiters
3. Begin content directly after frontmatter
4. End with single newline character

## Frontmatter Requirements

### Required Fields

**`description`** (string, MANDATORY)

| Attribute | Details                                                                              |
|-----------|--------------------------------------------------------------------------------------|
| Purpose   | Concise explanation of agent functionality                                           |
| Format    | Single sentence, 10-200 characters                                                   |
| Style     | Sentence case with proper punctuation                                                |
| Example   | `'Validates contributed content for quality and compliance with hve-core standards'` |

### Optional Fields

**`name`** (string)

| Attribute | Details                                                  |
|-----------|----------------------------------------------------------|
| Purpose   | Custom display name for the agent                        |
| Format    | Lowercase kebab-case matching filename without extension |
| Default   | File name used if not specified                          |

**`tools`** (array of strings)

| Attribute | Details                                                        |
|-----------|----------------------------------------------------------------|
| Purpose   | Lists GitHub Copilot tools available to this agent             |
| Format    | Array of valid tool names in logical order (read before write) |

Valid tools:

* `codebase` - Semantic code search
* `search` - Grep/regex search
* `problems` - Error/warning diagnostics
* `editFiles` - File modification
* `changes` - Git change tracking
* `usages` - Symbol reference search
* `githubRepo` - External GitHub repository search
* `fetch` - Web page content retrieval
* `runCommands` - Terminal command execution
* `think` - Extended reasoning
* `findTestFiles` - Test file discovery
* `terminalLastCommand` - Terminal history
* `searchResults` - Search view results
* `edit/createFile` - File creation
* `edit/createDirectory` - Directory creation
* `Bicep (EXPERIMENTAL)/*` - Bicep tooling
* `terraform/*` - Terraform tooling
* `context7/*` - Library documentation
* `microsoft-docs/*` - Microsoft documentation

**`agents`** (array of strings)

| Attribute   | Details                                                                            |
|-------------|------------------------------------------------------------------------------------|
| Purpose     | Declares subagent dependencies available to this agent                             |
| Format      | Array of agent names. Use `*` to allow all agents, or `[]` to prevent subagent use |
| Requirement | When specified, include the `agent` tool in the `tools` property                   |

**`model`** (string or array of strings)

| Attribute | Details                                                                                      |
|-----------|----------------------------------------------------------------------------------------------|
| Purpose   | Specifies the AI model for this agent                                                        |
| Format    | Single model name or prioritized list of models (system tries each in order until available) |
| Default   | Currently selected model in model picker when omitted                                        |

**`user-invocable`** (boolean)

| Attribute | Details                                                         |
|-----------|-----------------------------------------------------------------|
| Purpose   | Controls whether the agent appears in the agents dropdown       |
| Default   | `true`                                                          |
| Usage     | Set to `false` for agents that are only accessible as subagents |

**`disable-model-invocation`** (boolean)

| Attribute | Details                                                                                                       |
|-----------|---------------------------------------------------------------------------------------------------------------|
| Purpose   | Prevents the agent from being invoked as a subagent by other agents                                           |
| Default   | `false`                                                                                                       |
| Usage     | Set to `true` for agents that run subagents, cause side effects, or should only run when explicitly requested |

**`argument-hint`** (string)

| Attribute | Details                                                 |
|-----------|---------------------------------------------------------|
| Purpose   | Hint text shown in the chat input field to guide users  |
| Format    | Brief text with required arguments first, then optional |

**`target`** (string enum)

| Attribute    | Details                                 |
|--------------|-----------------------------------------|
| Purpose      | Target environment for the custom agent |
| Valid values | `vscode`, `github-copilot`              |

**`mcp-servers`** (array of objects)

| Attribute | Details                                            |
|-----------|----------------------------------------------------|
| Purpose   | MCP server configuration for GitHub Copilot agents |
| Usage     | Only applicable when `target: github-copilot`      |

**`handoffs`** (array of objects)

| Attribute    | Details                                                            |
|--------------|--------------------------------------------------------------------|
| Purpose      | Declares agent-to-agent handoff buttons that appear in the chat UI |
| Format       | Array of handoff declarations                                      |
| Requirements | VS Code 1.106+ required for handoff support                        |

Fields per handoff:

* `label` (string, required): Button text displayed in UI, supports emoji
* `agent` (string, required): Target agent filename without `.agent.md` extension
* `prompt` (string, optional): Pre-filled prompt text, can include slash commands
* `send` (boolean, optional): When true, auto-submits prompt; when false (default), user can edit
* `model` (string, optional): Language model override for the handoff execution

Example:

```yaml
  handoffs:
    - label: "📋 Create Plan"
      agent: Task Planner
      prompt: /task-plan
      send: true
  ```

### Deprecated Fields

**`infer`** (boolean)

| Attribute         | Details                                                                                                                         |
|-------------------|---------------------------------------------------------------------------------------------------------------------------------|
| Status            | Deprecated. Use `user-invocable` and `disable-model-invocation` instead.                                                        |
| Previous behavior | `infer: true` (default) made the agent both visible in the picker and available as a subagent. `infer: false` hid it from both. |

### Frontmatter Example

```yaml
---
description: 'Validates and reviews contributed agents, prompts, and instructions for quality and compliance'
tools: ['codebase', 'search', 'problems', 'editFiles', 'changes', 'usages']
disable-model-invocation: true
agents:
  - Prompt Tester
  - Prompt Evaluator
---
```

## Collection Entry Requirements

All agents must have matching entries in one or more `collections/*.collection.yml` manifests. Collection entries control selection and maturity.

### Adding Your Agent to a Collection

After creating your agent file, add an `items[]` entry to each target collection:

```yaml
items:
  # path can reference artifacts from any subfolder
  - path: .github/agents/{collection-id}/my-new-agent.agent.md
  kind: agent
  maturity: stable
```

### Selecting Collections for Agents

Choose collections based on who benefits most from your agent:

| Agent Type             | Recommended Collections                   |
|------------------------|-------------------------------------------|
| Task workflow agents   | `hve-core-all`, `hve-core`                |
| Architecture agents    | `hve-core-all`, `project-planning`        |
| Documentation agents   | `hve-core-all`, `hve-core`                |
| Data science agents    | `hve-core-all`, `data-science`            |
| Design thinking agents | `hve-core-all`, `design-thinking`         |
| ADO/work item agents   | `hve-core-all`, `ado`, `project-planning` |
| Code review agents     | `hve-core-all`, `hve-core`                |

### Declaring Agent Dependencies

If your agent dispatches other agents at runtime via `runSubagent`, invokes prompts, or depends on skills, document those relationships in the agent content and validate packaging behavior in affected collections.

For complete collection documentation, see [AI Artifacts Common Standards - Collection Manifests](ai-artifacts-common.md#collection-manifests-and-dependencies).

### MCP Tool Dependencies

When agents reference MCP tools in their `tools:` frontmatter or body content, document the dependencies clearly.

#### Frontmatter Declaration

```yaml
tools: ['github/*', 'ado/*', 'context7/*', 'microsoft-docs/*']
```

#### Curated MCP Servers Referenced by HVE Core Agents

| Server         | Tool Pattern       | Purpose                                   |
|----------------|--------------------|-------------------------------------------|
| github         | `github/*`         | GitHub repository and issue management    |
| ado            | `ado/*`            | Azure DevOps work items, pipelines, repos |
| context7       | `context7/*`       | Library and SDK documentation lookup      |
| microsoft-docs | `microsoft-docs/*` | Microsoft Learn documentation             |

#### Guidelines for MCP Tool References

* Document MCP dependencies in agent body text when using `mcp_*` tool patterns
* Agents should gracefully handle missing MCP servers (tools unavailable)
* Reference the [MCP Server Configuration](../getting-started/mcp-configuration.md) guide when agents require MCP tools
* Prefer built-in VS Code Copilot tools when equivalent functionality exists

## Agent Content Structure Standards

### Required Sections

#### 1. Title (H1)

* Clear, action-oriented heading matching agent purpose
* Should align with filename and description

```markdown
# Content Validator Agent
```

#### 2. Overview/Role Definition

* Explains what the agent does and when to use it
* Defines scope and boundaries
* Sets expectations for users

```markdown
You are an expert reviewer for GitHub Copilot agents, prompts, and instruction files.
Your mission is to ensure all contributed guidance files meet hve-core quality standards
before they're merged into the library.
```

#### 3. Core Directives/Instructions

* Uses clear, imperative language
* Employs RFC 2119 keywords consistently:
  * MUST, WILL, MANDATORY, and CRITICAL indicate required behavior
  * SHOULD and RECOMMENDED indicate strong guidance
  * MAY and OPTIONAL indicate permitted but not required behavior
* Provides step-by-step workflows
* Includes decision points and branching logic

#### 4. Examples and Templates

* Demonstrates correct usage patterns
* Shows both positive (✅) and negative (❌) examples
* Wraps in XML-style blocks for reusability

#### 5. Success Criteria

* Defines completion conditions
* Specifies validation checkpoints
* Lists quality gates

#### 6. Attribution Footer

Include at end of file (MANDATORY):

```markdown
---

Brought to you by microsoft/hve-core
```

### XML-Style Block Requirements

See [AI Artifacts Common Standards - XML-Style Block Standards](ai-artifacts-common.md#xml-style-block-standards) for complete rules and examples.

### Directive Language Standards

Use RFC 2119 compliant keywords (MUST/SHOULD/MAY). See [AI Artifacts Common Standards - RFC 2119 Directive Language](ai-artifacts-common.md#rfc-2119-directive-language) for complete guidance.

## Tool Usage Discipline

When agents use tools, they **MUST** follow these patterns:

### Tool Usage Preambles

Before any batch of tool calls, include a one-sentence explanation:

```markdown
Tool Usage Preamble: "Analyzing file structure, reading schemas, and checking
repository conventions to establish validation baseline."
```

### Checkpoints

After 3-5 tool calls or more than 3 file edits, provide a compact checkpoint:

```markdown
Checkpoint After Discovery: "Identified [file type], loaded [schema name],
found [N] related files for comparison."
```

### Tool Result Integration

* Document how tool results inform next steps
* Specify error handling for tool failures
* Justify tool selection (why this tool for this task)

## Output Formatting Requirements

Define how the agent communicates with users:

### Response Format

* Start all responses with: `## [Agent Name]: [Action Description]`
* Use short, action-oriented section headers
* Employ proper markdown formatting
* Include emojis for visual clarity (when appropriate)

### Status Reporting

Specify formats for:

* Progress updates
* Error messages
* Completion confirmations
* Validation results

### Requirements Checklist

For agents performing edits or validations:

```markdown
### Requirements Checklist

- [x] Pre-validation analysis complete - Loaded schema, checked conventions
- [x] Frontmatter validation - All required fields present
- [ ] Technical validation - 2 broken file references found
```

### Quality Gates

Report validation status:

```markdown
### Quality Gates

- Build: PASS
- Lint: FAIL - Markdownlint flagged: bare URLs (lines 45, 67)
- Schema: PASS - Frontmatter validates
```

## Research and External Sources

When agents integrate external knowledge, consult authoritative sources and provide minimal, annotated snippets with reference links. See [AI Artifacts Common Standards - Attribution Requirements](ai-artifacts-common.md#attribution-requirements) for guidelines.

## Validation Checklist

Before submitting your agent, verify:

### Frontmatter

* [ ] Valid YAML between `---` delimiters
* [ ] `description` field present and descriptive (10-200 chars)
* [ ] `tools` array contains only valid tool names (if present)
* [ ] `agents` array contains valid subagent names (if present)
* [ ] `user-invocable` and `disable-model-invocation` used correctly (if present)
* [ ] No trailing whitespace in values
* [ ] Single newline at EOF

### Content Structure

* [ ] Clear H1 title matching purpose
* [ ] Overview/role definition section
* [ ] Core directives with RFC 2119 keywords
* [ ] Examples wrapped in XML-style blocks
* [ ] Success criteria defined
* [ ] Attribution footer present

### Common Standards

* [ ] Markdown quality (see [Common Standards - Markdown Quality](ai-artifacts-common.md#markdown-quality-standards))
* [ ] XML-style blocks properly formatted (see [Common Standards - XML-Style Blocks](ai-artifacts-common.md#xml-style-block-standards))
* [ ] RFC 2119 keywords used consistently (see [Common Standards - RFC 2119](ai-artifacts-common.md#rfc-2119-directive-language))

### Technical Validation

* [ ] All file references point to existing files
* [ ] External links are valid and accessible
* [ ] Tool names in frontmatter are correct
* [ ] No conflicts with existing agents

### Integration

* [ ] Aligns with `.github/copilot-instructions.md`
* [ ] Follows repository conventions
* [ ] Compatible with existing workflows
* [ ] Does not duplicate existing agent functionality

## Testing Your Agent

See [AI Artifacts Common Standards - Common Testing Practices](ai-artifacts-common.md#common-testing-practices) for testing guidelines. For agents specifically:

1. Test with realistic scenarios matching the agent's purpose
2. Verify tool usage patterns execute correctly
3. Ensure decision points and branching logic work as intended
4. Check edge cases: missing data, invalid inputs, tool failures

## Common Issues and Fixes

### Agent-Specific Issues

### Invalid Tool Names

Referencing tools that don't exist or using incorrect camelCase variants. Use exact tool names from VS Code Copilot's available tools list.

For additional common issues (XML blocks, markdown, directives), see [AI Artifacts Common Standards - Common Issues and Fixes](ai-artifacts-common.md#common-issues-and-fixes).

## Automated Validation

Run these commands before submission (see [Common Standards - Common Validation](ai-artifacts-common.md#common-validation-standards)):

* `npm run lint:frontmatter`
* `npm run lint:md`
* `npm run spell-check`
* `npm run lint:md-links`

All checks **MUST** pass before merge.

## Related Documentation

* [AI Artifacts Common Standards](ai-artifacts-common.md) - Shared standards for all contributions
* [Contributing Prompts](prompts.md) - Workflow-specific guidance files
* [Contributing Instructions](instructions.md) - Technology-specific standards
* [Pull Request Template](https://github.com/microsoft/hve-core/blob/main/.github/PULL_REQUEST_TEMPLATE.md) - Submission requirements

## Getting Help

See [AI Artifacts Common Standards - Getting Help](ai-artifacts-common.md#getting-help) for support resources. For agent-specific assistance, review existing examples in `.github/agents/{collection-id}/` (the conventional location for agent files).

---

<!-- markdownlint-disable MD036 -->
*🤖 Crafted with precision by ✨Copilot following brilliant human instruction,
then carefully refined by our team of discerning human reviewers.*
<!-- markdownlint-enable MD036 -->