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docs/src/content/docs/guides/packaging-imports.md

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title: Packaging and Imports
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description: Complete guide to adding, updating, and importing workflows from external repositories using workflow specifications and import directives.
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This guide covers the complete workflow for packaging and importing agentic workflows from external repositories, including workflow specifications, CLI commands, and import mechanisms.

docs/src/content/docs/reference/command-triggers.md

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title: Command Triggers
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description: Learn about command triggers and context text functionality for agentic workflows, including special @mention triggers for interactive automation.
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GitHub Agentic Workflows add the convenience `command:` trigger to create workflows that respond to `/my-bots` in issues and comments.

docs/src/content/docs/reference/concurrency.md

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title: Concurrency Control
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description: Complete guide to concurrency control in GitHub Agentic Workflows, including agent job concurrency configuration and engine isolation.
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GitHub Agentic Workflows provides sophisticated concurrency control to manage how many AI-powered agent jobs can run simultaneously. This helps prevent resource exhaustion, control costs, and ensure predictable workflow execution.

docs/src/content/docs/reference/custom-safe-outputs.md

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title: Custom Safe Outputs
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description: Learn how to create custom safe outputs for third-party integrations using safe-jobs and MCP servers.
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Custom safe outputs enable you to extend GitHub Agentic Workflows with your own output processing logic for third-party services like Notion, Slack, Jira, or any custom API. This guide demonstrates how to create reusable, secure integrations using safe-jobs combined with MCP servers.

docs/src/content/docs/reference/engines.md

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title: AI Engines
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description: Complete guide to AI engines available in GitHub Agentic Workflows, including Claude, Copilot, Codex, and custom engines with their specific configuration options.
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description: Complete guide to AI engines (coding agents) usable with GitHub Agentic Workflows, including Claude, Copilot, Codex, and custom engines with their specific configuration options.
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GitHub Agentic Workflows support multiple AI engines to interpret and execute natural language instructions. Each engine has unique capabilities and configuration options.
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## Agentic Engines
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GitHub Agentic Workflows support multiple AI engines (coding agents) to interpret and execute natural language instructions. Each engine has unique capabilities and configuration options.
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### GitHub Copilot (Default)
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docs/src/content/docs/reference/frontmatter.md

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title: Frontmatter Options
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description: Complete guide to all available frontmatter configuration options for GitHub Agentic Workflows, including triggers, permissions, AI engines, and workflow settings.
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The YAML frontmatter supports standard GitHub Actions properties plus additional agentic-specific options:

docs/src/content/docs/reference/include-directives.md

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title: Imports
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description: Learn how to modularize and reuse workflow components across multiple workflows using the imports field in frontmatter for better organization and maintainability.
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The `imports:` field in frontmatter allows you to modularize and reuse workflow components across multiple workflows.
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## Frontmatter Imports
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The recommended way to import shared components is using the `imports:` field in the frontmatter:
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Imports can be specified either in frontmatter or in markdown. In frontmatter the `imports:` field is used:
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```aw wrap
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---
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Workflow instructions here...
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```
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In markdown, use the special `{{'#import ...}}` directive:
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```aw wrap
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---
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...
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---
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# Your Workflow
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Workflow instructions here...
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{{#import shared/common-tools.md}}
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```
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### Import Path Resolution
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- **Relative paths**: Resolved relative to the importing file
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## Frontmatter Merging
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When importing files, frontmatter fields are merged with the main workflow:
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- **Only `tools:` and `mcp-servers:` frontmatter** is allowed in imported files, other entries give a warning.
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- **Tool merging**: `allowed:` tools are merged across all imported files
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- **MCP server merging**: MCP servers defined in imported files are merged with the main workflow
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### Example Tool Merging
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```aw wrap
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# Base workflow
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---
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on: issues
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tools:
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github:
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allowed: [get_issue]
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imports:
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- shared/extra-tools.md
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---
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```
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```aw wrap
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# shared/extra-tools.md
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---
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tools:
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github:
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allowed: [add_issue_comment, update_issue]
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edit:
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---
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```
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**Result**: Final workflow has `github.allowed: [get_issue, add_issue_comment, update_issue]` and Claude Edit tool.
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### Example MCP Server Merging
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```aw wrap
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**Result**: Final workflow has the Tavily MCP server configured and available to the AI engine.
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## Legacy Directive Syntax (Deprecated)
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:::caution[Deprecated]
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The `{{#import}}`, `@import`, and `@include` directive syntax is deprecated. Use the `imports:` field in frontmatter instead.
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**Migration example:**
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```diff
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# Old approach
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---
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on: issues
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---
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- @import shared/extra-tools.md
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# New approach
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+ ---
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+ on: issues
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+ imports:
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+ - shared/extra-tools.md
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+ ---
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```
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:::
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## Related Documentation
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- [Packaging and Imports](/gh-aw/guides/packaging-imports/) - Complete guide to adding, updating, and importing workflows

docs/src/content/docs/reference/markdown.md

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title: Markdown Content
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description: Learn agentic workflow markdown content
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The markdown content is where you write natural language instructions for the AI agent.

docs/src/content/docs/reference/network.md

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title: Network Permissions
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description: Control network access for AI engines using ecosystem identifiers and domain allowlists
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Control network access for AI engines using the top-level `network` field. Network permissions provide fine-grained control over which domains and services your agentic workflows can access during execution.

docs/src/content/docs/reference/safe-jobs.md

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title: Safe Jobs
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description: Learn about safe-jobs feature that enables defining custom post-processing workflows with GitHub Actions job properties and artifact access.
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The `safe-outputs.jobs:` element of your workflow's frontmatter enables you to define custom post-processing jobs that execute after the main agentic workflow completes. Safe-jobs provide a powerful way to create sophisticated automation workflows while maintaining security through controlled job execution.

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