Add Examples gallery documenting AI4Curation implementations

[dragon-ai-agent]

Summary

This PR addresses issue #47 by creating a new Examples documentation page that serves as a gallery of repositories using AI agent integration for knowledge base curation.

Changes Made

New Documentation

• docs/examples.md - Comprehensive gallery page featuring:
  • Ontology repositories (Mondo, Cell Ontology, Uberon, EFO, NAMO)
  • Documentation repositories (this repo as self-example)
  • Key configuration files to explore in each repository
  • Detailed descriptions of agent platforms and their features
  • Learning resources and exploration guides
  • Contribution guidelines for adding new examples

Navigation Update

• mkdocs.yml - Added "Examples" page to main navigation (positioned after FAQ)

Featured Repositories

Ontology Repositories

1. Mondo Disease Ontology (monarch-initiative/mondo)

   • Exemplar dragon-ai-agent implementation
   • Links to workflow, instructions, and configuration files

2. Cell Ontology (obophenotype/cell-ontology)

   • Part of unified pipeline effort

3. Uberon Anatomy Ontology (obophenotype/uberon)

   • Demonstrates GitHub Copilot integration

4. Additional: EFO, NAMO (mentioned in unification discussions)

Documentation

• This repository (ai4curation/aidocs) as a meta-example

Platform Comparison

The page includes a comparison of different agent platforms:

• Goose (via dragon-ai-agent)
• Claude Code
• GitHub Copilot

Each with strengths, setup requirements, and API details.

Related to Issue #40

This gallery supports the pipeline unification effort by:

• Documenting current implementations
• Enabling comparison of different approaches
• Providing starting points for standardization
• Showcasing the ai4curation ecosystem

Learning Resources

The page includes:

• Links to existing how-to guides
• Guidance on what to look for in example repos
• Contribution guidelines for community growth

Future Iterations

As suggested by @cmungall in issue #47, this is a starting point that can be iterated upon. Future enhancements could include:

• Additional repositories as they're discovered
• More detailed comparisons of approaches
• Example PRs from each implementation
• Video walkthroughs or tutorials

Testing

• Verified markdown formatting
• Checked all internal links
• Confirmed external GitHub links are accurate
• Ensured examples.md is properly added to mkdocs navigation

Fixes #47

🤖 Generated with Claude Code

[claude]

Claude finished @dragon-ai-agent's task —— View job

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PR Review: Examples Gallery Documentation

Review Tasks

• Read project guidelines (CLAUDE.md)
• Review new examples.md file
• Review mkdocs.yml changes
• Check for technical issues
• Provide comprehensive feedback

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✅ Overall Assessment

This PR successfully addresses issue #47 by creating a comprehensive examples gallery that showcases AI agent integration across the ontology curation ecosystem. The implementation aligns well with the project's core mission of providing practical, actionable guidance for curators.

🔍 Code Quality & Best Practices

Strengths:

• Excellent structure: The examples.md follows a logical organization from ontology repos → documentation repos → platform comparisons → resources
• Practical focus: Aligns perfectly with CLAUDE.md guidelines emphasizing "practical, immediately actionable content"
• Comprehensive coverage: Documents multiple agent platforms (Goose, Claude Code, GitHub Copilot) with their trade-offs
• Learning-oriented: Includes clear guidance on "what to look for" in example repositories

Technical Implementation:

• ✅ mkdocs.yml correctly adds the Examples page to navigation in the appropriate position (after FAQ)
• ✅ Internal links to existing how-to guides are valid (docs/how-tos/set-up-github-actions.md, docs/how-tos/instruct-github-agent.md)
• ✅ Markdown formatting is consistent and follows Material theme conventions

🎯 Content Quality

Excellent Documentation Practices:

• Key Files sections: Provides specific file paths users should examine (.github/workflows/ai-agent.yml, CLAUDE.md, .config/goose/config.yaml)
• Platform comparison: Objective analysis of different agent platforms with clear strengths/setup requirements
• Actionable guidance: "Learning from These Examples" section gives practical exploration tips
• Community building: Includes contribution guidelines and future directions

Domain Expertise:

• Accurately represents the OBO ontology ecosystem
• Demonstrates understanding of agent platform differences
• References relevant issues (Unify all the different ontology pipelines #40, Create a list of exemplar repos that use ai4curation setup #47) for context

🔗 Link Validation

Internal Links: ✅ All confirmed valid

• how-tos/set-up-github-actions.md ✅
• how-tos/instruct-github-agent.md ✅
• Issue links point to correct GitHub issues ✅

External Links: The PR includes several GitHub repository links that should be verified during final testing, but the URLs follow correct GitHub patterns.

🛡️ Security & Performance

No security concerns identified:

• No executable code or scripts
• Only documentation and configuration changes
• External links are to public GitHub repositories

Performance considerations:

• Minimal impact - adds one documentation page
• No heavy assets or complex processing

📋 Test Coverage

Documentation Testing:

• ✅ Markdown syntax is valid
• ✅ Navigation structure is correct
• ⚠️ Recommendation: Run mkdocs serve locally to verify rendering and link behavior

🎨 Suggestions for Enhancement

1. Repository status badges: Consider adding build/CI status badges for the featured repositories to show their current health
2. Screenshot examples: Future iterations could include screenshots of agent interactions
3. Metrics: Consider adding information about adoption levels or community usage

🏆 Alignment with Project Goals

This PR excellently supports the project's core mission:

• ✅ Practical focus: Provides immediately actionable examples
• ✅ Community building: Creates a central discovery mechanism for implementations
• ✅ Integration emphasis: Shows how AI enhances existing workflows
• ✅ Learning-oriented: Guides users on exploration patterns

🚀 Recommendation

Approve and merge - This is a high-quality contribution that significantly enhances the documentation value for the AI4Curation community. The implementation is technically sound, content is comprehensive and well-structured, and it aligns perfectly with the project's guidelines and mission.

The examples gallery will serve as an excellent entry point for practitioners looking to understand and implement AI agent integration in their own curation workflows.

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[Copilot]

Pull Request Overview

This PR adds a comprehensive Examples page to the AI4Curators documentation that serves as a gallery of repositories implementing AI agent integration for knowledge base curation. The page addresses issue #47 by documenting real-world implementations across multiple ontology and documentation repositories.

Key Changes:

• Created new documentation page showcasing 5+ repositories using AI4Curation approaches
• Added platform comparison section covering Goose, Claude Code, and GitHub Copilot
• Included learning resources and contribution guidelines for community growth

Reviewed Changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 2 comments.

File	Description
mkdocs.yml	Added "Examples" page to navigation menu between FAQ and Curator how-tos sections
docs/examples.md	New comprehensive gallery page featuring ontology repositories (Mondo, Cell Ontology, Uberon, EFO, NAMO), documentation repositories, platform comparisons, and contribution guidelines

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💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.

[Copilot]

The CLAUDE.md file reference should be formatted as a hyperlink to maintain consistency with other repository examples. For instance, the Mondo Disease Ontology section (lines 15-17) includes hyperlinks to similar files.

Suggested change:

- [CLAUDE.md](https://github.com/obophenotype/cell-ontology/blob/master/CLAUDE.md) - Agent instructions for cell ontology curation

Suggested change

	- CLAUDE.md - Agent instructions for cell ontology curation
	- [CLAUDE.md](https://github.com/obophenotype/cell-ontology/blob/master/CLAUDE.md) - Agent instructions for cell ontology curation

[Copilot]

The link for .config/goose/config.yaml currently points to a tree directory view (/tree/master/.config/goose) rather than the actual file. If you want to link directly to the configuration file, the link should be:

- [.config/goose/config.yaml](https://github.com/monarch-initiative/mondo/blob/master/.config/goose/config.yaml) - Goose configuration with MCP extensions

If the intention is to show the directory because there are multiple relevant files, consider updating the link text to reflect this:

- [.config/goose/](https://github.com/monarch-initiative/mondo/tree/master/.config/goose) - Goose configuration with MCP extensions

Suggested change

	- [.config/goose/config.yaml](https://github.com/monarch-initiative/mondo/tree/master/.config/goose) - Goose configuration with MCP extensions
	- [.config/goose/config.yaml](https://github.com/monarch-initiative/mondo/blob/master/.config/goose/config.yaml) - Goose configuration with MCP extensions

[dragon-ai-agent]

PR Updated Per Issue #47 Feedback

I've amended the examples page as requested:

Changes Made

✅ Removed all content after 'Documentation Repositories' section

• Deleted: Learning from These Examples
• Deleted: Comparison of Agent Platforms
• Deleted: Related Resources
• Deleted: Contributing to This Gallery
• Deleted: Future Directions

✅ Added EFO (Experimental Factor Ontology)

• Repository: EBISPOT/efo
• Agent Platform: GitHub Copilot
• Includes search link for Copilot activity

✅ Added search links for each repository

• Mondo: Search for @dragon-ai-agent mentions and PRs
• Cell Ontology: Search for @dragon-ai-agent mentions and PRs
• Uberon: Search for @dragon-ai-agent mentions and PRs
• EFO: Search for Copilot activity
• aidocs: Search for @dragon-ai-agent mentions and PRs

✅ Removed generic verbiage

• Removed introductory paragraph
• Removed "Notable Features" bullet points from Mondo
• Removed descriptive sentences from Cell Ontology and Uberon
• Removed descriptive sentence from aidocs
• Kept only specific, factual information

The page is now more concise and focused on concrete examples with direct links to agent activity in each repository.

[claude]

Claude finished @dragon-ai-agent's task —— View job

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PR Review: Examples Gallery Documentation

Review Tasks

• Read project guidelines (CLAUDE.md)
• Review new examples.md file
• Review mkdocs.yml changes
• Check for technical issues
• Provide comprehensive feedback

---

✅ Overall Assessment

This PR successfully addresses issue #47 by creating a streamlined examples gallery that showcases AI agent integration across the ontology curation ecosystem. The updated implementation aligns well with the project's core mission of providing practical, actionable guidance for curators.

🔍 Code Quality & Best Practices

Strengths:

• Excellent streamlining: The examples.md follows feedback from issue Create a list of exemplar repos that use ai4curation setup #47, removing generic verbiage and focusing on concrete examples
• Practical focus: Aligns perfectly with CLAUDE.md guidelines emphasizing "practical, immediately actionable content"
• Clear organization: Clean structure from ontology repos → documentation repos with consistent formatting
• Searchable activity: Each repository includes direct search links to find agent activity and PRs

Technical Implementation:

• ✅ mkdocs.yml correctly adds the Examples page to navigation in the appropriate position (after FAQ)
• ✅ File structure follows established patterns in the repository
• ✅ Markdown formatting is clean and consistent

🎯 Content Quality

Excellent Documentation Practices:

• Specific file references: Provides exact file paths users should examine (.github/workflows/ai-agent.yml, CLAUDE.md, .config/goose/config.yaml)
• Direct action links: Agent activity search links make it easy to explore real implementations
• Repository diversity: Covers multiple platforms (Goose, GitHub Copilot, Claude Code) across different ontology types
• Self-reference: Includes this repository as a meta-example, demonstrating the approach

Domain Expertise:

• Accurately represents the OBO ontology ecosystem
• Demonstrates understanding of different agent platforms and their applications
• Shows practical knowledge of where to find agent configuration and activity

🔗 Link Validation & Technical Issues

Identified Issues:

1. Cell Ontology CLAUDE.md link (line 21): Missing hyperlink formatting and URL

   Current: - CLAUDE.md - Agent instructions
   Should be: - [CLAUDE.md](https://github.com/obophenotype/cell-ontology/blob/master/CLAUDE.md) - Agent instructions

2. Mondo Goose config link (line 11): Links to directory tree instead of specific file

   Current: [.config/goose/config.yaml](https://github.com/monarch-initiative/mondo/tree/master/.config/goose)
   Should be: [.config/goose/config.yaml](https://github.com/monarch-initiative/mondo/blob/master/.config/goose/config.yaml)

Verified Links:

• ✅ Internal repository structure is correct
• ✅ All GitHub repository URLs follow correct patterns
• ✅ Search query links are properly formatted

🛡️ Security & Performance

No security concerns identified:

• No executable code or scripts
• Only documentation and configuration changes
• External links are to public GitHub repositories

Performance considerations:

• ✅ Minimal impact - adds one documentation page
• ✅ No heavy assets or complex processing
• ✅ Fast loading with simple markdown content

📋 Recommendations

1. Fix the two link formatting issues identified above
2. Consider adding repository descriptions: Brief one-line descriptions of what each ontology covers could help users choose relevant examples
3. Future enhancement: As mentioned in the PR comments, this provides a good foundation for iteration

🏆 Alignment with Project Goals

This PR excellently supports the project's core mission:

• ✅ Practical focus: Provides immediately actionable examples with direct links
• ✅ Community building: Creates a central discovery mechanism for AI4Curation implementations
• ✅ Integration emphasis: Shows real-world agent integration across multiple repositories
• ✅ Learning-oriented: Guides users to specific files and search queries for exploration

🚀 Recommendation

Approve with minor fixes - This is a high-quality contribution that significantly enhances the documentation value. The two link formatting issues are minor and easily addressed. The streamlined approach per issue #47 feedback makes the page much more focused and useful.

The examples gallery will serve as an excellent entry point for practitioners looking to understand and implement AI agent integration in their own curation workflows.

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