Frequently Asked Questions

General Questions

What is AI4Curators?

AI4Curators is a project focused on providing practical guides for curators and maintainers of knowledge bases to integrate AI into their workflows. Rather than theoretical discussions, we emphasize immediate, actionable integration strategies that work with existing GitHub-based workflows.

Our core mission includes: - Helping curators integrate AI agents into existing GitHub-based workflows - Providing plugins and tools for existing chat UIs
- Supporting ontology editing and curation workflows with AI assistance

The project serves both as documentation and a practical example of AI agent integration, where GitHub agents can directly contribute to documentation and examples demonstrate real-world AI-assisted curation workflows.

GitHub Copilot Integration

Why can't GitHub Copilot access OBO PURLs like purl.obolibrary.org?

GitHub Copilot's coding agent includes a firewall that restricts internet access by default to prevent data exfiltration risks. While the agent can access GitHub-related hosts and a recommended allowlist of common package repositories, it blocks access to custom domains like purl.obolibrary.org that are commonly used in ontology workflows.

The Solution: Repository administrators can allowlist additional hosts in the Copilot firewall settings:

1. Navigate to your repository's Settings tab
2. Select Copilot, then coding agent from the Code & automation sidebar
3. Click Custom allowlist
4. Add purl.obolibrary.org (or specific URL paths) to the allowlist
5. Click Add Rule, then Save changes

Allowlist formats: - Domain: purl.obolibrary.org - allows the domain and all subdomains - URL: https://purl.obolibrary.org/obo/ - restricts to specific scheme, host, and path

Workaround: Until the firewall is configured, use direct GitHub URLs instead of PURLs: - ✅ Works: https://raw.githubusercontent.com/oborel/obo-relations/refs/heads/master/ro-base.owl - ❌ Blocked: http://purl.obolibrary.org/obo/ro/ro-base.owl

For more details, see the GitHub Copilot documentation and GitHub's guide on customizing the agent firewall.

Agent Harness and Infrastructure

What is an agent harness?

An agent harness is the infrastructure that wraps around an AI agent to manage its execution — context management, tool orchestration, validation, provenance, and human-in-the-loop controls. It's the difference between an agent that sometimes works and one that's reliable and auditable.

The same model behaves differently depending on the harness around it. Getting the harness right matters more than picking the "best" model.

See Build your agentic harness for a practical guide.

What tools are available for validating agent outputs?

Two key validators:

• linkml-term-validator — checks that ontology terms referenced in agent outputs actually exist and are used correctly
• linkml-reference-validator — checks that cited references actually contain the claimed supporting text

Both can be integrated into CI pipelines to automatically validate agent-generated pull requests. See Agentic tools for details.

How do I track which changes an AI agent made?

Use ai-blame, which extracts provenance and audit trails from agent execution traces. It provides line-level attribution, so you can see exactly which changes the agent made, when, and in what context.

What MCP servers are available for ontology work?

• noctua-mcp — GO-CAM editing via Noctua/Barista
• oak-mcp — ontology search, traversal, and operations via OAK
• owl-mcp — general OWL ontology operations

These give agents structured access to domain-specific operations instead of raw file manipulation.