GitHub Copilot Chat: Semantic Issue Search via Natural Language

GitHub Copilot Chat: Semantic Issue Search via Natural Language

GitHub has introduced semantic issue search inside Copilot Chat on the web, enabling developers to locate GitHub issues using plain-language queries rather than relying on precise titles or keywords.

How It Works

The feature integrates a semantic indexing layer into Copilot Chat's issue retrieval system. When a developer types a natural language query — for example, "authentication failing on mobile" or "performance regression in the rendering pipeline" — Copilot Chat surfaces issues that are conceptually related, even if those issues use entirely different vocabulary in their titles or descriptions. The system combines semantic and keyword matching in the same query, so both conceptually similar results and exact matches are returned together.

This approach is meaningfully different from traditional GitHub issue search, which depends on exact term matching and manual filters. Semantic search understands query intent, bridging the gap between how a developer describes a problem and how the original issue reporter chose to phrase it.

Practical Use Cases

The feature is particularly useful for issue triage and sprint planning workflows, where teams need to quickly identify whether a reported problem has already been filed. Developers can ask questions like "are there any open issues related to slow CI times on Windows?" without knowing the precise label names, assignees, or title keywords used in existing issues. It is also valuable for onboarding — new contributors can orient themselves by asking about known problem areas in natural language.

Availability

Semantic issue search in Copilot Chat is generally available across all Copilot plans: Pro, Pro+, Business, and Enterprise. No configuration is required. Users can access it directly through Copilot Chat on github.com.