From screenshot to issue: Copilot's new issue workflows

Issue tracking is often the least loved part of software development: verbose bug reports, inconsistent tagging, and the constant context-switching between discovery and documentation. GitHub Copilot now handles much of that administrative load, letting developers draft, categorize, and even fix issues through natural-language prompts. Here’s what the current feature set covers.

Turn images into reproducible bug reports

Pasting a screenshot into Copilot Chat with a short instruction—for example, "create me a bug issue because markdown tables are not rendering properly in the comments"—prompts the tool to inspect the image and generate a full bug report on its own. That report can include suggested steps to reproduce, removing the need to articulate visual glitches or UI alignment problems in words.

For more precise output, annotate the screenshot first. Highlighting or circling the problem area gives Copilot clear visual references and tends to produce issue descriptions that match what you actually see.

Automatic templates, labels, and issue types

Manually setting metadata for each issue is where discipline tends to drift. Copilot cuts out the dropdown navigation by inferring the suitable template from the prompt and attaching labels and issue types as it drafts. If you need to override the defaults, you can ask for specific tags such as priority: high, frontend, or needs-triage, or demand a given template or type like "Bug Report," "Feature Request," "Task," or "Epic."

Switching templates after a draft is already written is equally straightforward: Copilot reformats the content to match the new template rather than forcing you to rebuild the issue manually.

Scaling up with milestones and batch creation

Keeping a repository organized shouldn't rely on remembering to attach every project and milestone by hand. Type the request and Copilot applies that context when it creates the issue. All changes remain tracked, so you can look back at issue history and roll back modifications if anything gets out of place.

For the busy periods—after a customer meeting, user testing session, or bug bash—Copilot supports drafting several issues in a single conversation. You can ask for two issues at once:

Create me issues for the following features:
- Line breaks ignored in rendered Markdown despite double-space
- Bold and italic Markdown styles not applied when combined

Each generated issue still needs a human review pass before finalization, but the drafting becomes a single step instead of a repetitive one.

Hand issues over to the coding agent

Creating an issue is only the start. If the goal is closure, you can assign an issue straight to Copilot coding agent, which will analyze the bug and propose workable fixes, including draft pull requests. That direct handoff reduces context switching and shortens the path from reported problem to submitted solution.

Across the wider GitHub issues experience

Beyond the AI-assisted workflow, GitHub has meanwhile expanded the base issues tooling. Organizations can standardize issue types across repositories, break complex tasks into sub-issues for granular tracking, use advanced search with logical operators to locate specific tickets, and manage up to 50,000 items per project. These features complement the Copilot prompts; together they cover the arc from detection to resolution without forcing you to leave the tool where the bug was found.

Prompts worth trying

To jump in, open Copilot and experiment with direct phrasing:

  • "Create me an issue for…"
  • "Log a bug for…"
  • Or upload a screenshot and state that you want to file a bug.

The value is not in eliminating issue management, but in turning it from overhead into a conversational handoff—the AI drafts the detail so you can review, adjust, and move on.