Add an "Explain This Pull Request" AI feature to help reviewers understand changes faster

[orgito1015]

🏷️ Discussion Type

Question

💬 Feature/Topic Area

Other

Body

🏷️ Discussion Type

Feature Request

💬 Feature/Topic Area

Pull Requests / GitHub Copilot / Code Review

Title

Add an "Explain This Pull Request" AI feature to help reviewers understand changes faster

Discussion Details
Summary

Large pull requests are becoming increasingly difficult to review. A PR may contain hundreds of changed files, multiple components, dependency updates, and architectural changes, making it challenging for reviewers to quickly understand the purpose and potential impact.

It would be useful to have an AI-powered feature that generates a clear explanation of a pull request before reviewing the code.

Proposed Feature

Add an "Explain This Pull Request" button that generates a summary containing:

What changed and why
Main files/components affected
Possible breaking changes
Security considerations
Performance impact
Database/API changes
Risk areas that reviewers should pay attention to

Example:

Pull Request Summary

Purpose:
Migrates authentication from session-based login to JWT tokens.

Main changes:
✓ Updated authentication middleware
✓ Added token refresh endpoint
✓ Modified user database schema

Potential risks:
⚠ Existing sessions will become invalid
⚠ API clients need updated authentication headers

Recommended review areas:

• auth/middleware.ts
• user-service.ts
• migration.sql
  Why this would help

Many reviewers spend the majority of their time trying to understand the context of a change before reviewing the actual code.

This feature could:

Reduce review time
Improve code quality
Help new contributors understand unfamiliar projects
Make large open-source contributions easier to review
Highlight possible risks earlier
Possible Integration

This could integrate with:

GitHub Copilot
CodeQL findings
Dependabot alerts
Repository documentation
Previous PR history

For example, GitHub could provide additional context:

"This PR modifies authentication code. Similar changes were introduced in PR #245, which fixed a session expiration issue."

Questions

Would other developers find this useful for large PR reviews?

What additional information would you want an AI PR summary to provide?

[JoaoArnaud]

[JoaoArnaud]

I would find this especially useful for large or unfamiliar pull requests.

A good AI-generated summary could reduce the time reviewers spend understanding the structure of the change before they begin reviewing the implementation. However, I think the feature should complement the PR description rather than replace documentation written by the author.

In addition to the proposed information, I would like the summary to include:

• A distinction between behavioral changes, refactoring, tests, documentation, and dependency updates.
• A list of public functions, APIs, database tables, environment variables, or configuration files that were changed.
• Test coverage information, including which important code paths were modified without corresponding tests.
• A dependency-impact section showing newly added, removed, or significantly updated packages.
• A visual dependency or call-flow overview for changes that affect multiple components.
• Links to the most relevant commits, issues, previous PRs, documentation, CodeQL alerts, and Dependabot findings.
• A confidence indicator when the AI is uncertain about the purpose or impact of a change.

It would also be helpful to let users customize the explanation based on their role. For example:

• A maintainer may want architectural risks and compatibility concerns.
• A security reviewer may want authentication, authorization, secrets, and input-validation changes.
• A database reviewer may want migrations, rollback risks, indexes, and data-loss concerns.
• A new contributor may prefer a simpler explanation of how the affected components work.

One concern is that reviewers could trust the generated summary without verifying the actual diff. GitHub should therefore clearly indicate that the explanation is AI-generated and may be incomplete. Ideally, every statement in the summary should link directly to the files, lines, commits, or findings that support it.

A useful addition could also be an “Ask about this PR” interface, allowing reviewers to ask questions such as:

• Could this change break backward compatibility?
• Which endpoints changed?
• Are there database migrations without a rollback?
• Which files deserve the most careful manual review?
• Are there changes unrelated to the stated purpose of the PR?

Overall, I think this feature could be very valuable, particularly when it provides traceable evidence and helps reviewers prioritize their attention instead of attempting to replace human review.

[duaaaalityyyy]

This would definitely be useful — and worth noting, a version of it already exists and is worth checking out before building further on this idea: Copilot code review / PR summaries in GitHub already generates an AI walkthrough of changed files on PRs (available via Copilot in supported plans), and there's also Copilot's "Summary" comment that gets auto-generated on some PRs describing what changed. So the core idea isn't hypothetical — it's partially shipped. Worth checking the current state of Copilot PR summaries in your org before proposing this as wholly new, since the gap might really be about depth (risk/security/breaking-change analysis) rather than existence of a summary feature at all.
That said, your proposal goes further than what exists today in a few useful ways:
What's genuinely missing from current tooling:

Explicit breaking-change / risk flagging. Current summaries tend to describe what changed, not what could break. A dedicated "here's what a consumer of this API/schema needs to know" section is a real gap.
Cross-referencing PR history. "Similar changes were introduced in PR #245" is a great idea and isn't something Copilot does today — this would require indexing merged PR history and diffing semantic similarity, which is a heavier lift but high value, especially for large/old repos.
Integrating CodeQL + Dependabot context into the summary rather than as separate tabs/checks. Right now you have to go look at three different places (PR diff, Security tab, Dependabot alerts) to get the full risk picture. Pulling those into one narrative would save real review time.

Things I'd push back on slightly or flag as hard:

Database/API schema change detection is doable but needs to be scoped carefully — false positives (flagging a change as "breaking" when it's additive/backward-compatible) will erode trust in the feature fast if it's not accurate. This is probably the hardest part to get right.
Performance impact is the vaguest of your asks — without actually running benchmarks, an LLM summary of "performance impact" from a diff alone is going to be speculative at best. I'd deprioritize this one or scope it down to "flags PRs that touch known-hot-path files" rather than claiming to predict actual performance.

What I'd want as a reviewer, in priority order:

Breaking-change / compatibility flags (highest value, most trustworthy if scoped well)
"Files most likely to need careful review" ranked by risk, not just size
Security-relevant diffs surfaced explicitly (auth, permissions, input validation changes)
Linked prior PRs/issues for context
Plain-language purpose summary (lowest value add since this is closest to what already exists)

[minksy-ux]

the real leverage comes from contextual and inferential layers beyond surface diffs.. evolves beyond summarization into context aware risk prioritized reasoning over code changes vs others