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Nav: Discover > Deep Research Topical matching tells you what a paper is about. It doesn’t tell you where an approach sits in the field, what’s still unsolved, or which concrete change is worth trying in your repo. When you point Remyx at a repo, it runs a research pass that answers those questions and stores the result as a research brief that both ranking and drafting read from.

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Research briefs

A research brief is a typed, cited summary that Remyx produces and stores section-grained for a repo, so each section is addressable on its own. A brief contains:
SectionWhat it holds
Domain framingWhat problem space the repo sits in and why it matters
Approaches surveyThe methods in use across the field, with tradeoffs
Future directionsWhere the work could plausibly go next
Candidate changesConcrete, implementable changes worth trying
CitationsThe sources behind every claim above
Because the brief is typed and cited, ranking and drafting can pull just the section they need, and you can trace any claim back to its source.

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How briefs are created and used

A brief is created automatically when you create a Research Interest from a GitHub repo. Remyx runs the deep-research pass in the background; you don’t trigger it separately. Once stored, the brief is used in two places:

Recommendation ranking

The brief’s future directions become a forward-looking ranking axis alongside your shipping history, so the feed can weigh where the work is headed. The candidate changes seed recommendations directly.

Automated-PR drafting

When Remyx’s automated discovery PRs (a feature called Outrider) draft an implementation against your repo, the stored brief is part of the context they work from, alongside the recommendation and your repo’s history.

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The Remyx bot

You can ask about a brief and a run from the pull request or issue itself: any PR or Issue that Remyx’s automated discovery PRs (Outrider) opened.
1

Mention the bot

In a comment on such a pull request or issue, mention @remyx-ai (aliases @remyxai and @remyx also work) and ask your question.
2

It acknowledges

The bot posts a 👀 reaction so you know the mention was picked up.
3

It replies once

It posts a single grounded reply as remyx-ai[bot], retrieved over the stored research brief plus that run’s telemetry: the recommendation runs, their outcomes, and rejected candidates.
Because it answers from the brief and the run’s own telemetry, you can ask things like:
  • “Why was this recommendation surfaced over the others?”
  • “What did the brief say about alternatives to this approach?”
  • “Which candidate changes were considered and rejected for this run?”
The Remyx bot is read-only this phase. It answers questions; it does not take write actions, edit code, push commits, or change PR state. A human stays at every decision.
It only responds when all of these hold:
  • The comment mentions the bot (@remyx-ai / @remyxai / @remyx).
  • The comment is on a pull request or issue that automated discovery PRs opened.
  • The permission check passes.
If any condition fails, no reply is posted.
A recommendation is only actionable if you can find the code behind it. Two background steps make more papers implementable. Both need nothing from you and run at ingest.
For a paper with no code link, an enrichment agent traverses the arXiv abstract and HuggingFace papers pages through to project pages, classifies the URLs it finds, resolves licenses, and recovers GitHub, HuggingFace, and SPDX links back into the paper record. Existing fields are left alone; it only fills empties.
More papers then arrive with a named reference repo already attached. That is the difference between a recommendation you can act on now and one you’d have to go find the code for first.

Feed

Repo-backed interests trigger a brief that feeds ranking

Automated discovery PRs

The scheduled agent (Outrider) that drafts PRs from the brief

Continuous Experimentation

How discovery, briefs, and implementation form a loop