Rejourney Marlin for GitHub

Fix the leaks your replays expose.

Marlin is the Rejourney GitHub App that uses replay context to identify funnel and revenue issues, then suggests code fixes your team can review from the repository.

Rejourney Marlin artwork
Marlin suggestionFound Fix

checkout/PaymentSheet.tsx

+ retry failed intent before empty state

+ guard CTA when plan quote is stale

What Marlin actually uses

The fix starts from the issue Rejourney already found.

Marlin is not a generic code assistant. It starts with Rejourney's issue detection: ranked leaks, replay evidence, affected sessions, and the markdown handoff your team already uses to debug.

Issue detection

First, Marlin watches the ranked leak feed.

Rejourney groups repeated checkout failures, rage taps, broken onboarding paths, and abandoned funnels into signals. Marlin reads the same evidence your team sees: affected users, session count, failure cluster, and why the leak matters.

Rejourney issue detection feed with ranked funnel leaks

Replay context

Then it keeps the exact user session attached.

The repair note is grounded in the replay timeline: user actions, console events, network failures, DOM state, and the specific sessions that prove the leak is real.

Rejourney replay theater showing session timeline and diagnostic context
Rejourney revenue growth dashboard with revenue trend and release markers

Revenue priority

The issue is ranked by business impact.

Marlin can tell the difference between cosmetic noise and a checkout path that blocks revenue. Revenue movement, affected cohorts, and release timing travel into the GitHub suggestion so engineers know why the fix should move now.

Stability evidence

Crashes, ANRs, and API spikes become fix paths too.

When the leak is technical, Marlin uses the same issue feed to connect stack traces, device cohorts, endpoint spikes, and replay context to likely files. The result is a focused repair brief instead of a vague stability ticket.

Rejourney stability monitoring table with crashes, ANRs, API spikes, events, and affected users