Tech debt translated into real engineering hours and dollar cost.
You'd think this needs a senior engineer's gut feel — Astra reads the repo and tells you exactly which 5 fixes pay back the fastest.
Astra answers "how much tech debt do we actually have" by scanning your GitHub repositories for TODO/FIXME/HACK comments, Sentry for recurring errors, deploy logs for failed-then-rolled-back releases, and Linear for tickets tagged debt or refactor — then estimates engineering hours owed. She quantifies it: "~127 hours of debt across 4 repos, costing ~3.2 hrs/week in slowdown." Then she ranks the top 5 items by ROI — picking ones where the fix is small but the ongoing pain is large (a 2-hour fix saving 30 min/week beats a week-long refactor saving 1 hr/month). The output is a Lark message: total debt estimate, weekly drag in hours, top 5 fixes with effort + payback, and the items safe to ignore. You stop debating debt in the abstract and start fixing the ones that pay.
GitHub search for TODO/FIXME/HACK/XXX comments across all repos, file age, last-touched dates.
Sentry top 20 errors by frequency, filtered to the same root cause occurring >5x/week — those are debt symptoms.
Vercel and Cloud Run deploy history for last 90 days — failed deploys, rollbacks, hotfix-after-deploy patterns indicate fragile areas.
Each marker gets a rough hours estimate based on file size, complexity (LOC + cyclomatic), and whether tests exist.
Effort to fix vs ongoing weekly drag. Lark message with total estimate, weekly cost, top 5 prioritized list, plus safe-to-ignore items.
Lark digest with total debt in hours, weekly slowdown cost, top 5 fixes ranked by payback period, and a safe-to-ignore list so you stop second-guessing.
Monthly + on-demand before each planning cycle.
We'll spin up your workspace, hand the prompt to Astra, and you see the answer in 60 seconds. Free.
Try this with AstraClear answers about wallet credit, usage, subscriptions, and how Tycoon charges for work.
She uses file LOC, complexity, test coverage, and historical commit-time signals (how long similar refactors took your team in the past, pulled from git history). Estimates are within ~30% on first run; she calibrates as you mark fixes done.
No — she only flags TODOs that correlate with active errors, recent rollbacks, or recurring on-call pings. A `TODO: cleanup` on a stable file no one has touched in 18 months gets marked safe-to-ignore.
Yes — say "file these as Linear tickets" and she creates one per fix with the estimate, the linked code location, the proposed change, and the payback metric in the description. Assigns to whoever last touched the file.
Override anything: "the inventory bug is actually critical, bump it." She updates her weighting and the next audit reflects your team's judgment. Three corrections usually dial her into your style.