Quellbot review
Verdict-based GitHub reviews with severity findings, fixes, and CI diagnostics.
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Quellbot is an AI code review and development assistant focused on GitHub pull requests. It examines correctness, security, conventions, and tests, then posts approval, request-changes, or comment verdicts. Findings are grouped by severity, with per-file walkthroughs and committable suggestions for concrete fixes. Teams can request a review with a /review comment, configure repository instructions and ignore rules, and retain control of merges because Quellbot does not merge pull requests. Its fit is strongest for small and mid-market GitHub teams that want structured review outcomes and CI assistance in one workflow.
Pricing has two clear tiers. Free costs $0 monthly for public repositories and includes fixes, reviews, CI triage, and replies; it uses your own runner and credential. Pro costs $29 per month, unlocks private repositories, and allows unlimited teammates without a seat count. Model spend is billed by your provider, so the subscription is not the only potential cost. Quellbot integrates with GitHub, Claude Code, OpenAI Codex, and Fly.io. Reviews can run through Claude Code or OpenAI Codex on ephemeral machines in the customer’s Fly.io account, which gives teams a defined path for connecting their preferred model tooling.
The standout workflow is iterative review: after new commits, Quellbot reports fixed, open, and new findings rather than repeating a static report. Its GitHub Actions explanations add likely causes and next steps when a run fails, while issue assignments can be turned into pull requests. Setup therefore depends on supplying model credentials and a Fly.io account, with those services billed separately, and support is provided by email. Choose Quellbot if your repositories are on GitHub and you value verdicts, actionable fixes, and review deltas. Consider another tool if you need broader code-host coverage or do not want to manage external model and infrastructure accounts.
Quellbot pros and cons
- Where it wins
- Severity-grouped findings with per-file walkthroughs
- Committable suggestions and delta re-reviews for new commits
- Explains failed GitHub Actions runs with likely next steps
- Where it doesn't
- Supports GitHub repositories rather than multiple code hosts
- Customers provide model credentials and a Fly.io account
- Model usage and Fly.io costs are billed separately
Quellbot fact sheet, pricing and score →
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