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A cloud coding agent for your backlog. Assign a Linear issue or label a GitHub issue; it writes the code in an isolated sandbox, runs your tests, opens a pull request, and reviews its own diff. Free: 1 task at a time, plus 1 queued.

TRASH: Vibe Check
VibeScan
Turn an AI-built repo into a production-ready launch checklist.

Which is more popular?
Website, pricing, platforms and company facts side by side.
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| Website | sinatra.dev | viberaven.dev |
| Pricing | ||
| Company | — | 2026 |
| Listed in |
In their own words, as submitted to SaaSHub.


Sinatra is a background coding agent for teams on Linear and GitHub. Assign a Linear issue to Sinatra or add the sinatraai label to a GitHub issue, and it works the ticket in an isolated cloud sandbox: it reads the code, writes the change, runs your tests, reviews its own diff and opens a pull...
VibeRaven helps builders check whether AI-built apps are ready for production before launch. It reviews the repo evidence around auth, payments, environment variables, deployment, database rules, webhooks, error monitoring, and common “works locally but breaks in production” risks, then turns the...
What each product offers, as listed by its team.


An editorial look at what each product does well and who it suits.


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Walkthroughs and reviews on video.
Sinatra demo: GitHub issue to pull request, end to end (22 seconds)
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As answered by people managing Sinatra.dev and VibeRaven.dev.
Sinatra.dev's answer
It runs on the model subscription you already pay for. You assign a Linear issue or label a GitHub issue, the agent does the work in its own isolated sandbox and comes back with a pull request, and the model bill goes to your own Claude or ChatGPT subscription or API key. Sinatra never bills for model usage. The free plan is 1 task at a time, plus 1 queued, with no daily limit and no card. Pricing was the reason we built it in the first place, the agents we tried billed in credits you couldn't predict.
VibeRaven.dev's answer:
VibeRaven is built for the moment after an AI-built app “works” but before you trust it with real users. Most tools review code quality or monitor errors after launch. VibeRaven looks for launch gaps before launch: missing env vars, weak auth assumptions, webhook problems, RLS issues, deployment risks, and the boring production stuff AI builders often skip.
Sinatra.dev's answer
Pricing and entry points. Plans are one flat monthly price for the whole workspace, any number of people: Pro is $20/mo for 3 tasks at a time, plus 10 queued, and inference runs on your own Claude or ChatGPT subscription or API key, so Sinatra never bills for model usage. And it works from Linear issues as well as GitHub, so a team whose tickets live in Linear can assign work to the agent the way they'd assign a teammate. It also reviews its own diff and posts the findings on the PR, fixes failing CI, and pushes revisions when a reviewer leaves comments. To be honest about the limits, it only works from GitHub and Linear issues today, and the agent never merges its own PRs, a person does that.
VibeRaven.dev's answer:
Choose VibeRaven if you are not looking for another generic code review. It is more focused: “Can I ship this AI-built app without obvious production mistakes?” The output is a short checklist and a fix prompt, so you can go straight back to your coding agent and clean up the highest-risk gaps.
Sinatra.dev's answer
I built a pet sitting marketplace with my wife. She always had features she wanted shipped and every one of them went through me, so I spent about three months building an agent she could assign tickets to instead. She writes the ticket, assigns it, and a PR comes back. She's now a big contributor to that codebase without me being in the way. I started handing it my own backlog too and eventually it turned into a product. It has been a lot harder to build than I expected, lots of edge cases, which is why it only works from Linear and GitHub issues right now and why the agent doesn't merge its own PRs, you still do that last part yourself.
VibeRaven.dev's answer:
VibeRaven came from a simple problem: AI makes it much faster to build an app, but it also makes it easier to miss production details. The app can look finished while auth, billing, deployment, webhooks, or database rules are still fragile. I wanted a tool that checks those gaps before users find them.
Sinatra.dev's answer
Small engineering teams and solo founders with a backlog of well specified tickets they never get to: reproducible bugs, small features with acceptance criteria, the work that is clear enough to hand off but keeps getting pushed behind bigger things. Teams already working out of Linear or GitHub Issues who don't want another tool to learn, and who would rather run agent work on the Claude or ChatGPT subscription they already have than open a new metered account somewhere else.
VibeRaven.dev's answer:
Solo founders, indie hackers, and small teams building apps with Cursor, Claude Code, Codex, Lovable, Bolt, Replit, or similar AI coding tools. It is especially useful when the app is close to launch and the builder needs a second pass on production readiness.
Sinatra.dev's answer
TypeScript throughout. A Fastify API for webhooks and OAuth, a Temporal worker that orchestrates each agent run, Next.js for the dashboard and the site, and Prisma on Postgres. Every task runs in its own Daytona sandbox that gets cloned, worked and torn down. Model access is bring your own: an Anthropic or OpenRouter API key, or a Claude or ChatGPT subscription connected to the workspace.
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