Sinatra vs OpenAI Codex
OpenAI's cloud agent: the one that runs tasks in ChatGPT and opens pull requests, not the Codex CLI on your laptop. Compared here on Codex cloud.
Codex cloud is genuinely good at the thing Sinatra does: assign a Linear issue, get a pull request. The catch is that everything runs through one vendor relationship. Your throughput is a ChatGPT plan tier, your models are OpenAI's, and the API-key path that would give you published per-token pricing explicitly turns the cloud features off. Sinatra runs on that same Codex subscription, but also on Anthropic, OpenRouter, or a Claude plan, and it starts from a GitHub issue label, which Codex does not.
- Yes means the vendor's own app starts a run from the issue itself, with nothing to commit to the repo first. Sinatra's trigger is the Sinatra label that ships with the GitHub App install (`sinatraai` on the hosted app). Partial means either that a workflow file and an API-key secret have to be added per repository first, or that the mention only works on pull requests and not on issues.
- Yes means assigning the ticket to the agent in Linear starts the run. Partial means the run starts some other way: an attachment link you click, or a trigger you configure yourself against Linear's webhooks. Assignment on its own does nothing.
- Yes means a changes-requested review is enough on its own: Sinatra reworks the branch and pushes the follow-up commit with no re-trigger and no mention. Partial means the agent acts only when it is @-mentioned in the thread, or only while its original session is still open.
- Yes means your own provider API key runs the agent everywhere the product runs it. Partial means keys work on some surfaces but not the one being compared here, either because the vendor documents them as local-CLI-and-desktop only, or because it never documents them covering its cloud agent at all.
- Yes means a Claude Pro/Max or ChatGPT subscription you already pay for authenticates the run on the vendor's hosted cloud. Partial means it works only where that CLI's login already sits on the machine: your own laptop or a self-hosted backend, not a clean cloud sandbox.
- Yes means you are never charged a marked-up model rate, either because you pay your provider directly, or because the vendor publishes the same per-token rates the provider does, or because model use is included in a flat plan with a published allowance. Partial means the answer depends on which plan you are on: no fee on the individual tiers, a published per-token fee on the team ones, charged even against your own key.
- Both halves have to be published: the plan price, and the rate for work past the plan. A published seat price sitting on top of an undisclosed credit, compute unit, or quota size is partial.
- Yes means the free tier states its daily allowance as a number. Sinatra's is 5 tasks a day with your own key or a Codex subscription, 1 a day on Sinatra's keys, no card. Partial means a free plan exists but its allowance is not published.
- Yes means you can run without supplying a model key at all, because the vendor bills you for the model.
- Yes means an editor plugin or a desktop app; partial means a terminal CLI and nothing that runs inside an editor. Sinatra has neither, on purpose: the work starts in the tracker and comes back as a pull request. If you want an assistant inside your editor, that is a real reason to pick one of these instead, and several teams run both.
- Sinatra has no Slack trigger. GitHub and Linear are the only two ways to start a run, and a Slack-first team should weigh that.
- Yes means you can run the agent on infrastructure you control, or the source is open. Partial means execution or inference can be pointed at your own account while the product itself stays the vendor's and stays closed. Sinatra is hosted only; there is no self-managed build.
Read off each vendor's own documentation and pricing pages on September 4, 2026.
How you start it
- Add the Sinatra label to a GitHub issue. The label ships with the GitHub App install and is named after the app (
sinatraaion the hosted one) - Assign a Linear ticket to Sinatra, or @-mention it in a comment
- Assign a Linear issue to Codex, or mention @Codex in a comment
- @codex in a GitHub or GitLab pull-request comment
- Slack channels and threads
- The Codex web app, CLI, IDE extension, and iOS app
- The openai/codex-action GitHub Action, from a workflow file you commit
$20 per member per month for hosted sandboxes and orchestration, with model cost passed through at provider rates and no markup. Free tier: 5 tasks a day with your own key or Codex, 1 a day on ours. No card.
Sinatra pricing →Included in a ChatGPT plan: Free $0, Go $8/mo, Plus $20/mo, Pro from $100/mo, Business $20 a user a month billed annually ($25 monthly), Enterprise contact-sales. Usage is a rate limit rather than a rate. Plus is documented as roughly 10 to 100 local messages per five hours, and cloud chats use more. An API key runs the CLI and IDE extension at OpenAI's published API prices but unlocks no cloud features.
OpenAI Codex pricing page →How you start a task
On Linear these two are a genuine tie: install the integration, assign the issue, and it reports back on the ticket.
GitHub is where they part. OpenAI's integration is built around pull requests, so
there is no issue trigger in it. You can build one with the openai/codex-action
Action, which means committing a workflow file and storing an OPENAI_API_KEY
secret in every repository that needs it. Sinatra's label ships with the App
install and starts the run from the issue itself.
For a backlog in GitHub Issues rather than Linear, that is the difference between a one-click install and a per-repository project.
What it costs, in dollars
Codex is bundled, not sold, and the agent comes with the plan. What the plan does not come with is a rate. OpenAI publishes an estimate instead, roughly 10 to 100 local messages per five hours on Plus, with the explicit caveats that cloud chats "may use more of your allowance" and that "these estimates are not fixed message limits." Two tickets that look the same to you can consume very different amounts, and the way to get more throughput is to move up a tier rather than pay for what you used.
There is a path with real per-token pricing, and OpenAI's own pricing page says what it costs you: "Codex in the CLI, SDK, or IDE extension" with "no cloud-based features (GitHub code review, Slack, etc.)." Published pricing or the cloud agent, not both.
Sinatra publishes both numbers because they are separate things: $20 per member per month, and your provider's rate for models. If the credential you connect is a Codex subscription, the marginal cost of a task is whatever that already costs you.
Where Sinatra wins
No lock-in to one model vendor. A Codex subscription works, and so does an
Anthropic key, an OpenRouter key, or a Claude plan, pinned per repository in a
committed .sinatrarc. You can change your mind next quarter without changing
tools.
A GitHub issue label starts a run, with no workflow file, no repository secret, and no Action to maintain across twenty repos. Review is the instruction, so asking for changes gets the follow-up commit without a mention; Codex's documented autonomous behavior is reviewing new pull requests, not acting on a review of its own. The free allowance is a number rather than a range and it resets daily. And throughput is not a plan tier: more tasks cost provider tokens at provider rates, not an upgrade from $20 to $100.
Where Codex wins
The models come first. Codex cloud runs OpenAI's newest models the day they land, tuned by the people who made them. If GPT is the family you want, nobody serves it better.
One subscription also covers everything: ChatGPT, Codex in the browser, the CLI, the IDE extension, iOS, Slack, and GitHub review, on one plan and one login, where Sinatra deliberately gives you two invoices. Slack and the web app are real surfaces Sinatra does not have at all. Codex reviews your team's human-authored pull requests on open, with security review as a first-class mode, which is a different job from closing tickets and one Sinatra does not do. And a $0 ChatGPT plan gets you in the door.
Looking for an OpenAI Codex alternative?
Two things bring people here. Model lock-in: a team standardized on Claude cannot point Codex cloud at it, and running two agents to run two model families is silly. And the ceiling: when Plus stops being enough, the fix is a $100 plan rather than a bill that tracks what you used.
Sinatra separates the two purchases. You pay $20 per member per month for the machinery and buy models from whoever you want, including OpenAI, since a Codex subscription is a supported credential. Switching does not mean abandoning what you already pay for, and throughput is bounded by your provider's limits rather than our tier.
If you are here because Codex's GitHub PR review is the part you like, keep it. It reviews your team's pull requests, which the two do side by side.
Switching, or running both
The triggers do not collide: Codex answers @codex on pull requests and a Linear
assignment, Sinatra watches a label and an assignee of its own. The experiment
worth two weeks is the one where both use the same credential. Connect your Codex
subscription to Sinatra, hand each five real tickets, and read the ten pull
requests knowing the model was identical. What you are measuring then is the
harness and the trigger, which is the only part that differs.
Questions people ask about OpenAI Codex and Sinatra
Can Sinatra use my ChatGPT or Codex subscription?
Yes, on the hosted cloud, alongside Anthropic and OpenRouter keys. The free tier is built around it: 5 tasks a day with your own key or Codex, 1 a day on Sinatra's keys, no card.
Can Codex start from a GitHub issue?
Not from OpenAI's GitHub integration, which is scoped to pull requests. You can wire issue events up with the openai/codex-action Action, which means a workflow file and a secret in each repository.
What does Codex cloud cost?
It comes with a ChatGPT plan, and what you get is a rate limit rather than a rate: roughly 10 to 100 local messages per five hours on Plus, with cloud chats using more. Raising throughput means moving up a plan.
Can I use my own OpenAI API key with Codex cloud?
An API key runs the CLI, SDK, and IDE extension at published prices, but OpenAI's pricing page says that path has no cloud-based features. You choose between published per-token pricing and the cloud agent.
Where these facts came from
Every mark on this page was read off OpenAI Codex's own documentation and pricing pages on September 4, 2026, not from a third-party roundup. If something here is out of date or wrong, tell us and we will fix the page.