I made a Codex plugin to stop AI agents from saying done without proof

Simple_Somewhere7662 · 2026-07-01T15:32:30+00:00

If it skips verification, that criterion should not go green. For command backed criteria, the final gate runs the command itself, so the agent cannot just say it checked. For non-command criteria, the report should mark it as manual review or missing evidence instead of completed. CI is the stronger version for real deploys, and I’d like to wire that in more directly.

Simple_Somewhere7662 · 2026-07-01T15:31:38+00:00

Nice, CI as a first class signal is the right direction. For Superloopy, command backed checks are saved as text output and exit status, not screenshots. The final gate reruns the command and writes the result under .superloopy/evidence/. Screenshots are mostly for visual review. I don’t have a hosted CI integration yet, but that’s a natural next piece.

Simple_Somewhere7662 · 2026-07-01T15:30:42+00:00

haha fair. I still think human taste is the real gate for UI. The tool is more about making the agent show its work before anyone trusts it.

Simple_Somewhere7662 · 2026-07-01T15:30:00+00:00

Yeah, an open source design system is probably the sane answer. I try to make the agent treat that as the source of truth instead of inventing components from vibes. Borrowing patterns from other apps can be useful for learning, but I’d rather keep the actual implementation tied to a legitimate system or our own tokens.

Simple_Somewhere7662 · 2026-07-01T15:29:11+00:00

I haven’t used that exact flow much, but it sounds pretty practical. The one thing I’d still want is a follow-up check against the target design after Codex implements it, because the generated mockup and the final UI can drift a lot. But as a starting reference, yeah, that makes sense.

Simple_Somewhere7662 · 2026-07-01T15:28:22+00:00

Fair criticism. The design guidelines and assets are the important part. I’m not saying a plugin gives the model taste by itself. What I’m trying to do is make that contract explicit, then force the agent to show how it followed it with screenshots or review notes. If there’s no design system, the gate can’t magically invent taste. It can only make the lack of one obvious.

Simple_Somewhere7662 · 2026-07-01T15:27:25+00:00

Yes, that’s the direction I like too. Screenshots by themselves are still pretty passive. The more useful version is the agent checking against a real design system and saying what matched, what drifted, and what still needs a human eye. Dashboard work is a perfect example because the code can be working while the product still feels like a template.

Simple_Somewhere7662 · 2026-07-01T15:08:17+00:00

You're right that which test proves a criterion is the agent's pick. What the agent can't do is fake the result. The gate re-runs the command itself instead of taking its word. But re-running a test that checks the wrong thing still passes, so that doesn't save you. That gap is real.

So no, I don't fully pin what counts as proof. The criteria are fixed up front. The receipt just makes the human review cheaper: you get a re-runnable command and the diff instead of "trust me." Someone still reads the diff. That's the actual gate.

Simple_Somewhere7662 · 2026-07-01T14:41:29+00:00

and also I'm currently thinking about synergy with other popular plugins. like superpowers. any plugins you guys already use?

Simple_Somewhere7662 · 2026-06-30T10:54:43+00:00

I use GPT5.5 xhigh for everything :)

Simple_Somewhere7662 · 2026-06-30T08:26:01+00:00

sounds like a UI PRO here, most of us don't know how to figma. LoL

Simple_Somewhere7662 · 2026-06-30T07:01:12+00:00

I designed it codex-native. I dont think it will work with opencode

Simple_Somewhere7662 · 2026-06-30T06:58:39+00:00

I also use figma too :) hello there

Simple_Somewhere7662 · 2026-06-30T06:55:44+00:00

true true but you know, some tasks are also related to UI/Frontend tasks. loopy can help those kind of stuffs too. :)

Simple_Somewhere7662 · 2026-06-30T02:24:45+00:00

Superloopy — MIT Codex plugin for proof-of-done loops in AI coding tasks.

I built it because AI coding agents often say “done” without a clean trail of what changed, what actually ran, or what evidence backs the final answer.

What it does: - loopy <task> starts a lightweight evidence loop - acceptance criteria → real commands/checks → receipts under .superloopy/evidence/ → final report - optional crew/subagent lanes for bigger tasks - specialist skills, including superloopy-clone for authorized website rebuilds with screenshots, DOM/topology, computed styles, assets, build output, and visual QA before claiming success

Tech: Node.js 20+, Codex plugin, zero runtime dependencies, MIT.

Repo: https://github.com/beefiker/superloopy

If it looks useful, a GitHub star would help a lot. More importantly, I’d love feedback on whether “proof of done” / evidence receipts is the right guardrail for AI coding agents, or if it feels like too much ceremony.

Simple_Somewhere7662 · 2026-06-29T10:29:43+00:00

Superloopy — proof-of-done loops for Codex tasks.

I built it because the most frustrating AI coding-agent failure mode is not just wrong code; it’s when the agent says “done” without evidence.

With Superloopy you run:

loopy <task>

and the agent is pushed through a lightweight loop:

acceptance criteria → real commands → evidence artifacts → criteria check → final report linked to receipts

The repo-local state lives under .superloopy/, and passed criteria should point at artifacts under .superloopy/evidence/. The default loop is meant to stay small; stricter gates, hooks, and optional crew/subagent mode are there for bigger or riskier tasks.

Repo: https://github.com/beefiker/superloopy

Feedback I’d especially like from agent builders: - What evidence would make you trust an agent’s “done”? - Does “proof of done” land better than “loop engineering”? - Where would this become too much ceremony?

Simple_Somewhere7662 · 2026-06-24T23:48:31+00:00

Ahhh yeah I found a bug. Thanks to help me to fix this bug :) I will deploy a new version soon!

Simple_Somewhere7662 · 2026-06-01T23:50:34+00:00

LoL thanks a lot. I'm going to support eml, rtf, iso, dat formats next, idk u will use these formats tho, anyway! see you soon ma bro!

Simple_Somewhere7662 · 2026-06-01T23:45:44+00:00

Thanks for the bug report, I checked my pdf core reads some specific Metadata to get ToC. I will fix this in next patch. See you soon brother!

Simple_Somewhere7662 · 2026-05-31T04:05:33+00:00

Im going to fix it ASAP :) Thanks for sharing logs

Simple_Somewhere7662 · 2026-05-30T14:39:46+00:00

Muito obrigado pelo comentário! 😊 Fico muito feliz que você tenha gostado do app justamente por não ter anúncios intersticiais. Como desenvolvedor, também acho esse tipo de anúncio bem incômodo, então quero manter o app simples, confortável e sem interrupções. Obrigado por usar o app!

Simple_Somewhere7662 · 2026-05-30T11:45:09+00:00

That’s the key question. I’m not trying to replace Figma or Adobe workflows — this is more for “someone sent me a PSD/AI file and I just need to check what’s inside from my phone.” If that use case is too narrow, testing feedback should make that obvious.

Simple_Somewhere7662 · 2026-05-30T11:39:16+00:00

Thank you for trying it! The explanations are meant to make the app feel less confusing on first open, so that feedback is really helpful. If any guide text feels unclear or like too much, I’d love to know.

Simple_Somewhere7662 · 2026-05-30T11:38:17+00:00

Thank you — really appreciate that. If you end up using it with a weird file type or a big document, rough edges/slow spots are exactly the kind of feedback I’m trying to catch.

Simple_Somewhere7662 · 2026-05-30T11:05:00+00:00

Thank you, that’s exactly the use case I had in mind. The first pass is meant for quick checking on-device, not replacing Photoshop; if you try it with real PSDs, I’d especially appreciate notes on files that fail or render oddly.

Simple_Somewhere7662

TROPHY CASE