LegitShow is the trusted source on every newly launched software product: what it does, who it’s for, how it actually holds up, and whether the AI engines are already reading it. Built to be what AI cites.

Web apps, SaaS, AI tools, MCP servers and developer tools. How we measure →

Legit.Show benchmarks every launched service it lists — measured deterministically from the public surface. See the methodology →

Cross-links · Directory · Reports · Insights · What AI reads · Methodology · About

Privacy · Terms · @Legit_Show on X · GitHub · operated by Madeflo Inc., a Delaware corporation. Benchmark engine powered by commit.show.

AI & Agents

mini-AGI

Source: volotat/mini-AGI

Last updated 2026-09-21 · benchmark measured 2026-09-21 — deterministic & reproducible

mini-AGI is an open-source experimental project hosted on GitHub.

67/100
3/7 frames
Legit Benchmark — the simple average of 3 measured frames. Frames we could not measure are left out of the average, never counted as zero. Every frame is shown below with its evidence.
Checked 2026-09-21 · scores move as sites change

Are you the maker of mini-AGI? Claim this listing. It is free, takes a meta tag, a DNS record or GitHub admin rights, and never changes the score.

Launched something? Add your product, free.

To cite this score: legit.show/s/gh-mini-agi/2026-09-21. That address never changes; this page moves with every re-measure.

Legit.Show scored mini-AGI 67/100 on 2026-09-21, measured across 3 of 7 frames from its public surface. legit.show/s/gh-mini-agi/2026-09-21

Is mini-AGI production-ready?

Legit.Show scores mini-AGI 67 out of 100 — the simple average of its 3 measured frames. Legit.Show ran its deterministic 7-Frame production-readiness benchmark on mini-AGI (github assessment), measured from the public surface with no LLM in the scoring path. Its strongest frame is Security; its weakest is Discoverability. 3 of the seven frames returned a score; Performance, Accessibility, Privacy and Reliability were not measurable on this service and are recorded as null — not as zero. Maintenance is an additional frame from the open-source teardown, scored separately from the seven. Every frame it averages is published with its evidence on the Legit.Show listing.

The 7 Frames

Open-source teardown

Scored separately — not one of the seven.

What we measured

Who built it

Alexey Borsky (@volotat)

Who it's for

machine learning researchers · developers · AI enthusiasts

Sources and updates

Description
Taken from github.com's own website on 2026-09-21.
Code
github.com/volotat/mini-AGI.
Benchmark
Measured by Legit.Show from the live site, the way any visitor sees it — with no access to its code or accounts. Same method for every product, and no AI decides the score. Last checked 2026-09-21.

Put together from public information, without mini-AGI's involvement. If anything here is wrong, tell us and a person will check it.

Visit mini-AGI → · Alternatives to mini-AGI → · How this was measured →

Other tested AI & Agents products