Opinion page / measured product / rank 17
Convex Chef Reviews and Ratings (2026)
Reader ratings for Convex Chef, aggregated on the same 0 to 100 scale we use for the lab index, with our own commentary underneath. If you are looking for Convex Chef opiniones, reviews or a rating you can check, the measurements behind every claim are on the Convex Chef benchmark page.
Reader index
70.80
3 voters, 26 axis scores. Never blended into the lab index.
Lab index
70.50
Measured on the vibeOps spec
Strict pass rate
60.0%
27 clean and 10 failed executions
Median per prompt
88.7 s
p90 142.4 s
Reader index
One score per reader per axis on a 0 to 100 scale, editable at any time.
Reader index
70.80
Lab index
70.50
3 readers, 26 axis scores, last change 13 Aug 2026. Readers rate Convex Chef 0.3 points above the measurement.
| Axis | Weight | Lab | Readers | Votes | Reader mean |
|---|---|---|---|---|---|
| Agent performance | 18% | 75.0 | 77.7 | 3 | |
| Reliability | 18% | 60.0 | 56.7 | 3 | |
| Scalability | 13% | 84.0 | 85.3 | 3 | |
| SEO and GEO | 12% | 65.0 | 66.7 | 3 | |
| API and MCP | 9% | 82.0 | 82.0 | 3 | |
| Integrations | 8% | 72.0 | 72.3 | 3 | |
| Speed | 7% | 35.4 | 37.7 | 3 | |
| Value | 5% | 78.0 | 79.0 | 2 | |
| Code ownership | 3% | 88.0 | 94.0 | 3 |
The reader index is a weighted mean of reader submitted axis scores using the published index weights, renormalised over the axes readers have scored. It is never blended into the lab index. How this works.
Score Convex Chef
Your scores feed the reader column only. Submitting an axis again edits your existing score rather than adding a second vote.
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Reader scores are published in a separate reader index column. They never move the measured lab index.
Reader lab notes on Convex Chef
Written by readers with an account. Sorted by upvotes, then by date.
The backend did the operational prompts for it
Petra Bergstrom | 10 Aug 2026
Interesting one to score, because a lot of what it got right is not the agent being clever, it is the platform making the wrong answer hard to write. Scheduled work is durable because durable is the default. Reads are consistent because there is no other kind. That is a legitimate way to score well and I gave it full marks on API and MCP for it. Where it struggled was prompt two: expressing the tenancy rule the way the platform wants took me two rewrites, and if you come in expecting a relational schema you will fight it for an afternoon before it clicks.
Marijke Kuipers | 11 Aug 2026
The default being correct is underrated. Most of the incidents I have been paged for were a default that let someone write the fragile version without noticing.
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What you built, what broke, what you measured. Short opinions belong in the open rating form further down.
Open rating distribution
Open ratings submitted without an account. Neither the lab index nor the reader index is part of this average.
| Band | Share | Ratings |
|---|---|---|
| 90 to 100 | 0 | |
| 80 to 89 | 0 | |
| 70 to 79 | 0 | |
| 60 to 69 | 0 | |
| 0 to 59 | 0 |
Lab commentary
Our reading of the numbers, kept separate from the reader ratings.
The reactive backend underneath it does most of the work the operational prompts ask for, so scheduled functions, durable actions and consistent reads arrived without prompting. That is why it posts one of the best API subscores in the cohort despite a middling agent score. Where it struggles is anything conventionally relational: prompt 2 needed rework in three of five runs to express the tenancy constraint the way the platform prefers.
On the measured axes, Convex Chef is strongest at code ownership with a subscore of 88.0 and weakest at speed at 35.4. Because speed carries 7 of the 100 index points, that weakness costs it roughly 4.52 points against a perfect result on that axis alone.
Reader ratings and lab measurements answer different questions. A reader rating carries the thing a harness cannot capture: whether the product was pleasant to work with over weeks, how support behaved, whether the bill matched the plan. The lab index carries the thing an opinion cannot: 45 timed executions of the same specification with the failures counted. Read them side by side and treat a large gap between the two as the interesting signal.
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