A candidate-scoring head returns distributions for gates, routes and scores without decoding prose or JSON answers. The README compares a benchmark-trained AgentJev specialist with Jev 1.13.0 evaluated zero-shot; these use different training conditions.
typesafe-ai-benchmark — Structured Outputs · Jev
iammrduncan/typesafe-ai-benchmark
VerifiedResearchDocumented
typesafe-ai-benchmark: This is a LLM Gateway that mimics typesafe ai structured output. Explore the Jev references, TypeScript source code and similar projects.
Repository description: This is a LLM Gateway that mimics typesafe ai structured output. Like an imposter Jev.
What you can build with it
Get started
Clone the repository and follow its README for install and usage. JevHunt has not run this project.
git clone https://github.com/iammrduncan/typesafe-ai-benchmark.gitProject facts
- Relationship to Jev
- Research
- Evidence
- Documented
- Language
- TypeScript
- License
- MIT
- Origin
- Original repository
- Repository status
- Not archived
- Created
- 2026-09-16
- Last code update
- 2026-09-19
- GitHub stars
- 40
- Evidence checked
- Sep 29, 2026
- Metadata checked
- Sep 29, 2026
- Check status
- Up to date
Stars measure the whole repository, including work unrelated to Jev.
Evidence and scope
Documented records the linked documentation or source. JevHunt has not independently run or benchmarked this project.
| **Native judgment API** | Jev / TypeSafe | One request batching native Choice/Noul questions, mapped to the same application output |
Evidence commit: cf348cd291bb538ad9fa902334649ef5dd937e92
Discovered through: awesome-jev, typesafe-field-guide.
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