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.
jev_project_context: Evidence-first long-term experiment memory
poiuyjie/jev_project_context
VerifiedResearchDocumented
jev_project_context: Evidence-first long-term experiment memory skill for AI coding agents, with optional Jev decision-model layers. See Jev references and source code.
Repository description: Evidence-first long-term experiment memory skill for AI coding agents, with optional Jev decision-model layers
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/poiuyjie/jev_project_context.gitProject facts
- Relationship to Jev
- Research
- Evidence
- Documented
- Language
- Python
- License
- MIT
- Origin
- Original repository
- Repository status
- Not archived
- Created
- 2026-09-22
- Last code update
- 2026-09-22
- GitHub stars
- 9
- 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.
Two scripts become active once `TYPESAFE_API_KEY` is configured. The simplest way is a `.env` file:
Evidence commit: 52b06f6fc4ebe2ac91d504ffa90bd3eeb9245359
Discovered through: awesome-jev.
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