Overview & Result
Built in Rust, SkillRanker evaluates user intent against hundreds of installed agent skills, utilizing Jev to compute ranked probability scores with sub-millisecond overhead.
How Jev fits in the loop
- Parse installed skill metadata directory.
- Dispatch query to Jev for fast ranking.
- Emit ranked skills to stdout for shell scripts or agent harnesses.
How to reproduce
- Inspect the source implementation at https://github.com/Dicklesworthstone/skillranker.
- Configure local Jev API credentials and register required tool/model bindings.
- Execute test prompts and observe decision latency and routing outputs.
Why this build matters
Provides a lightning-fast system-level skill selector for local agent runners.
Limitations
- Metrics are author-reported from the initial release unless independently verified.
- Requires access to the respective agent framework or runtime environment.
- Generative model execution remains external to the Jev decision step.