Slack Agent Skill Routing

Overview & Result

Inside busy Slack channels, agents often delay responses while deciding which tool to call. This build uses Jev as a lightning-fast front router that chooses the skill and fills parameters before the LLM generates prose.

How Jev fits in the loop

1. Listen to Slack message event.
2. Jev evaluates user request against registered company skills in under 50ms.
3. Pass pre-selected tool bindings to agent for immediate response generation.

How to reproduce

1. Inspect the source implementation at https://x.com/johnyeo_/status/2100987661926252737.
2. Configure local Jev API credentials and register required tool/model bindings.
3. Execute test prompts and observe decision latency and routing outputs.

Why this build matters

Demonstrates substantial latency improvements in enterprise chat interfaces.

Reported performance

Latency: 2× speed-up

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.

Patterns